Our analysts compared Power BI vs Einstein Analytics 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.
Analyst Rating
User Sentiment
Microsoft Power BI is an analytics and reporting solution for individuals and enterprises. Ranked among the top five products in our BI product directory, it’s a user favorite, with 88% of reviewers giving it the thumbs up.
It’s versatile in connectivity, pulling data from files, databases and cloud sources. Power Query helps users transform data to the desired format for building accurate models. They will serve as the basis for analysis and reporting. With Azure Machine Learning, Power BI incorporates AI into the analysis.
Government agencies find them handy for tracking citizen programs, crime and health data, and utilities. For healthcare companies, it proves helpful in patient data tracking, population health management and operations. Retail is all about sales and revenue, and if this is you, the vendor offers ready-made report templates that can help you hit the ground running. That’s not all; other report samples are available too.
Reusable dataflows in Power BI help you create a process once and run it again. Dataflows are shareable, so your whole team benefits. DAX enables complex calculations, while natural language Q&A speeds up analysis. Team workspaces enable collaboration, and mobile insight is available.
Individual accounts include Power BI Desktop, Power BI Pro and Premium per User (PPU). Pro and PPU licenses use Power BI Service, which lets you share content with other Pro users and is suitable for small businesses.
Power BI Premium is an enterprise license; you can share content with anyone, even external users. Pro and PPU cost $9.99 and $20 per user monthly, while Premium comes at $4,995 per month. User reviews praise it for ease of use, connectivity and modeling, but most users find the pricing confusing, possibly because of the various Microsoft integrations that make Power BI a complete package.
among all Business Intelligence Tools
Power BI has a 'great' User Satisfaction Rating of 88% when considering 5246 user reviews from 4 recognized software review sites.
Einstein Analytics has a 'great' User Satisfaction Rating of 83% when considering 1161 user reviews from 4 recognized software review sites.
SelectHub research analysts have evaluated Power BI and concluded it earns best-in-class honors for Embedded Analytics Capabilities, Geospatial Visualizations and Analysis and Mobile Capabilities.
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.
Einstein Analytics from Salesforce is a predictive analytics BI tool that uses the power of AI and machine learning to glean insights and create visualizations and reports to drive business decisions. All users who reviewed its analytics capabilities said that it excels at augmented analytics. Many users who reviewed data visualization said that templates and dashboards are easy to customize for deep-dive data exploration. With a range of reporting options and intuitive drag-and-drop functionality, the platform empowers business users to create their own reports without needing to code. Being part of the Salesforce suite, the platform integrates well with other SF offerings, as expected, as well as with external data sources. As for the tool’s data management capabilities, some users said that ETL functions are self-contained in that they replace the need to write code, however others said that data needs to be cleansed before the ETL engine can consume it for data analysis. Commenting on the software’s functionality, around 68% of users said that it is easy to drill down into KPIs with little training in analytics, whereas some users said that the platform is sparse in terms of features and does not have the same reporting capabilities as other Salesforce tools. Mentioning the interface, a majority of users said that it is clean and interactive, though quite a few users said that they preferred the classic version to the new one. A majority of the users who reviewed pricing said that, in addition to expensive per-user licenses, other costs can quickly add up, since implementation is not easy and often requires professional vendor support. Many users who discussed setup said that the platform struggles when processing large amounts of data, and plugins are needed to process heavier data sets, which further compounds costs. Quite a few users said that the platform performs well within the Salesforce ecosystem; however, it does not have the robustness and flexibility of Tableau. Overall, Einstein Analytics is a BI tool with strong out of the box ETL and data visualization capabilities that glean deeper insights into business metrics and seems to be suited for organizations with lightweight data analysis needs or those that already implement Salesforce solutions.
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