Last Reviewed: November 26th, 2024

Best Embedded Analytics Tools Of 2024

What are Embedded Analytics Tools?

Embedded analytics tools integrate data insights directly into existing software applications or web platforms. Imagine having live sales figures within your CRM or customer behavior charts embedded in your marketing tools. These tools solve the problem of siloed data and fragmented user experiences by delivering relevant analytics seamlessly within workflows. Their importance lies in empowering users with data-driven decision-making at their fingertips. Benefits include improved user adoption of analytics, increased operational efficiency, and deeper customer understanding. Key functionalities involve data visualization, interactive dashboards, and self-service analytics capabilities. Emerging features leverage AI and machine learning for automated insights and predictive analytics. Industries like sales, marketing, finance, and healthcare benefit most, as embedded analytics streamlines data access and analysis for informed decision-making across departments. While limitations include potential vendor lock-in and initial setup costs, the overall value proposition lies in transforming scattered data into actionable insights embedded within familiar workflows, ultimately driving user engagement and organizational success.

What Are The Key Benefits of Embedded Analytics Tools?

  • Seamless data context
  • Improved decision-making
  • Boosted user adoption
  • Enhanced operational efficiency
  • Deeper customer understanding
  • Streamlined data access
  • Self-service analytics power
  • Increased user engagement
  • Data-driven culture adoption
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Our Research Analysts evaluated 36 solutions and determined the following solutions are the best Embedded Analytics Tools overall:

Overall

Dundas BI  Award
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Why We Picked Dundas BI

Dundas BI is a web application that stands out for placing the buyer first with built-in ETL, shared licenses and unlimited refreshes. It surpasses market leaders like Power BI and Qlik Sense in native functionality. It’s feature-rich, with 77% of capabilities available out of the box.

About 72% of users reviewing the interface praised the platform, whereas others felt it was confusing. An open API architecture might be one reason for the UI's clutter, but the vendor offers a way out. You can make onboarding easier by removing components that seem complex.

Usually, reporting is a loose term for dashboards and static reports and not much else. However, the vendor packs these tools into a neat package at no extra cost. Dashboards are usually static, single-screen views, but Dundas allows embedding reports in them to complement your KPIs. The support team is responsive with clear SOPs and quick responses, and the documentation is detailed.

On the downside, many users felt it slowed when handling heavy workloads. Performance is critical in business, but every data tool has accompanying tradeoffs, and sadly, it’s often speed. That said, keep in mind that many factors are at play here — the hardware, internet speed, data complexity and database efficiency. Consider them for your use cases when evaluating performance, as they significantly impact how a program responds to user interactions.

Ultimately, it boils down to this — how much lag can you accept before it impacts your business? A proof-of-concept or, even better, a trial would be your best bet to assess how the platform fares.

Due to its rich scripting options, the learning curve can be steep. Users felt the feature documentation should cover more information on Javascript and APIs. Most reviewers were satisfied with the pricing, saying it offers value for money.

In summary, Dundas BI is a powerful tool if you need a high degree of customization, scalability and flexibility. It can handle complex data environments and supports many users concurrently. It would be a good fit for mid to large-sized enterprises as they have diverse data needs and are open to investing in training.

Organizations with simple data requirements may find the tool a bit over the top and the cost excessive. In such a case, opting for a tool with basic functionality might be a good start. One non-negotiable would be frequent, stable updates. It'll ensure the tool grows with your business over time.

Pros & Cons

  • Cost: Around 88% of reviewers mentioning pricing said the platform offered value for money.
  • Data Analysis and Visualization: Around 86% of users reviewing dashboards said they helped in decision-making.
  • Service and Support: Almost 83% of users praised support services for being prompt and said they got the help they needed.
  • Functionality: Around 75% of users praised the solution's rich feature set for helping them accomplish their tasks.
  • Ease of Use: Around 72% of users citing user friendliness said they could use it without much difficulty.
  • Training: Around 86% of users citing learning said there was a steep learning curve and documentation was inadequate.
  • Speed: Around 75% of users who reviewed performance said it lagged when handling large data volumes.

Key Features

  • Data Visualization Sandbox: Create and test data visualizations before using them in dashboards. Experiment with different chart types, color schemes and data combinations without risk. It's an excellent learning tool for teams that want to start using data for decisions.
  • Pattern Identification: The Identify Clusters button is a tool within Dundas BI that examines your dataset. It helps you find patterns in your data by clicking a button rather than manually sorting it. The tool puts similar data into groups that can help spot trends or unusual patterns.
  • Small Multiples: They allow you to compare values on the same scale and axes but in separate charts and graphs. One example is comparing the prices of hotels on an aggregator site.
  • Mobile Insight: Collaborate with your teams through an HTML5 browser, whatever the device. Leave comments and annotations for colleagues on visualizations and share them as a PDF or link. Double-tap to zoom into views, and pinch in and out to see maps and charts.
  • Content Scheduling: Share content by setting a schedule or trigger. Dundas BI offers scheduled sharing via the notifications option. Select the content type from among Excel, CSV, PDF, PowerPoint and PNG formats. Choose from email or file delivery. More distribution methods are available if you install Dundas BI extensions.
  • Administrator Privileges: Create, edit and delete projects and configure security settings. Share projects among tenants and assign or revoke permissions as required. Set up and manage user accounts and view login history. Monitor system and warehouse performance and keep tabs on memory storage with application logs.
  • DundasScript: Do more with your data. Write custom formulas and expressions that aren’t possible with standard connectors or visualization tools. Apply conditional formatting and define how users should interact with visual elements, such as setting up drill downs and tooltips.
  • Contextual Views: View only the information that matters to your role. Dundas BI has a data connector override function that switches to a different data source or schema based on who’s viewing the content.
  • Architecture: Dundas BI has JavaScript, HTML and CSS on the back end with a patented in-memory engine. It’s a C#, Asp.NET application hosted on Microsoft IIS for Windows, systemd for Linux or a Docker or Kubernetes container. The platform is available in hosted and managed versions. Supported databases include Microsoft SQL or PostgreSQL. All screens, including dashboards and report designers, are built on a public API with JavaScript or a REST interface. It makes it easy to customize and embed. Tiers include the user, application and data layers. End users get a smooth user experience with drag-and-drop and select actions. It's open to plugins for adding new functions, formulas, controls, and security and tenant and export providers.

Pricing

License/Subscription Cost
  • Dependent on the deployment method and the number of users
  • Offers a flexible license-pricing model and concurrent user licenses.
Maintenance Cost
  • On-premise: Support and maintenance incur additional costs.
  • Cloud-Based/SaaS: Included in the subscription cost.
Installation/Implementation Cost
  • On-premise: Typically charged over and above the license cost.
  • Cloud-based/SaaS: Included in the subscription cost.
Customization Cost
  • This information and section are only included for products in a pricing guide.
Data Migration Cost/Change Management/Upfront Switching Cost
  • Will vary depending on the functional requirements such as configurable dashboards, operational and dashboard reporting needs, type of data elements required for tracking, the complexity of workflows, forms to collect additional data, UI changes, etc.
Recurring/Renewal Costs
  • Dependent on the model opted – an annual lease or own in perpetuity.
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Why We Picked Zoho Analytics

Zoho Analytics is a BI and data analytics software platform that helps users visually analyze data, create visualizations and get a deeper understanding of raw data. It helps users generate dynamic, highly customizable and actionable reports and allows integration with multiple platforms for achieving greater insights. Its multifaceted and customizable dashboards can enhance the user experience. However, many reviewers have reported that the user-interface can be confusing to use with the many options and features available. Also, it has a steep learning curve, and non-technical users might find it difficult to use in the beginning. Overall, it is a user-friendly platform that enables effortless data handling.

Pros & Cons

  • Ease of Use: It is a user-friendly platform that makes it easy to upload and control data, as noted by more than 77% of reviewers who mention ease of use.
  • Integration: Facilitates integration with multiple databases and platforms for greater insights, as reported by 82% of the users noting integrations.
  • Dashboards: It enables easy creation and sharing of multifaceted, custom dashboards, as observed by 75% of reviewers specifying dashboards.
  • Flexible Reports: It helps generate dynamic and customizable reports quickly, as stated by 88% of the users who refer to reports.
  • Implement: This tool is simple to deploy and implement, as noted by 75% of reviewers mentioning the implementation process.
  • Learning Curve: Around 63% of reviewers who mention the learning curve report that it has a steep learning curve for non-technical users.
  • User Interface: Its user interface can be confusing because of the multiple options and features available, as noted by over 54% of reviewers that mentioned the user interface.
  • Limited Queries: All users who refer to queries state that composing and joining queries is limited.

Key Features

  • Geo Visualization: Sales reps can quickly and easily compare regional performance with interactive map charts. Comparisons can be performed across countries, states, counties and more. 
  • Data Alerts: Managers can set alert conditions that trigger automated alerts when there is a significant change or anomaly in the data. 
  • Report Scheduling: Reports can be scheduled to be published or emailed automatically. Also, schedule recurring reports to generate on a set schedule. 
  • Drag-and-Drop Interface: An intuitive drag-and-drop interface makes generating useful reports quick and easy, without the need for code. View underlying data, set contextual filters, perform data exploration and drill down into the data to gain insights. 
  • White Labeling: The solution is white-labeled to facilitate embedding into websites or applications. Use this technology to embed individual reports or dashboards. 
  • Ask Zia: Zia is a smart analytical assistant built out of a blend of AI and machine learning algorithms. Employees can type out questions in natural query language (NQL), and the assistant will offer answers and suggestions via reports or automatically build and source KPI widgets. 
  • Data Connectors: Connects to a broad range of data connectors, including files and feeds, cloud storage, multiple databases, CRM systems, Google Analytics, marketing platforms, social media, financial platforms, e-commerce platforms, HR and more. 
  • Auto-Joined Data: Auto-joining tables can automatically merge tables linked by a Lookup column (schema attribute). This assists and partially automates cohesive database creation. 
  • Mobile Support: Apps on iOS and Android allow managers to view reports and dashboards from their mobile devices and overwatch operations from anywhere. 
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Why We Picked MicroStrategy

MicroStrategy is a patchwork quilt of products on the web, desktop and mobile. There’s MicroStrategy Library where you can access published content and Auto Express for dashboarding and bot creation. Anyone with basic data skills can feed information to a bot and gain insights in seconds.

You don’t need a credit card to sign up for the free trial, but you won’t be able to publish content to the server without a paid upgrade. As for choosing which edition to use, there’s the web and the desktop instance. Which one will suit you? Maybe both?

MicroStrategy Workstation is for developers and data analysts and is more robust for manipulating data. It provides administrative control, even when offline, and helps prototype content before it goes live. Combining multiple visualizations on a single page provided me with more context for the same data.

On the other hand, the Workstation version lacks the same level of natural language processing as the web version.

MicroStrategy Web is for delivering content to your clients. Being online, it’s open to seamless upgrades and customization, and identity management and collaboration are built in. If you have a small organization, the web version might suffice, but you might want to consider going for both if you deal with large data volumes.

Metadata mapping was immensely useful to me when designing a bot using MicroStrategy Auto Express. All I needed to do was feed it the data, and it generated a slew of questions I might want to ask.

With a semantic layer, Microstrategy is among the BI tools that work best with large data warehouses. If you’ve just started in business or haven’t got large data volumes yet, you might want to consider a simpler tool.

An oft-repeated sentiment in user reviews was that this motley crew of products — web, desktop and mobile — didn’t always sync. The vendor positions MicroStrategy One as a unified solution that’ll, hopefully, eliminate these annoyances.

On the flip side, quite a few users said it could be clunky for inexperienced users. Also, some reviewers said it slowed on occasion. Most people said the solution was expensive and found its learning curve quite steep.

In summary, MicroStrategy is worth considering, especially if you’re a medium or large-sized company looking for a web reporting tool with a user-friendly interface.

Pros & Cons

  • Data Visualization: Users were satisfied with its powerful dashboards and personalization options for self-service analytics.
  • Functionality: Reviewers praised the platform for delivering on capabilities and scaling with their data needs.
  • Ease of Use: User reviews appreciated its reusable objects and semantic layer for automating data wrangling and visualization workflows.
  • Cost: A majority of the users found the platform to be expensive.
  • Adoption: Most reviews said the platform had a steep learning curve.

Key Features

  • HyperIntelligence: Learn about departments or employees by hovering over their names. To get ready information, add the HyperIntelligence extension to your Chrome instance and configure it to your MicroStrategy environment.
  • Auto Express: Shift the heavy lifting to AI bots — have them analyze your dashboards and suggest deep-dive questions, many of which you might not have thought of. Pull data from Amazon Redshift, Azure SQL Database, Databricks, Google BigQuery and Snowflake, among others.
  • Action Triggers: Update data in Salesforce CRM, trigger email campaigns in Marketo, or approve expenses in Workday from a MicroStrategy dashboard. Triggering workflows from dashboards is available in MicroStrategy One and Auto Express.
  • Intelligent Cubes Technology: Drive targeted marketing campaigns by digging deep into buyer demographics, purchase histories and engagement levels. Create an Intelligent Cube to store data in memory and reuse it for as many reports as desired.
  • Metadata Management: Organize data using a handy index that points to where everything is. It also gives contextual names to datasets so everyone uses the same terminology. Metadata management establishes data lineage by narrating its entire journey — where it started, how it was changed and which tasks use it now.
  • Role-Based Displays: Remember skimming through your course book a day before an important test? You read the important parts while you skipped the rest. If that’s what you feel when decisions are at stake, role-based views are what you need. CEOs can choose high-level overviews, while middle management might want detailed reports.
  • Free-form Subscriptions: This is a new feature that allows users to view updates as PDF or Excel files without signing in to MicroStrategy. It’s a great functionality for those who are away from their desks and for their teams in the field.

Pricing

License/Subscription Cost
  • On-Premise: It includes an upfront fee for the server software installation.
  • Cloud-based: It includes user-based pricing for the web and mobile-based platforms.
  • CPU-based payment models are also available.
Installation/Implementation Cost
  • On-Premise: Included in the upfront license cost.
  • Cloud-based: Included in the subscription cost.
Customization Cost
  • Dependent on the functional requirements and specific needs of the organization.
Change Management
  • Dependent on the current software, data complexity and volume, availability of migration tools and the gaps between the existing system and the new system.
Training Cost
  • Online training and video tutorials are available free of cost.
  • Enterprises can choose from in-center training, live online lectures, on-demand learning, and private on-site engagements to meet their training requirements. Each day of training costs $700 and most courses are two days in length.
Recurring/Renewal Costs (including maintenance costs)
  • On-Premise: Includes cost for updates, maintenance, upgrades, and patches.
  • Cloud-based/SaaS: Renewal cost is equivalent to the fees paid monthly or annually. The vendor manages upgrades and add-ons at no extra cost.
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Why We Picked Power BI

Our researchers ranked products on a whole bunch of features. They include data management, querying and visualization, advanced and embedded analytics, mobile BI, and IoT and location analytics.

In our rankings, Power BI scores 87 for connectivity, leaving behind Tableau, Oracle Analytics and Dundas BI. Robust Microsoft technology is one reason, for sure. Besides, intelligent techniques like DirectQuery and easy data modeling make it popular among users.

In product reviews, some users mentioned a lag when sharing reports from the desktop to the cloud. For me, the platform was a tad slow to start, but otherwise, it stayed performant for my average-sized dataset.

When dealing with sales data, total sales, the top-performing products, seasonality and period trends are common queries. Creating a sales KPI report in Power BI was an excellent way for me to answer them. My CSV files included sales, calendar, products and store data.

Connecting to sources is straightforward with Get Data on the home screen and toolbar. Once I had pulled in the data, I clicked on Transform Data and opened the Power Query editor. It automatically detects the data type for strings and numbers but can get confused with dates and currency, which it marks as text. It involved some manual wrangling, but I had it sorted in no time. Read my article on KPI Reports to learn how I did it.

But I wouldn’t call it a deal-breaker as it’s not a tedious task. I had the same experience with Qlik Sense, but Tableau was way better as it recognizes seven data types — string, number, date, date and time, boolean, geographic and cluster values.

Tracking sales over periods required a greater level of detail, so I added new columns to the calendar data — start of month and start of week. Column statistics were immensely helpful in identifying unique, distinct and null values and correcting incomplete records. Clicking on the number of products selling at a particular price allowed me to see which toys sold at that price.

Creating a relational data model by defining primary keys is a manual process and seems dated once you’ve used Qlik Sense. Adding calculated measures is where DAX shows its magic. For data workers well-versed with SQL, DAX is a ready-to-go tool they’ll be glad to have in their corner.

Creating visualizations wasn’t as intuitive as Tableau as it involved drag-and-drop onto the canvas, and frankly, I felt like I was flying blind. I didn’t feel that way with Tableau, and it’s slicker.

Power BI offers a paintbrush tool that lets you define the layout, the card arrangement and the maximum number of cards. You can define the canvas settings, background and headers and determine the filter pane settings. It took me longer to create a dashboard from scratch than it took in Tableau.

Some users found the pricing structure too complex. While using Azure data in Power BI for basic queries is free, costs can add up when you go for text and sentiment analysis. With Microsoft Fabric, the pricing complexity is set to rise. Though Power BI is available separately too, you’ll need to rely on Fabric to manage users, licenses and other administrative tasks.

About 31% of the users mentioning cost complained about onboarding difficulties, possibly because DAX introduces the complexity of learning syntax. It can daunt non-technical users initially, but guided formulas can make the task easier. That said, I agree with the majority of user reviews that training will speed up onboarding and help your team maximize the investment.

Overall, Power BI has many powerful features and will give you value for your money. If you’re not a Microsoft user yet, it’s worth checking out for the baked-in vendor technologies like Azure and SSAS. If you are an MS user, Power BI might be a no-brainer, though be prepared to shell out a little extra for advanced functionality and additional modules.

Pros & Cons

  • Integrations: Around 95% of users who mentioned data sources said they were satisfied with its flexibility in connecting to sources.
  • Data Visualization: About 93% of the users who discussed visual analysis said they relied on it for daily reporting.
  • Functionality: Over 75% of the users reviewing features said they were impressed with its live queries, DAX calculations and data modeling.
  • Ease of Use: Approximately 72% of the users who mentioned its UI said it was straightforward to use.
  • Speed: About 95% of recent reviews citing performance said the platform lagged when dealing with large data volumes.
  • Adoption: Around 81.5% of the reviewers mentioning adoption said the learning curve was steep.
  • Cost: Approximately 71% of users discussing pricing complained about the platform being expensive.

Key Features

  • Dataflows: Save time with reusable workflows that lock the logic in. While shared datasets are open to interpretation, dataflows will take your users in one direction only, ensuring consistent results. It’s like a written recipe, just follow the steps to get the taste right.
  • Analyze in Excel: Focus on the end game. Give your teams the freedom to analyze their data in Excel and move the results back to Power BI.
  • DAX: Empower your people to go beyond raw data. Derive calculated columns and measures with Data Analysis Expressions. Watch them update as you apply filters and slicers and interact with data in other ways.
  • Data Alerts: Act in time to keep things running smoothly. Stay informed of changes with alerts. Subscribe to receive notifications via email or the Power BI notification center (available only with Power BI Service). Among visualizations, KPI cards, cards and gauges have the alert option. 
  • Data Refreshes: Stay ahead of trends with the latest insight. Update data on demand in Power BI or schedule refreshes with Power Automate. Power BI Pro and Premium allow up to eight and 48 refreshes daily, respectively.
  • Key Influencers Visual: Decide the next steps by spotting the factors affecting a critical metric. As a transporter, does only the terrain impact how consistently your trucks deliver, or is the average age of the fleet vehicles also a factor?
  • Decomposition Tree: Identify which product category or region contributed most to sales increase or decrease. For instance, you can analyze sales trends by channel with the decomposition tree.

Pricing

License/Subscription Cost
  • Based on the number of users for Power BI Pro and capacity-based pricing for Power BI Premium
Maintenance Cost
  • Included in the subscription cost
Installation/Implementation Cost
  • Included in the subscription cost. Additional charges may apply for data migration during implementation of Power BI, maintaining on-premise data sources and building dashboards and reports
Customization Cost
  • Dependent on functional requirements and specific needs of the organization
Data Migration Cost/Change Management/Upfront Switching Cost
  • Dependent on your current software, amount of data to be migrated, availability of migration tools, complexity of data and gaps between the existing system and the new system.
Recurring/Renewal Costs
  • Renewal cost is included in the fees paid monthly or annually
Tableau  Award
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Why We Picked Tableau

Tableau Desktop is a BI solution for data visualization, dashboarding and location analysis. In online reviews, users said they found its drag-and-drop charting a boon for creating charts and maps. Regarding customization, many users praised the platform for its various labeling and design options.

I recently tried the Tableau Desktop 2024.1.3 version. The trial is only for 14 days and is enough for a sneak peek into Tableau’s dashboarding and data storytelling capabilities. For more straightforward use cases, Tableau is incredibly user-friendly and fast. Creating a new sheet gives you a canvas to create a visualization. Once you have the required sheets, combining them into a dashboard view is straightforward — select and add.

My dataset included healthcare data, including details of patients, their hospital visits and insurance payer details. One use case was to find the total claim settlement amount. I dragged the Total Claims Cost and Payer fields to the column and row shelves, and Tableau gave me a bar graph. The toolbar had single-click options for sorting data from increasing to decreasing values or the other way around.

To view the number of encounters by payer, I dragged the Payer field to the row shelf and used the SUM(ROW_COUNT()) function on the column shelf. The chart popped up with more visualization and layout options.

I wanted an interactive filter to view the average claim cost by birthdate. I dragged the Birthdate field to the Filters shelf and right-clicked on it to set the end date as October 22, 1961. Selecting Show Filter added a slider conveniently to the right of my visualization. I could see the data for people born before October 22, 1961, and if required, I could change the end date.

Another use case would be viewing the data by the type of hospital visits — how many people were inpatients, outpatients or those who needed emergency care. I dragged and dropped the Total Claims Cost and Payer fields into columns and rows, respectively. Similarly, I dropped Encounterclass into the Filters shelf and clicked on Show Filter to enable a checkbox on the screen. It had all the categories of visits, giving users the option to select the desired views.

One-fourth of the users discussing adoption said there was a steep learning curve. Tableau relies on Python and R scripts for statistics in its visualizations. It's where the named licenses can prove to be a blessing, as you can opt to train upcoming Creators and Explorers. We recommend factoring in training if you want to hit the ground running.

Some reviewers felt discounted packages for business editions should be available, similar to the free student licenses. At $70 per user, the Creator license can seem costly when compared to Power BI ($9.99 per user) and Qlik Sense ($30 per user).

Here's the good news, though. Its built-in user management acts as a permissions layer for your organization - users can only access the relevant content. Plus, an organization will have very few Creators and a greater number of Viewers and Explorers, and the license fee reduces from Creator to Explorer to Viewer.

We recommend opting for a wise license combination to get the most out of the product.

On the upside, the vendor constantly releases new features, the latest one being Einstein CoPilot in beta.

Overall, Tableau is a competitive BI solution, but if the pricing seems inflexible, quite a few other solutions offer live insights and advanced analytics out of the box.

Pros & Cons

  • Data Visualization: Almost 98% of users who reviewed its visual capabilities praised the platform for its dashboards and the freedom to play around with data and modify charts as desired.
  • User-Friendly: According to 93% of users who mentioned ease of use, it makes data accessible with its easy user actions and handy tooltips.
  • Data Connectivity: About 92% of users who discussed data sourcing praised its ability to pull data from disparate systems.
  • Pricing: Around 90% of the users citing cost found it expensive.
  • Speed: About 71% of the users who discussed performance found it slow when processing large data volumes.
  • Onboarding Woes: Approximately 67% of the users who reviewed the platform's adoption said there was a steep learning curve.

Key Features

  • Connectors: Combine data from various sources by choosing from a wide range of connectors — no need to spend on expensive third-party data integration tools. Tableau Bridge connects private networks to live data sources via Tableau Cloud.
  • AI: Tableau now offers AI capabilities thanks to Einstein Analytics.
    • Tableau Pulse: Explore data independently and ask questions with AI analytics. Tableau Pulse is available with Tableau Cloud and Embedded Analytics.
    • Explain Data: Understand the displayed insights with natural language explanations of data points.
    • Einstein CoPilot (Beta): Close the gap in understanding data with AI insights. Discover hidden trends by asking follow-up questions without losing context, thanks to generative AI. Einstein CoPilot is available with a Tableau Cloud subscription.
  • Tableau Prep: Clean and transform data of all types, including survey results, feedback data and social media posts. Shape and combine it with Tableau Prep, which is available with the paid edition only.
  • Data Stories: Convey your message with compelling narratives to get stakeholder buy-in. Drag and drop sheets onto the storyboard to show the growth, decline or stability of critical metrics.
  • Animations: Explain how data changes over time with animated charts and customize them to include graphics, labels and colors.
  • Filtering: Focus on the data that matters; it’s as easy as dragging and dropping desired fields to the Filter shelf. Specify a value range, set a condition or choose the top values to display.
  • User-Based Licenses: Explore cost-effective license combinations that work for your team.
    • Creators can build dashboards, permissions, and governance rules, and establish connections to new sources. They’re content authors who transform and analyze data. This license is available at $70 per user monthly, billed annually. However, they can’t control the Tableau Server or Desktop environment.
    • Explorer licenses are suitable for line-of-business users whose role requires independent data exploration. They can author content but within a governed ecosystem. Each Explorer license costs $42 monthly, billed annually. They can’t connect to new sources, modify data, or use the Tableau desktop or custom SQL.
    • Viewers can interact with data, apply filters and follow pre-decided workflows. This license is available for $15 per user monthly, billed annually. Viewers have limited rights and can’t create and edit visualizations and the underlying data.
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Why We Picked Domo Everywhere

For users with typical embedded analytics needs, Domo Everywhere presents a mixed bag. Fans rave about its ease of use and visual storytelling tools, enabling anyone to explore data without coding - "Like having a personal data chef," gushed one reviewer. Its ability to unify data from various sources is another major pull, breaking down silos and offering "a single source of truth" for complex operations. However, Domo isn't without its detractors. Some find the learning curve for advanced features like custom visualizations "steeper than a Matterhorn climb," requiring technical expertise beyond basic analysis. Concerns also linger about its offline capabilities, with internet connectivity still crucial for most functionalities - "a deal-breaker for field teams," noted another user. While pricing starts reasonably, advanced features and high data volumes can quickly inflate costs, making some feel Domo becomes "pricey for its complexity" compared to alternatives like Looker or Tableau. Ultimately, Domo Everywhere shines for its intuitiveness and data unification, empowering non-technical users with valuable insights. However, its limitations in offline access, advanced features, and potential cost escalation leave some users yearning for a more well-rounded package. As one reviewer put it, "Domo is like a Ferrari: powerful and flashy, but not everyone needs a race car for their daily commute." So, if your embedded analytics needs prioritize accessibility and a holistic view, Domo could be your champion. But for those needing robust offline functionality, advanced customization, or a more budget-friendly option, exploring other contenders might be the wiser route.

Pros & Cons

  • Empower non-technical users: Drag-and-drop interface and visual storytelling tools let anyone explore data without coding.
  • Break down data silos: Unify internal and external data sources for a holistic view with 1,000+ pre-built connectors.
  • Real-time insights and alerts: Monitor key metrics and identify trends instantly with live dashboards, driving faster decision-making.
  • Enhanced collaboration: Share dashboards and insights easily, fostering data-driven discussions and alignment across teams.
  • Scalability and flexibility: Adapt to your evolving needs with a cloud-based platform that grows with your data volume and user base.
  • Steep learning curve for advanced features: Custom visualizations and scripting require technical expertise beyond basic data exploration.
  • Limited offline functionality: Data access and analysis primarily relies on internet connectivity, with some offline capabilities still under development.
  • Pricing for complex needs: While base costs are reasonable, advanced features and high data volumes can significantly increase the price tag.
  • Data transformation limitations: Magic ETL simplifies basic processing, but complex data manipulation may require additional tools or coding.

Key Features

  • Data Visualization: Create intuitive visualizations using different chart types, including line, filter, bar, area, stacked bar charts, gauges, maps and more. Add tooltips and apply page-level filters to gauge insights. Create multi-period projections to convey predicted changes.  
  • Data Transformation: Leverage a drag-and-drop interface to pull data from multiple sources, process and transform it. Leverage Magic ETL to schedule data pipelines, map values from one column to another and add, combine or split columns in the dataset. Use SQL-based ETL to build and automate complex data pipelines. 
  • Automated Data Discovery: Receive AI-powered data insights through deep learning and a descriptive stats module. Ask questions in natural language and get instant responses via chatbots. Create custom alerts to define thresholds, monitor information and track key changes.  
  • Data Governance: Create entitlement policies and manage custom roles to grant data access to authorized groups and individuals. Develop workflows that enable content owners to certify content as authentic and trusted. Formulate standards based on user attributes rather than individuals. 
  • Embedded Analytics: Prescribe chart-specific interactions to allow users to filter content, drill down into specific details and link to other elements. Offer personalized data access to enable users to view relevant information. Create robust paths to dive deeper into complex hierarchical data. 
Start Price
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Why We Picked Looker

Looker is a forerunner in the business intelligence field for a reason; it generates reports that include easy sharing via link, automatic scheduling and a level of granular detail that allows for deeper analysis below the surface. It excels in its filter and drill-down features and creates unique URLs when users make changes to data, leading to enhanced sharing. However, one of its biggest strengths could also be considered one of its biggest weaknesses: its proprietary programming language, LookML which is used to construct SQL queries in the platform. While a flexible and powerful data querying language, of course, LookML isn’t the most accessible to non-technical users, which means that Looker requires an IT or data team to access its full capabilities and has a steep learning curve. Users also note that its data visualizations, while simple and easy to understand, are quite basic and lacking in customization options, particularly in comparison to competitors. Some users say that it may be more appropriate for internal reporting than presentation to shareholders and end-users because of its bare-bones visualization options. However, Looker truly shines when used by enterprises, with its scalability and data accessibility making it a stellar solution that can align departments and provide thousands of users access to data insights. Its price point reflects this, with its pricing being prohibitive to startups as about 88% of users who comment on its cost remark. Overall, Looker is a solid pick for larger businesses that have a team of power users who can maximize its functionality and set it up to deliver to employees across an entire organization.

Pros & Cons

  • Reporting: Looker features strong reporting features that offer a degree of granularity and scheduling that 100% of users who mention reporting evaluate as a strong benefit.
  • Support: Of the users who say they’ve contacted customer support, 95% say the team’s quick and informative responses are a plus.
  • Data Accessibility: All users who mention accessibility to data say Looker does this well, distributing insights to employees across departments and teams with ease, with 100% of users mentioning this feature believing it is a benefit.
  • Learning Curve: About 74% of users who touch on the platform’s ease of use say that the confusing documentation, lack of training opportunities and difficulty of using programming language make Looker a tough tool to pick up as a beginner.
  • Setup: Of the users who mention implementation, 81% say that setting up the platform is difficult, with integrations not being as plug-and-play as competitors and assistance from IT necessary to the setup process.
  • Speed: Approximately 87% of users who comment on the platform’s speed say that it is slow to render certain queries and often takes a while to load.
  • Functionality: About 78% of users who talk about Looker’s features say that they are left wanting many functions and find the ones that it does have limited in customization or too complex to use easily.

Key Features

  • Automated Modeling: Connects to relational databases and automatically generates models from the database schema.
  • Intuitive Visualizations: Generates visualizations in real time directly from the specified data source. Choose from an expansive library of visualization options like bar graphs, pie charts, Sankey diagrams, spider web charts, sunburst graphs, chord diagrams, heatmaps, funnels, treemaps and many more.
  • Time Zone Handling: Incorporates data seamlessly into the visualization, regardless of what time zone it is coming from.
  • LookML Data Modeling Language: Create scalable, reusable data models through the proprietary SQL-based data modeling language LookML.
  • Pre-Built Analytics Code: Use its Blocks feature as a starting point for building data analytics models with customizable code blocks. Includes optimized SQL patterns, custom visualization options, pre-built data models and more.
Sisense  Award
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Why We Picked Sisense

Users appreciate how Sisense creates large datasets from constantly evolving data sources to be seamlessly streamlined into actionable data, and presented easily in the form of graphs, bar and pie charts, scattergrams, line graphs, interactive maps and many more visualization types. Regarding customer support, users praise their prompt and informative responses - from implementation to handling subsequent queries — as high quality customer service that comes neatly packaged with pricing plans.
Users mention that the implementation of this solution, though easy for basic setup, can be quite demanding in terms of scripting and configuration setup, especially for advanced analytics. Non-technical users might find it challenging to set up the data objects - ElastiCubes - without strong IT support. On the front-end, dashboard customization and formatting of visualizations can be tricky as these require basic knowledge of CSS, Javascript and development. Though a large number of users find this solution to be cost-effective, smaller businesses and startups that only need a limited number of licenses might find it expensive.
Overall, Sisense is a strong BI solution with strong data capabilities, and its drill-down functionality empowers users to glean insightful and actionable analytics that drive business strategy by aiding in decision-making processes. To maximize its potential, businesses may require strong IT support for implementation and formatting of visualizations. It is certainly worth considering for enterprise BI needs, if the price is right!

Pros & Cons

  • Customer Service and Support : More than 92% of users mentioning customer support said that responses to their queries were prompt and informative, and that there’s good access to online user communities.
  • Data Integration: Approximately 92% of users who mention data source integrations express satisfaction with its ability to import, blend and streamline data from multiple sources into a cohesive database.
  • Data Visualization: Citing stunning dashboards with a range of visually powerful visual tools like widgets, graphs and scattergrams, 85% of users who mention data visualization say it’s a strong feature of Sisense.
  • Ease of Use: More than 93% of users mentioning the platform’s ease of use praise it as user-friendly, citing self-service BI features such as interactive dashboards and data visualizations.
  • Cost: Among users who comment on its pricing, more than 85% said that Sisense offers great value for its cost, with some reviews coming from long-time customers.
  • Data Preparation and Modeling: About 50% of users who mentioned data modeling say that it is not as intuitive for non-technical staff, requiring strong IT support.
  • Training: More than 60% of users who write about learning how to use the platform say that with frequent new releases, a lack of sufficient documentation, coupled with the difficulty of using a programming language make this a tricky tool to master.

Key Features

  • In-Chip Analytics: Free up processing power for other tasks, improve the speed of processing and reduce downtime caused by overworked RAM or disks. Combine a columnar database with smart algorithms in an in-chip cache. Choose between either disk or RAM, rather than solely disk or RAM, as an alternative to in-memory processing.
  • Data Connectivity: Draw from many different data sources and formats with hundreds of built-in connectors with cloud applications such as Zendesk and Salesforce. Drag and drop to import from databases and spreadsheets. Pull directly from CRMs or embed the BI interface into the CRM, providing versatility in workflow options.
  • Data Blending: Blend huge datasets from a range of sources instantly into one centralized location, and receive a holistic view of all data. Investigate further through slicing, dicing and exploration of data via a simple, accessible interface.
  • Data Visualizations: Organize user data into easy-to-understand visualizations like bar charts, scattergrams, pie charts, line graphs, interactive maps, etc. Access a rich library of prebuilt graphics and widgets or open source designs, and easily manipulate them from within an intuitive UI. 
  • Interactive Dashboards: Drag-and-drop to build interactive dashboards that encourage deeper data exploration. Help users to build widgets and filters, and leverage AI-assisted exploration and automatic analysis to provide further insight. 
  • Real-Time Insights: Set up and maintain live connections to data and monitor dashboards in real time. Establish push notification alerts to receive automatic updates when changes to KPIs occur. 
  • Single-Stack System: Perform a range of data preparation tasks, such as exploration, analysis, visualization and collaboration, without needing to switch to other platforms.
  • Publish and Share: Enable everyone in an organization to access and filter information with web-based dashboards. Publish a dashboard with one click and open it to the entire company for easy access without needing to download files.
  • Augmented Intelligence: Leverage Sisense Pulse, powered by machine learning algorithms, to continually monitor KPIs and receive proactive alerts when anomalies and variations are detected. Automate previously manual tasks and data-driven workflows, personalize the BI experience with a tailored command center and deliver a dynamically updated feed that keeps users up to date.
  • Embedded Analytics: Turn data into data products that deliver BI to clients with a white label solution in Product Teams.
  • R Integration: Perform predictive analysis and access better BI reporting and decision-making through R programming language.
  • Add-Ons: Extend the functionality of the platform by downloading and equipping any number of free and premium native and third party extensions from the marketplace.
  • Natural Language Processing: Empower users of all data literacy levels to derive the full value of their insights through natural language generation with Sisense Narratives. Simplify into everyday language the complexities of data analysis for accessibility and easier understanding through AI-generated text-based insights.
  • Mobile BI: Access BI on-the-go directly from iOS and Android phones with a native app that renders mobile-optimized responsive dashboards with touchscreen integration. Alternatively, access the platform through a browser from any laptop, tablet or smartphone, no downloads or installation required.

Pricing

License/Subscription Cost Annual license cost is based on tiers depending on the number of users. The first tier allows up to 10 users (Basic). The second tier (Business) supports up to 50 users, and the third tier (Business+) supports an unlimited number of users
Maintenance Cost

There are no additional costs for training or to maintain the software

For each pricing plan, there are free levels of support

Installation/Implementation Cost The solution can be implemented in a short span of time as there are no additional hardware or servers to set up
Customization Cost Dependent on functional requirements and specific needs of the organization
Data Migration Cost/Change Management/Upfront Switching Cost Dependent on your current software, amount of data to be migrated, availability of migration tools, complexity of data and gaps between the existing system and the new system
Recurring/Renewal Costs Renewal cost is equivalent to the fees paid annually
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Why We Picked Infor Birst

Infor Birst is an integrated cloud-based end-to-end solution for sourcing raw data, and extracting, warehousing and reporting for enterprise data analysis. With built-in tools for data integration and strong embedded analytics capabilities, users leverage its data visualization capabilities to create and share metric-specific dashboards and reports. Users who reviewed data management said that automated data warehouse creation was a strong feature of the platform, as well as its user-friendly interface. Many users who reviewed its functionality said that, equipped with a powerful ETL and efficient ODBC drivers for integration, the platform was flexible and scalable with a multitude of features for data discovery and analysis. Around 69% of users who reviewed ease of implementation said that deployment was easy with the integrated cloud platform, though some users said that the setup processes were unclear and they required in-house IT support for onboarding.
On the flip side, users who mentioned performance said that the speed of data processing and data refresh was slow and this impacted report generation capabilities. Documentation was inconsistent and often incorrect, and the use of proprietary query language made the learning curve quite steep, many users who reviewed this feature said. Support turnaround times were woefully long, even extending up to several months as reported by a number of users. Some users who reviewed functionality said that the code was buggy and the platform stalled often when processing data for ad-hoc reporting. Many users complained that these bugs were not addressed for years, and new releases often impacted pre-existing features. Possibly because of its performance issues with large amounts of data, quite a few users rate it as a good BI tool for small and midsize companies that require less complex data analysis, rather than larger enterprises.
In summary, Infor Birst is a BI ecosystem with a networked approach to data visualization and predictive analytics that eliminates data silos and serves as a single source of truth for enterprise data.

Pros & Cons

  • Data Integration: About 80% of users who mentioned its data integration capabilities said that the platform, powered by built-in connectivity tools, connected well to many types of data sources.
  • Data Visualization: Approximately 81% of users who reviewed visualization said that the tool provided attractive and intuitive data presentation options for at-a-glance data analysis and trend charting.
  • Ease of Use: The platform was user-friendly and intuitive, according to around 77% of users who reviewed the interface.
  • Functionality: Approximately 68% of users who reviewed functionality said that the platform provided strong capabilities to streamline preparation and consumption of data for developers and end users alike.
  • Data Management: Automated data warehouse creation made data modeling a breeze, around 65% of users who reviewed the platform’s data management system said.
  • Setup: Around 69% of users who mentioned implementation said that the solution being cloud-based, coupled with excellent onboarding support from the vendor, made deployment easy.
  • Performance: Approximately 87% of users who reviewed the platform’s performance said that it was slow and inconsistent in data processing and data refresh.
  • Learning Curve: About 81% of users who mentioned the learning curve said that documentation was often insufficient and incorrect, and that the platform’s use of proprietary language made the learning curve quite steep.
  • Service and Support: About 46% of users who reviewed this feature said that support was poor and turnaround times were painfully long, extending up to several months.

Key Features

  • Automated Data Refinement: Automatically merge data from different sources into one user-ready data storage and optimize it for analysis. 
  • Semantic Layer: Boosts trustworthiness of data and reduces data anarchy by adding an agile semantic layer between the user and data. Work with data privately while staying connected to the network via a virtual tenant space.">
  • Real-time Access: Directly query on-premise data sources in real-time, eliminating the need to first extract and then upload data to the cloud.
  • Adaptive UX: Create reports and dashboards without coding knowledge via intuitive drag-and-drop tools. Supports different analytic styles, such as visual discovery, and mobile, and third-party tools such as Excel, R and Tableau. 
  • Reusable Rules: Automatically generates a common architecture based on a reusable set of business definitions without manual intervention.
  • Interactive Dashboards: Explore data even further via interactive dashboards that have drill-down capabilities such as lasso filters.
  • Multi-Tenant Cloud Architecture: Scales vertically and horizontally with a multi-tenant architecture built on a multi-node environment. Speeds insight generation by reducing the overall time spent on repetitive on-premise tasks. 
  • One-Click Data Connectivity: Access existing data with one click via its extensive library of pre-built connectors.
  • Embedded Analytics: Scale with clients’ businesses via flexible deployment options including embedding, APIs and localization capabilities.
  • Machine Learning: Recognizes patterns in data via Smart Analytics and automatically builds visualizations based on predictive analytics. Learns over time, and remembers previous search queries, past visualizations and more.
  • Deployment Options: Deploy as a SaaS through the cloud or go hybrid, keeping data in-house but running analytics through cloud-based servers. Or, deploy through a virtual appliance that delivers all the benefits of a traditional cloud-hosted SaaS while being locally hosted on-premise or in a private-cloud.
  • Mobile App: Access reports and dashboards via its native mobile application for iOS and Android.

Pricing

License/Subscription Cost
  • On-Premise: License fee includes an upfront fee to own the software or other intellectual property for a fixed term
  • Cloud-based/SaaS: Pricing includes upfront cost for customization & integration along with monthly per user or subscription cost
Maintenance Cost
  • On-Premise: An additional cost over and above the upfront cost has to be paid for ongoing support and maintenance
  • Cloud-based/SaaS: There is no maintenance and support cost for the Cloud/Web-based solution
Installation/Implementation Cost
  • On-Premise: Typically charged over and above the license cost
  • Cloud-based/SaaS: Included in the monthly subscription cost
Customization Cost
  • Will vary depending on the functional requirements or services chosen
Data Migration Cost/Change Management/Upfront Switching Cost
  • Dependent on your current software, amount of data to be migrated, availability of migration tools, complexity of data and gaps between the existing system and the new system.
Recurring/Renewal Costs
  • On-Premise: Includes cost for updates, maintenance, upgrades, and patches
  • Cloud-based/SaaS: Renewal cost is equivalent to the fees paid monthly or annually, based on number of users
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Why We Picked Qlik Sense

Qlik Sense focuses on independent data analysis for enterprises with advanced tools that include AI, natural language processing and automation. User reviews praise it for its associative engine, interactive visualizations and sophisticated analytics.

Its dataset-linking functionality gets my vote as the most significant differentiator since it makes data modeling seamless and saves time. In comparison, manually linking tables in Tableau and Power BI feels like a huge task.

It supports fewer features out of the box (69%) compared to Tableau (72%) and Power BI (74%), but this could be intentional. Qlik has ready-to-go modules for analytics, automation and printing, so keeping it lean is a smart vendor move. Users should be aware that additional modules will cost extra, though.

Qlik Sense SaaS is multi-cloud, so unless the admin assigns separate workspaces, your users won’t be able to create personal dashboards — everything is shared otherwise. Some users said the platform slowed when processing large workloads, which is a common issue with many other platforms. Assess your need for speed before committing to a purchase.

If upgrading from QlikView, you’ll need to create new objects initially, as both platforms have different architectures. However, the vendor assists in seamless migration with the Qlik Analytics Modernization program.

Overall, Qlik Sense is an efficient platform that offers many analysis capabilities worth considering. We recommend checking it out if you’re looking for an alternative to Power BI, entrenched in Microsoft technology, or Tableau, with its emphasis on visualization.

Pros & Cons

  • Integrations: Approximately 86% of users reviewing data sources were satisfied with its wide connectivity.
  • Ease of Use: About 84% of users who cited usability praised the platform for self-service BI.
  • Functionality: Around 80% of the reviews that mentioned features praised it for ETL and data visualization.
  • Data Visualization: About 66% of the users discussing dashboards were satisfied with its interactive displays that allowed them to dig deep.
  • Cost: About 87% of users who mentioned pricing found the tool expensive.
  • Performance: Around 86% of users citing speed said it lagged when processing large and complex datasets.
  • Training: Approximately 69% of users who discussed adoption said there was a significant learning curve.
  • Customization: Around 65% of users who mentioned the freedom to design dashboards said the tool offered limited options.

Key Features

  • AI Integration: Ask and answer questions in natural language and automate processes using OpenAI and H2O.ai. Feed massive datasets to the LLM and watch as it summarizes the insight for you. Move beyond traditional analysis by working with the IBM Watson API for natural language.
  • Qlik Sense Management Console: Develop apps, manage tasks and connections, and track performance. With QMC, create content and consume data insights.
  • Reporting Service: Keep partners and clients on the same page by sending reports to everyone involved, even non-Qlik users. Download reports, subscribe to charts and sheets, or automate report delivery with its Reporting Service, available with Qlik Sense Enterprise SaaS.
  • Apps: Create interactive dashboards and visualizations for separate tasks within Qlik Sense. An organization can use hundreds of Qlik Sense apps in its tech stack. 
  • Associative Recommendations: Save time defining how data tables relate with its intelligent suggestions, something Tableau and Power BI lack. Bubbles represent data tables and color-coded rings — green, orange and red — inside them indicate the possibility of links between the tables.

Pricing

License/Subscription Cost
On-Premise:
  • License fees include an upfront fee to own the software, plus IP for a fixed term, installation, customization and integration costs
  • Enterprise Edition is offered on-premise and is based on a token system
  • Based on a combination of server, user, document and application-based licensing
Cloud-Based/SaaS:
  • Based on recurring subscription-based model: $X per user, per month
Cost may vary depending on the Qlik Sense Pricing plan selected:
  • Cloud Basic, Cloud Business, Desktop, Enterprise Edition or Personal Edition
Maintenance Cost
On-Premise: Maintenance cost is over and above the upfront fee
Cloud-Based/SaaS: Maintenance cost is included in the service fees charged at the time of purchase
Installation/Implementation Cost
On-Premise: Included in the upfront cost/subscription cost
Cloud-Based/SaaS: None
Customization Cost
For both on-premise and cloud-based/SaaS, customization costs vary depending on the product and pricing tier chosen, and the level of customization requiredCosts will vary depending on the package selected
Recurring/Renewal Costs
On-Premise: Annual recurring fees to be paid over and above the upfront cost include annual renewal, upgrades and ongoing support
Cloud-Based/SaaS: A recurring monthly fee is charged, which typically includes maintenance, monitoring, upgrades, training and support

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MicroStrategy

by MicroStrategy
MicroStrategy
MicroStrategy is a data visualization and reporting platform that deploys on-premise and on the web. The cloud version runs on AWS or Microsoft Azure. MicroStrategy Library is the web edition, while Workstation is the desktop version.It reigns supreme as the top analytics tool in our product directory and provides 91% of the required features out of the box. Regarding source data integration, it leaves very little to chance, winning our best-in-class award for connectivity. With over 200 connectors, there’s a high chance it’ll satisfy your data needs.If not, you can build one using a software development kit. SDKs are also the force behind REST and embedding APIs, HyperIntelligence and data visualization. Plus, the semantic layer enables automating data prep and analysis and generating visualizations on cue.Dossiers in MicroStrategy are like books; they have chapters further divided into pages, and each page has one or more visualizations. Every view is free-form — you can move charts around and organize them as you like. With write-back capability, you can update underlying databases from visualizations.The vendor launched its unified cloud AI analytics platform, MicroStrategy One, with GPT-4o in September 2024. It’s twice as fast, digging into the selected data to produce dashboard summaries and answer user queries in seconds. Update 12 has auditing capabilities and shows details of active licenses, including their compliance status.Its heart and soul is an Intelligence Server that manages metadata and processes queries. A mobile app is available. There’s a 30-day trial, but access to group permissions, KPIs and subscriptions requires a paid upgrade.User reviews mentioned that the solution was effective, but the ecosystem and pricing were complex.
User Sentiment User satisfaction level icon: great
Cost Breakdown
$10 - $100
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Qlik Sense

by QLIK TECHNOLOGIES INC.
Qlik Sense
Qlik Sense is a self-service analytics solution that supports enterprise decisions and strategy. Its value lies in interactive dashboards and reports for exploring data independently. Embedded analytics lets your users work freely with data within their applications and websites.Like QlikView, Qlik Sense has an associative engine. It links data tables in memory, keeping the information ready for when your users build models. Plus, its cognitive engine uses natural language for data tasks.The Enterprise subscription includes Talend Data Integration and Qlik Advanced Analytics in Qlik Cloud. You can also choose Qlik Data Integration. Qlik Sense Enterprise SaaS includes 5000 automations and 100 reports. It might be a good fit if your data loads are predictable and don't change much. The vendor charges for the data you move or the volumes you analyze; you can choose between the two.Qlik Sense deploys on Windows, Mac, Linux and any phone device. By contrast, Tableau runs on Windows, Mac and mobile, while Power BI is available only on Windows and Android devices.Individual users can choose the desktop edition, though they’ll need a Qlik Cloud account to download it. A 30-day trial period is available, after which it'll cost $30 per user monthly.
User Sentiment User satisfaction level icon: great
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Pricing & Cost Guide

See the Price/User for the top Embedded Analytics Tools… plus the most important considerations and questions to ask when shopping.

Buyer's Guide

Embedded Analytics Tools Are All About Insight at Your Fingertips

Embedded Analytics BG Intro

Embedded analytics addresses the last mile of insight — delivering information where it matters. The technique drives business growth with on-demand visibility into metrics.

At-hand information with embedded analytics spurs operational improvements and long-term strategy, including diversification planning.

Looking for a better way to manage your analytics needs? This buyer’s guide breaks down embedded BI, how it can help you succeed and how to pick the best solution.

Executive Summary

  • Embedded BI solutions deliver data to end users on demand without switching contexts when working within their business platforms.
  • They maximize your investment by minimizing risk, boosting efficiencies and supporting business forecasting.
  • Know your implementation goals and the key features of embedded analytics tools for a fruitful software search.
  • Self-service analytics, end-user development, open APIs and artificial intelligence (AI) are current embedded business intelligence trends.
  • Ask questions internally and from vendors to learn about products, implementation support and post-sales services.

What Is Embedded BI Software?

Embedded BI software are programs that provide business intelligence and analytics within enterprise applications and workflows. Embedded BI solutions deliver ready insight, presenting it in a user-friendly format.

Dashboards are interactive but not actionable. You can move the data points around to derive insight, but taking action is another thing.

The inventory dashboard tells you stock is surplus for specific items, but you can’t pause or modify orders from there. You’ll need to navigate to the order workflow in your procurement software to do it.

Embedded analytics tools present your inventory report within your order workflows, enabling proactive action when needed. It’s the same for the various industries and domains it serves.

Depending on who you are, embedded BI solutions benefit you in different ways.

  • As a vendor, you can save money by adding analytics to existing software — no need to start from scratch. Advanced offerings can differentiate you from the competition in your industry.
  • As a buyer, you don’t need to invent the wheel — embed analytics within your systems. Ask potential vendors if their products will work with your tech stack.
  • As an end-user, you get ready-to-go insight with data management and preparation capabilities.

With the required information at hand, you can save time and make informed decisions in the moment. In addition to following a strategy, you can course-correct if the current approach doesn’t serve your business.

Primary Benefits

Embedded business intelligence makes teams more productive with streamlined workflows and less context switching. Greater transparency into data helps spot opportunities and potential risks.

Primary Benefits of Embedded Analytics

Maximize ROI

White label an embedded BI solution to achieve revenue targets — provide metrics to end users without knowing they’re accessing an embedded program. You can act upon insights via interactive workflows within your routine processes.

Embed customer analytics — combine data from multiple user touchpoints into your BI system with embedding APIs. Retail, healthcare, finance, and consumer goods and services use in-app insight routinely.

Managing internal operations becomes easier with an embedded ERP (enterprise resource planning) solution. ERP includes accounting, supply chain, inventory, marketing automation and workforce management.

Minimize Risk

Embedded business intelligence solutions protect sensitive data by complementing security with robust architectures. Activity monitoring keeps track of data access and reporting tasks and who performed them. 

Embedded BI solutions have rich visualizations highlighting discrepancies and outliers, including the top performers. 

Outliers in data can indicate problems in operations like low stock, faulty items and falling sales. Setting KPI alerts helps minimize risk and gives you time to act.

Boost Efficiency

Embedded workflows help you maintain focus by keeping you within your primary workflows. They’re user-friendly, so anyone with basic data interpretation skills can connect the dots by establishing associations between complex data sets. 

Self-service BI is a big part of embedded tech, helping you engage better with data without analyst skills.

Embedded analytics SaaS (Software-as-a-Service) solutions came through during the 2019 pandemic.

Mike Brody, CEO of Exago, an embedded SaaS software vendor, said their company adapted quickly to the transition to remote work.

“In many ways, we’re more effective than we were before. COVID didn’t stop a lot of people, especially in the software industry. One-third of our company is now permanently remote; our staff works as effectively as if they were in the office next door, and we’ve increased our pool of great employees around the country.”

Predict Trends

Forecasting business trends with data science gives you the confidence to plan instead of relying on experience or guesswork. Embedding analytics systems into your business lets you build predictive data models from your preferred platforms.

Predictive analytics works with AI algorithms. The more data you feed them, the more accurate the results will be. You can include historical data in your forecast, besides seasonality, geographical data and weather metrics.

Anticipating product demand and supply chain issues is critical to ensure you’re not left hanging. Visualizing your project load for the foreseeable future can help you decide whether to hire more people.

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Implementation Goals

When buying embedded BI solutions, it’s essential to list your organization’s goals to ensure successful implementation. These will vary from one business to another, depending on specific needs. We recommend performing an internal assessment of your business processes, projects and resources beforehand.

Goal 1

Boost Your Bottom Line

  • You want to earn more revenue by offering better products and services.
  • You hope to reduce costs and increase efficiency.
  • You wish to improve your company’s financial health.

Goal 2

Improve Customer Service

  • You want to maintain high product quality.
  • You wish to offer products that customers want.
  • You hope to attract more buyers and keep current customers happy.

Goal 3

Track Operations

  • You want operational insight on demand.
  • Data access on mobile devices should be available.
  • You want KPI alerts if they exceed preset values.

Goal 4

Forecast Trends

  • You wish to improve processes today to get the desired outcome.
  • You hope to manage risk better by anticipating when something might go wrong.

Goal 5

Boost Productivity

  • You want in-app analytics and streamlined workflows for your teams.
  • You wish for your team to be self-sufficient in interpreting reports and dashboards.

Goal 6

Get Ahead of the Competition

  • You hope to take advantage of promising business opportunities.
  • You want to launch competitive products in the market at the right time.
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Basic Features & Functionality

According to a survey in the ThoughtSpot product manager’s guide, 57% of the polled companies said embedded analytics directly impacted revenue. 61% said it boosted engagement.

Embedded Analytics Stat

Thinking about where to start? Let’s get acquainted with the basic features of embedded software to help finalize your requirements.

Developer Tools

An open architecture lets you add functionality to the platform. Some vendors offer open APIs without charging extra.

Pick-and-click toolkits and white labeling are other desirable features. Multi-tenancy support ensures login-based access to data while keeping other tenants separate.

Version control keeps your application compatible with the host application as it updates. Write-backs keep the database in sync with front-end information changes.

Source Connectivity

Relational and NoSQL databases, Hadoop, and CSV, Excel and XML files are common data sources. FTP and SFTP server compatibility enable file transfer across networks.

The solution must support JDBC, ODBC and parametrized connectors. Adding and setting up new information sources should be possible.

Data Management

The solution must provide data preparation with profiling, parsing and enrichment.

Quality management requires data governance, metadata and object-level access. Multidimensional data analysis, including OLAP, must be possible.

Embedded Visualizations and Dashboards

Ready templates and customizable widgets save you from starting from scratch when building dashboards. Animations show changes in data over time.

Auto-refresh keeps you informed about the latest metrics. Interactivity lets you dig deeper, while a rich graphics library gives more options.

View only the desired metrics while hiding the rest with selections and filtering.

Besides your internal software, visualizations must be embeddable into websites and applications.

Security

Role-based data access, single sign-on (SSO) and SAML must be available. Activity logs and login-specific IP locks enforce accountability and compliance.

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Advanced Features & Functionality

If you plan to scale and have the budget, consider opting for advanced functionality. It can save you a tidy sum in the long run.

Embedded Reporting

Conventional reporting is still very relevant, but sometimes vendors offer it as a separate module at extra cost.

Opting for a vendor that includes reporting and dashboarding in the same package is cost-effective.

Often, vendors refer to dashboards as reports, so check what you’re getting and specify if you need both.

Customizable elements and formatting options can lend a professional look to dashboards. Scheduled report sharing gives you time for tasks that need human intervention.

You should be able to share reports as shareable URLs and email attachments and embed them into client applications.

Communication and Collaboration Tools

In-dashboard messages and comment threads help teams conduct meaningful data discussions. Email notifications are effective alerts for data changes and comments.

Availability

Though many vendors promise 100% availability, it’s better to cover your bases by asking about failsafe mechanisms. How does the vendor handle scheduled maintenance?

What happens if the application crashes? Are backup services and data caching available?

Mobile Support

Mobile updates help you stay on top of trends. Check with stakeholders if it’s a deal-breaker.

If yes, ask vendors if the solution is available via a mobile browser and app. You should be able to receive updates on your mobile email client.

Sending reports and dashboards as email attachments and viewing them on your phones, laptops and tablets should be possible.

Augmented Analytics

AI, machine learning (ML) and NLP enhance data analytics with self-learning algorithms and plain language searches.

They help you prepare, analyze and visualize data to pull it into dashboards and reports. Automated workflows free you from repetitive tasks.

IoT Analytics

IoT data comes from physical devices remotely connected to the internet for obtaining personal or business insights.

Enterprise IoT devices include construction and mining machinery, transport vehicles, and oil, gas and power utilities. Is this you?

Look for an embedded analytics system that gathers data from remote systems.

Pushing updates to these physically distant systems is another matter — ask the vendor if it’s part of the functionality.

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Current & Upcoming Trends

Embedded analytics is a game-changer for non-technical end users. It’s why self-service BI, end-user application development and AI are trending.

Embedded Analytics Trends

Self-Service Analytics

The need for shorter delivery cycles pushes enterprises to be more open with their data. They’re aware that the benefits of making information available to all outweigh the security risks. Besides, security and governance protocols help plug any gaps.

This demand for data democratization drives vendors to offer autonomous embedded platforms with help from augmented analytics.

It boosts employee engagement and productivity, helping enterprises stay competitive. Self-service analytics is a must-have feature and will continue to trend for years.

Citizen Developers

Self-service isn’t limited to deriving insight. Now you can develop software programs using simple user actions — no code involved. You can be a citizen developer, building apps using SDKs (software development kits) and app designing wizards.

Gartner defines a citizen developer as “an employee who creates applications for their own use or for others, using tools approved by the business.”

End-user development can reduce costs —- public APIs make embedding possible, whether it’s specific content or a complete analytics program. Security and compliance oversight is a must, but it’s working.

Who better than a business user to know what type of app they need?

Will citizen data scientists replace developers? It doesn't seem likely, with digital transformation becoming more niche. But citizen development is here to stay, with employees becoming more tech-savvy.

Open Platforms

Embedded tools rely on an open architecture to integrate with various applications and scale as data requirements change.

These integrations are loosely coupled software modules — you can modify the solution without affecting the other components. Javascript APIs bridge the back and front ends, letting you build from an intuitive HTML5 interface. 

At the front end, white labeling the embedded solution to your brand is a simple, one-click selection. Additionally, vendor plug-ins for transformations, formulas, visualizations, report export and user account management facilitate analytics.

Vendors should offer robust and resilient open APIs that can withstand technology changes.

Embedded AI

AI with embedded analytics — embedded AI — is currently big, abstracting queries with plain text responses and automating processes. While AI is the technology, machine learning is how you do it.

Machine learning also serves prescriptive analytics, helping you decide the next action.

Speaking of embedded intelligence, generative AI is currently a hot topic of discussion. From research tools to image and content generation, AI is a part of our lives now more than ever.

But enterprises are cautious about its usage as it’s not that great with data security.

The technology needs stricter guardrails to prevent sensitive data from being exposed publicly. User management and authentication systems have a lot of catching up to do.

Though embedded AI is yet to mature regarding security, it’ll continue to disrupt software development and data analytics.

Cost & Pricing Considerations

According to the ThoughtSpot survey, 78% of users said customization is the primary requirement when seeking in-app analytics. 52% of users rated autonomous data discovery as business-critical.

These findings confirm that tailor-made solutions are a high priority for companies.

Build or Buy?

If you’re considering developing in-house, consider this.

  • Developing an analytics solution from scratch is costly, and getting executive buy-in can be challenging.
  • Differentiating the product to stand out from the competition takes time. Keeping up with feature requests can slow down the time-to-market.
  • Generating revenue isn’t easy when the competition offers equally good or better products.
  • Finding skilled developers can be difficult.

Buying a software solution may be more practical.

If you want CRM analytics, should you look for an embedded BI tool or an embedded CRM system?

Consider your business needs, how the two tools deploy with your tech stack and which features they provide.

Licensing Options

  • For on-premise versions, the cost of ownership may be high, and maintenance, customization and upgrades are your responsibility.
  • SaaS software versions are available for a monthly or annual subscription fee. They’re lightweight and accessible from anywhere with an internet connection.

Pricing may be user, query, core or workspace-based.

  • How many people will use the program? User-based pricing might fit you if you’re not planning to expand soon.
  • How often do you need analytics? Query-based pricing can help you keep prices in check.
  • Core-based pricing fits teams with fluctuating workloads, allowing them to pay only for usage.
  • Workspace-based pricing might be for you if delivering analytics to external users and clients is a crucial requirement.

Many vendors offer tailored pricing, a mix of two or more options. Research your vendor — check online reviews, read industry guides and ask colleagues for recommendations.

Get our free embedded analytics pricing guide for cost estimates.

Additional Considerations

Ask for free trials, demos or proofs-of-concept to check product usability.

Often, basic support and training are included in the product package. Dedicated assistance and tailor-made training may cost extra.

Follow our Lean Software Selection methodology to procure a suitable solution.

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Questions To Ask Yourself

Software selection is unique to each organization. What works for others might not be the best fit for you.

Ask these questions internally.

  • How many users will work with the solution?
  • Will they need training?
  • What are our current pain points? How do we expect the new solution to address them?
  • What are our analytics requirements?
  • Which self-service capabilities do we need?

Embedded Analytics Key Questions

Questions To Ask Vendors

Face-to-face discussions with vendors help fill in the gaps online research won’t. Prepare questions to get clarity about the products and services from vendors.

About the Software

Add these questions to your list.

  • Which integrations does the software offer?
  • Is automation available? To what extent?
  • Which security features does the software offer?
  • Is it compatible with my existing system?
  • How does your platform serve companies in my industry?

About the Vendor

  • Which customer support and training options do you offer?
  • How does your technical support team handle help requests?
  • How long does onboarding take?
  • What are the storage and processing limits?
  • How many years of expertise do you have in the industry?

FAQs

What are the types of embedded BI tools?

Here’s a list. Check out the product directories on our website for product pros and cons and user sentiment analysis.

What are some embedded analytics techniques?

You can embed content directly within websites and applications using iFrames and HTML code, but it may become clunky for large data sets. Missing interactivity and customization can make for a less-than-satisfactory experience.

Additionally, ill-secured web forms can expose sensitive data to third parties.

Opting for an open embedded analytics platform allows you to customize the platform to your needs. Many vendors offer basic customization to get you started.

You can ask them for custom functionality depending on who’ll use it.

  • Data consumers prefer ready reports and dashboards with personalized views and interactivity.
  • Content creators perform queries, make reports and dashboards and share insight with others.
  • Data analysts may need a blank canvas, often starting from scratch and connecting to their preferred sources.

Who are your end users?

Check out our Jumpstart platform for a score-based comparison of the leading embedded software.

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Next Steps

Embedded BI tools drive business processes with comprehensive insight. On-demand information saves time, helping you focus on what’s important — steering your business to success.

To choose the right embedded business intelligence tool, create a requirements checklist of your must-have and nice-to-have features. Compare the shortlisted solutions based on how well they perform for each feature.

Shortlist five to seven systems, read user reviews, and request vendor price quotes and trials. Narrow your options based on price, UX, interface, support and other business needs.

Worried about how to go about it? Get started today with our free comparison report to gain insight into top software leaders.

Product Comparisons

Additional Resources

About The Contributors

The following expert team members are responsible for creating, reviewing, and fact checking the accuracy of this content.

Senior Technical Content Writer
Ritinder Kaur is a Senior Technical Content Writer at SelectHub and has eight years of experience writing about B2B software and quality assurance. She has a Masters degree in English language and literature and writes about Business Intelligence and Data Science. Her articles on software testing have been published on Stickyminds.
Technical Research By Sagardeep Roy
Senior Analyst
Sagardeep is a Senior Research Analyst at SelectHub, specializing in diverse technical categories. His expertise spans Business Intelligence, Analytics, Big Data, ETL, Cybersecurity, artificial intelligence and machine learning, with additional proficiency in EHR and Medical Billing. Holding a Master of Technology in Data Science from Amity University, Noida, and a Bachelor of Technology in Computer Science from West Bengal University of Technology, his experience across technology, healthcare, and market research extends back to 2016. As a certified Data Science and Business Analytics professional, he approaches complex projects with a results-oriented mindset, prioritizing individual excellence and collaborative success.
Technical Review By Manan Roy
Principal Analyst
Manan is a native of Tezpur, Assam (India), who currently lives in Kolkata, West Bengal (India). At SelectHub, he works on categories like CRM, HR, PPM, BI, and EHR. He has a Bachelor of Technology in CSE from The Gandhi Institute of Engineering and Technology, a Master of Technology from The Institute of Engineering and Management IT, and an MBA in Finance from St. Xavier's College. He's published two research papers, one in a conference and the other in a journal, during his Master of Technology.
Edited By Hunter Lowe
Content Editor
Hunter Lowe is a Content Editor, Writer and Market Analyst at SelectHub. His team covers categories that range from ERP and business intelligence to transportation and supply chain management. Hunter is an avid reader and Dungeons and Dragons addict who studied English and Creative Writing through college. In his free time, you'll likely find him devising new dungeons for his players to explore, checking out the latest video games, writing his next horror story or running around with his daughter.