Sisense For Cloud Data Teams vs Oracle Analytics Cloud

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Our analysts compared Sisense For Cloud Data Teams vs Oracle Analytics Cloud based on data from our 400+ point analysis of Business Intelligence Tools, user reviews and our own crowdsourced data from our free software selection platform.

Sisense For Cloud Data Teams Software Tool

Product Basics

Formerly known as Periscope Data, Sisense for Cloud Data Teams is a data analytics software tool that integrates seamlessly with the Sisense platform, offering advanced analytics that delivers actionable insights to teams that work with data in the cloud. It provides a single, cohesive interface for users to store, organize, analyze and visualize all their data for better decision-making. It empowers users of all kinds to produce, consume and share insights intuitively together, with or without coding knowledge.

Originally founded in 2012 in San Francisco, California, it was acquired by Sisense in May 2019 and rebranded in January 2020.
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Oracle Analytics Cloud is a public cloud service on which you can build and run reporting and analytics solutions. It can also manage data from Oracle Database and Oracle Autonomous Data Warehouse. Pairing it with Oracle Data Integration can help you move and transform data at scale. But that’s not all. You can build and deploy analytics applications even with non-Oracle systems. However, the level of integration and capabilities may differ.

You’ll need an Oracle Cloud account, and a free trial is available. Oracle customizes the view for you, whether you’re a web app developer, account admin or cloud architect. Workbooks and dashboards enable data exploration. You can set it up so the system sends reports to selected users on schedule. Governed analytics is available; your data stays secure. Annotations, export options and integration with social platforms are other capabilities.

Two pricing tiers are available. The Professional edition has self-serve analytics, direct source connections and dataflows for preparing content. It costs $16 per user monthly.

The Enterprise edition lets you enrich data, connect to private sources and build semantic models. You can track usage and set encryption keys, all at a cost of $80 per user monthly. Opt for a user or consumption model based on OCPUs (Oracle CPUs).

The user reviews were an interesting read. I haven’t seen many products with such strongly divided opinions. In all positive reviews, over 70% of the users voted for a specific feature, indicating a high level of user satisfaction and perceived value. On the flip side, over 87% of users said price and a steep learning curve were blockers to successful adoption.

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Product Insights

  • Transforms Data Fast: Perform timely data querying and large-scale data ingestion for any volume of workload, through the analytics warehouse integration. Plug the data engine directly into cloud databases and optimize raw data by bypassing steps of the ETL process. Enable hassle-free data import via proprietary data caching technology
  • Centralized Data Warehouse: Creates a single source of truth by ingesting and storing data where it’s analyzed, speeding up analytics processes.
  • Ease of Use: Explore data and visualize trends through simple search query language, rather than via coding or modeling, making it an accessible solution for users of all technical skill levels.
  • Stats at a Glance: Understand and parse the results of data queries through Summary Statistics, without needing to write more SQL while exploring data and building models.
  • Reusable Analysis: Save time by storing frequently used in-house codes for swift collaboration without needing to start new queries from scratch.
  • Collaborative Insights: Enable collaboration between analysts and decision-makers through programming and self-service analytics combined. Hand off data analysis between teams, then publish and share insights with others via direct linking, password-protected links, email or Slack.
  • Self-Service BI: Pinpoint important data points in minutes, with reusable formulas and ad hoc analysis modeling that query data and return answers in real time.
  • R, Python and SQL On One Platform: Develop more advanced analytics processes with any programming language, with support for SQL, Python and R all in the same environment. Integrate open-source programming and formulas from other packages or libraries.
  • Scalability: Incorporate more complex datasets, higher volumes of data, more users and more, as the solution grows with the company.
  • Security: Have confidence in data security, with a cloud security infrastructure that upholds industry wide best practices and standards. Encrypt all traffic between users’ web browsers and Sisense’s servers, and for additional user-level security, manage data permissions, TFA and single sign-on functionality.
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  • Leverage ML: According to our research, Oracle Analytics Cloud gets the top score of 76 for augmented analytics. The Explain and AutoML functionalities and one-click predictions give it an edge over other competitors like Qlik Sense and
  • Generate Reports: Oracle Analytics Cloud scores 93 in our analyst rankings with instant and planned reports that are interactive and accept conditional formatting. Plus, it supports text and voice searches even on the mobile app.
  • Monitor Usage: Track expenses with the Billing tab on the Oracle Cloud Console. Keep tabs on usage with a dedicated tool, Oracle Cost Analysis, included with your Oracle Cloud subscription.
  • Try for Free: Sign up for a free Oracle Cloud trial and get access to the Autonomous Database and Object Storage. You’ll need to sign in with your credit card details. The vendor deducts a token account verification amount from your card, which they return promptly. For me, it was annoying as they deducted it again three days later. Get $300 credits for 30 days to use the Analytics Cloud, Data Integration and the Container Engine for Kubernetes.
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  • Native Data Connectors: Blend data together into a single accessible database via an ecosystem of native data connectors and ETL partners.
  • Cloud Data Pipelines: Control when and how often data is refreshed and what the flow of information looks like. Gain visibility and control over data pipelines with a flexible, low maintenance solution.
  • Data Discovery: Directly access CSVs and data sets curated by analysts and interact with these insights through a drag-and-drop interface that does not require fluency in SQL. 
  • Git Integration: Grant developers complete control over their analytics environment through Git integration, sophisticated version control, release management workflows as well as file-level access to all user-generated content, like reports. Create, edit, sync and delete all settings through Git. 
  • Model-as-You-Go: Perform ad-hoc analysis to answer crucial questions at the click of a button by generating custom, on-the-fly data models.
  • Data Visualization: Create and share advanced, highly customizable data visualizations, including scatter plots, bar charts, bubble charts, bullet charts, funnel charts, waterfall charts, control charts, Gantt charts, radial bar charts and more.
  • SQL Editor Tools: Shorten the amount of time necessary to go from query to answer with powerful SQL writing tools, such as query revision history, views, filters, autocomplete suggestions, formatting and more. 
  • Learn SQL: Experiment with SQL programming language and data querying via drag-and-drop fields and see how the results change. Encourage users who aren’t fluent in SQL to become more familiar with it.
  • Code Library: Reduce repetitive data entry tasks and save time for subsequent report generation. Store frequently used code in a common library via Snippets for easy access later. 
  • Spaces: Manage data-level permissions to gate and restrict access to sensitive data and customize dashboards on a per-organization basis.
  • Share and Embed: Share dashboards via password-protection enabled public URLs or embedding inside other web applications or web portals. Download dashboards as static PDF images for uses such as email distribution.
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  • Deployment: Install and run anywhere, including as a hybrid solution. Scale the instance depending on your workload — deploy OCPUs in multiples of two, extending up to 52. Or pause it when idle. Though identity management is available, there is the option to use one’s own SSO provider. Admins can set user, group and role-based permissions.
  • Connectivity: Make decisions based on data; connect to social media feeds, data lakes and IoT sources. Store and process data at scale, irrespective of its volume, velocity and variety. Get started as soon as you log in with over 40 readymade connectors.
  • Direct Query: Oracle Analytics Cloud uses live queries and data caching to fetch responses. Each has its downside. Live connections are heavier on the system, and you might have to compromise on data freshness with data caching. A combination of both might be best. Consider live queries for critical KPIs and data caching for less frequent queries.
  • Data Preparation: Enrich data from the interface — get data quality insights as you work. Remove the grunt work — create reusable flows for transforming data you can test, share and schedule. Add custom calculations or write regular expressions in the dataset editor.
  • Semantic Data Modeling: Engage business, dev and data teams in meaningful discussions. Give them data views with a presentation layer that simplifies metrics. Hide the physical data structure with a logical one that speaks the business language. Give stakeholders the power to explore data independently.
  • AI/ML: Boost productivity with embedded machine learning and natural language insights every step of the way. Display quick forecasts, trend lines and clusters from a popup menu with one click. View the basic facts, key drivers and anomalies with the Explain option. Hit the ground running with recommendations on dimensions, measures and attributes to use when you don’t know where to start.
  • Oracle Analytics Publisher: Generate reports from any dataset or semantic model. Create formatted documents unique to your business, be it shipping labels, checks, letters or PDF forms.
  • Data Visualizations: Put your best foot forward with suitable charts and graphs that convey your message effectively. Modify them to answer users’ questions better. Choose from over 45 visualization types, or build your own using extensions from its vast library.
  • Embedded AI On Mobile: Get real-time alerts and intelligent recommendations on mobile. The Oracle Analytics mobile app captures your preferences and location. Upload datasets just like on the desktop or create a workbook from existing data. Powerful searches enable access to your favorite worksheets; add them to your home screen for a quick view. Use voice-enabled searches and listen to the results as a podcast.
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Product Ranking

#16

among all
Business Intelligence Tools

#10

among all
Business Intelligence Tools

Find out who the leaders are

Analyst Rating Summary

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Analyst Ratings for Functional Requirements Customize This Data Customize This Data

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Oracle Analytics Cloud
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Advanced Analytics Augmented Analytics Data Management Data Pre-processing Data Transformation Data Visualization Embedded Analytics Capabilities Geospatial Visualizations And Analysis Mobile Capabilities Platform Capabilities Reporting 88 82 100 100 100 100 71 100 79 83 98 0 25 50 75 100
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Analyst Ratings for Technical Requirements Customize This Data Customize This Data

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User Sentiment Summary

Great User Sentiment 140 reviews
Great User Sentiment 719 reviews
87%
of users recommend this product

Sisense For Cloud Data Teams has a 'great' User Satisfaction Rating of 87% when considering 140 user reviews from 4 recognized software review sites.

84%
of users recommend this product

Oracle Analytics Cloud has a 'great' User Satisfaction Rating of 84% when considering 719 user reviews from 4 recognized software review sites.

4.5 (72)
4.0 (228)
4.3 (33)
4.1 (59)
4.8 (4)
4.3 (316)
4.1 (31)
4.3 (116)

Awards

we're gathering data

SelectHub research analysts have evaluated Oracle Analytics Cloud and concluded it earns best-in-class honors for Augmented Analytics, Data Pre-processing and Geospatial Visualizations and Analysis.

Augmented Analytics Award
Data Pre-processing Award
Geospatial Visualizations and Analysis Award

Synopsis of User Ratings and Reviews

Data Querying: Almost 77% of users who mentioned data querying and data modeling said that this solution allows them to perform data queries of almost any kind.
Data Visualization: Of the users who mentioned data visualization, about 75% said that this tool excels at creating easily understandable graphics and visuals.
Sharing and Collaboration: Approximately 88% of users who mentioned this feature said that this solution facilitates strong collaboration on data analysis internally, while allowing for easy external sharing.
Implementation: In reference to setting up the platform, about 90% of users said that the process was smooth and quick.
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User-Friendly: Citing its interface, about 91% of users agreed that a drag-and-drop UI makes it easy to use.
Machine Learning: Around 86% of users who discussed augmented analytics were impressed with its ML capabilities.
Integrations: Approximately 84% of users who mentioned connectivity said the platform worked well with other systems, especially Oracle products.
Functionality: According to 83% of users who reviewed capabilities, it has all the required features to support data tasks.
Data Visualization: Around 73% of users who mentioned visualization praised the platform for its storytelling features.
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Reliance on SQL: While it excels in data querying, around 78% of users said that SQL knowledge is necessary to use this platform.
Self-Service Analytics: About 80% of users reviewing this feature said that data analysis is not truly self-service, requiring the involvement of a hands-on IT or analyst team.
Cost: Of the users who reviewed the cost of this tool, almost 86% of them found it too expensive, especially for smaller companies.
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Price: About 88% of reviews citing pricing said that it’s too expensive.
Adoption: Approximately 87% of users who discussed onboarding said there’s a significant learning curve.
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Sisense for Cloud Data Teams is a powerful BI tool that excels in the hands of data analysts with coding knowledge. These analysts will be able to model, manage, prepare, manipulate and analyze data with ease. As the platform supports SQL, Python and R programming languages, the sky's the limit when it comes to extensibility, development and coding support. The platform allows for strong collaboration within an organization, designed to alleviate the time-consuming burden of reporting and data visualization on IT teams while allowing business users to access insights on their own time. Most of the features are built around making the analytics team’s job easier, with reusable code, built-in collaboration and more. The support team earned universal praise from users who contacted them, citing their swift, in-depth and informative answers as immensely helpful in resolving any issues they had with the solution. In addition to hands-on support, a speedy implementation process ensures that customers can get the platform up and running in no time. We found that users’ opinions of the platform’s functionality and ease of use differed significantly based on their own roles; analysts generally praised its robust data visualization and data querying features, while decision-makers often found it hard to use, due to the SQL language barrier. SQL is necessary for most functions, and even though there is a visual query editor that attempts to make SQL more accessible, some users said that the platform doesn’t do enough in this regard. Overall, users did agree that the tool makes it easy to collaborate with each other to bridge that gap, with most of the analytics being done on the technical end, letting business users simply access those results. Still, it’s difficult to accurately call Sisense for Cloud Data Teams a self-service analytics tool, as it requires an IT or analyst team’s involvement to truly shine. Additionally, the cost can be prohibitive to smaller businesses. Overall, Sisense for Cloud Data Teams can be extremely powerful in the right hands - for those who know SQL and how to use it, it’s a dream for querying data and delivering analytics, but for those who don’t have the necessary IT resources, it could prove difficult to fully maximize the value of this data solution.

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Oracle Analytics Cloud is among the vendor’s many data services, including a business intelligence suite and a data intelligence platform. Besides, Oracle offers bespoke solutions for HCM, supply chain and customer experience. What differentiates Oracle Analytics is that extra dash of augmented capabilities.Embedded BI is where it truly shines, giving you natural language insights with a single click. This feature extends to its mobile app, and it outperforms many leading platforms with natural language queries and podcasts on mobile.According to our researchers, Oracle Analytics Cloud has fewer out-of-the-box features than its competitors, such as Power BI and Qlik Sense. Plus, licensing becomes complex when combining the database, middleware and analytics applications.It’s common for large vendors to offer specialized platforms, but the downside is that they can be out of reach of small organizations. But there’s a silver lining. Many vendors offer customized solutions, so we advise reaching out to the vendor for quotes.Users appreciate its regular updates, but some report initial bugs due to its relative newness. Despite a positive user experience, the learning curve can be steep. Some users found technical support slow and inadequate, as did I. They took two business days to get back to me when I needed assistance with my account.Oracle Analytics, though a robust platform, is suitable for mid- and large organizations. If you seek a powerful, scalable platform, consider opting for a trial, but be prepared for sticker shock, especially if you’re new to the Oracle ecosystem.

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