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Automating Excel to Power BI Publishing

Excel 2016 added a Publish to Power BI menu to let you export or connect Excel workbooks to Power BI. You can read more about this Excel feature here. One area where Excel is still ahead of Power BI Desktop is that is has an object model that lets you automate tasks with VBA. Unfortunately, Power BI Desktop doesn’t have an object model so you have to resort to unsupported ways (aka hacks) to automate tasks, such as refreshing and publishing to Power BI. I discussed some here.

I’ve noticed that Microsoft added not yet documented PublishToPBI method to Excel 2016. With it, refreshing the Excel data model and publishing it to Power BI Service takes two lines of code (you’d need more code to open the Excel workbook from an external application).

Sub Macro1()

ActiveWorkbook.Model.Refresh

ActiveWorkbook.PublishToPBI PublishType:=msoPBIExport, nameConflict:= msoPBIAbort, bstrGroupName:=”<Some Workspace>”

End Sub

Power BI Quick Measures

One of the most common complaints raised by Power BI customers is the DAX steep learning curve. The April release of Power BI Desktop introduces a feature called Quick Measures. Currently in preview (make sure to enable Quick Measures from File ð Options and settings ð Options, Preview features), Quick Measures are supposed to replace Quick Calcs. Besides supporting only a limited number of packaged calculations and not working on top of custom measures, the problem with Quick Calcs is that they don’t show the DAX formulas so there isn’t a way for you to learn from the work Microsoft did or to change the formulas to customize their behavior. This changes with Quick Measures.

You can create a Quick Measure over implicit or explicit measures. To do so, once you add a field to the report, expand the measure drop-down in the Fields of the Visualizations pane, and the click “Quick measures”. Then, select the calculation type. Currently, Power BI Desktop supports about 20 quick measures organized in four categories: Aggregate by category (average, min, max, variance), Filters (filtered value, difference or percentage from filtered value), Time intelligence (YTD, QTD, MTD, and their variances), Running total, Mathematical operations (additions, subtractions, division, multiplication, percentage difference).

040417_0137_PowerBIQuic1.png

For some obscure reason, the YTD quick measure I tried works only with an inline date hierarchy (Power BI Desktop can auto-generate an inline date hierarchy when you add a Date field to the report). But fear not! Once you create the quick measure, it becomes a regular measure and it gets added to the Fields list. Which means that you can change its formula! This is the auto-generated one.

SalesAmount YTD =

IF(

ISFILTERED(‘Date'[Date]),

ERROR(“Time intelligence quick measures can only be grouped or filtered by the Power BI-provided date hierarchy”),

TOTALYTD(SUM(‘ResellerSales'[SalesAmount]), ‘Date'[Date].[Date])

)

And this is how to get it work with any field in your Date table.

SalesAmount YTD = TOTALYTD(SUM(‘ResellerSales'[SalesAmount]), ‘Date'[Date])

Quick Measures are a welcome upgrade of Quick Calcs. They are designed to help you add common calculations and help you learn DAX.

“Get the Most Out of Power BI” Seminar on May 3rd

Patrick LeBlanc and I will deliver a free seminar “Get the Most Out of Power BI” on May 3rd, 8:30 AM to 12 PM, at the Microsoft Office in Alpharetta.

You won’t want to miss this educational and engaging event! Please register today as seating is limited at http://prologika.com/event/get-the-most-out-of-power-bi/.

Power BI is about empowering all types of users to get insights from data. It consists of the Power BI Service (powerbi.com), Power BI Desktop, Power BI Mobile, and Power BI Embedded, and it comes in two pricing options: Power BI Free and Power BI Pro. Power BI enjoys a tremendous momentum and industry observers has given it high scores. Packed with a dizzying variety of features, Power BI supports different solutions but it might be difficult to understand which features you need to reduce licensing cost.

Join Prologika and Microsoft for a 3-hour free seminar on Wednesday, May 3rd, 8:30 AM -12 PM ET, at the Microsoft Office in Alpharetta, when Teo Lachev (CEO of Prologika) and Patrick LeBlanc (Data Platform Solutions Architect at Microsoft) share practical knowledge and experience to help you get the most out of Power BI. If you’re planning Power BI rollout in your organization, this event is for you. Join Prologika and Microsoft for a 3-hour free seminar on Wednesday, May 3rd, 8:30 AM -12 PM ET, at the Microsoft Office in Alpharetta, when Teo Lachev (CEO of Prologika) and Patrick LeBlank (Data Platform Solutions Architect at Microsoft) share practical knowledge and experience to help you get the most out of Power BI. If you’re planning Power BI rollout in your organization, this event is for you.

Learn tips and tricks to stay within Power BI Free and reduce cost, including:

  • Simple sharing
  • Content service packs
  • Avoid gateways for refreshing imported data
  • Deploy Power BI reports on-premises
  • Share reports with external users

Power BI customer stories from the frontline

  • Learn how other customers use Power BI
  • Learn top customer issues when adopting Power BI that we have faced
  • Explore different problems and how we have fixed them

Ask questions and get them answered

“7 Ways to Integrate Excel with Power BI” Presentation on April 19th

I’m presenting “7 Ways to Integrate Excel with Power BI” for the Atlanta Modern Excel Group on April 19th at the Microsoft office in Alpharetta. Prologika and Microsoft are sponsoring the event. Please RSVP here.

Power BI is gaining a momentum but Excel still rules the corporate world. Fortunately, Power BI and Excel are not exclusive choices. Join me to learn how you can preserve your Excel investment in Power BI.

I’ll start by explaining the value Power BI brings to different types of users. Then, I’ll discuss and demo seven options for integrating Excel with Power BI:

  • Import Excel files in Power BI Service
  • Build self-service data models from Excel data
  • Deploy Excel models to Power BI
  • Convert Excel models to Power BI
  • Connect to Excel reports
  • Analyze Power BI datasets in Excel
  • Add Excel reports to Power BI dashboards

Prologika Newsletter Spring 2017

15 Reasons Why Microsoft is Leading the BI Space


I hope you’re enjoying the beginning of 2017 and you’re staying healthy and busy. It’s been a hectic and exciting period for me. I published the second edition of my “Applied Microsoft Power BI” book in January to keep it up to date.  It’s great to see all the momentum and interest surrounding Power BI. Just last month, I taught my “Applied Power BI” class three few weeks in a row! On the implementation side of things, companies of all sizes are adopting Power BI. And, one of our customers made the Power BI blog with their CRM platform that uses Power BI Embedded to deliver interactive reports to their users!


The Gartner 2017 Magic Quadrant for BI and Data Analytics

Speaking of Power BA and its momentum, industry observers are taking notice. As Kamal Hathi (General Manager, Microsoft BI) announced, the newly released Garner Magic Quadrant for Business Intelligence and Data Analytics gave Microsoft a very high score. Read the full report here.

Of course, there are many competing definitions of what constitutes a BI and Analytics platform. Note that Gartner reviewed only Power BI and certain aspects of Cortana Analytics. Reporting Services, Analysis Services and the other on-premises and cloud Microsoft BI-related solutions are not covered, such as Azure SQL Database, SQL Data Warehouse, Azure ML, Query Catalog, Cognitive Services, HDInsight,  Data Lake, StreamInsight). If we take them in consideration, where will the dot be?

The image below shows the Microsoft’s lift between last year and this year in the Gartner magic quadrant. What a leap!

 031117_2001_PrologikaNe2.png  031117_2001_PrologikaNe3.png

I’m surprised to find that the dot is not higher on the ability to execute, especially considering that Gartner ranked Microsoft and its main rival (Tableau) almost the same. You might also find my two-part blog about Tableau vs. Microsoft useful if you are tasked to compare these two vendors.

Understanding the 15 Critical Capabilities

As explained in the report, to evaluate vendors, Gartner uses 15 critical capabilities to support five main use cases: Agile Centralize BI Provisioning, Decentralized Analytics. Governed Data Discovery, Embedded BI, and Extranet Deployments. The following table includes my comments on each of the 15 capability.

Capability My Rank  Teo’s Comments
Infrastructure BI Platform Administration, Security and Architecture
Capabilities that enable platform security, administering users, auditing platform access and utilization, optimizing performance and ensuring high availability and disaster recovery.

Medium to High

There are a lot of things here:
Security – More work is required to support external users in Power BI, Power BI Embedded, and SSRS
Administering users – Power BI supports a progressive deployment depending on the desired level of integration with Office 365 (unmanaged tenant, managing tenant, and federated AD)
Auditing: Power BI supports auditing access and utilization but more work is required for proactive monitoring and improving its data governance capabilities
Performance and HA: Highly-redundant and scalable backend, consisting of SSAS Tabular farm and Azure services.
Cloud BI
Platform-as-a-service and analytic-application-as-a-service capabilities for building, deploying and managing analytics and analytic applications in the cloud, based on data both in the cloud and on-premises

High

Power BI supports both pure cloud and hybrid architectures depending on data volumes and security requirements. No other vendor offers both architectures.
Data Source Connectivity and Ingestion
Capabilities that allow users to connect to the structured and unstructured data contained within various types of storage platforms, both on-premises and in the cloud.

High

As of this time, Power BI supports close to 70 connectors to let you connect to cloud and on-premises data sources. No scripting required.
Data Management Metadata Management
Tools for enabling users to leverage a common SOR semantic model and metadata. These should provide a robust and centralized way for administrators to search, capture, store, reuse and publish metadata objects such as dimensions, hierarchies, measures, performance metrics/key performance indicators (KPIs), and report layout objects, parameters and so on. Administrators should have the ability to promote a business-user-defined data mashup and metadata to the SOR metadata.

Medium to High

Microsoft offers an organizational BI Semantic Model (BISM) which is typically implemented as an Analysis Services Tabular or Multidimensional models. On the self-service side of things, users can create Excel or Power BI Desktop models. IT can promote a self-service Excel model to a Tabular model. Although not officially supported because Power BI Desktop is changing every month, IT can upgrade a Power BI Desktop model to a Tabular model.
Self-Contained Extraction, Transformation and Loading (ETL) and Data Storage
Platform capabilities for accessing, integrating, transforming and loading data into a self-contained storage layer, with the ability to index data and manage data loads and refresh scheduling.

Medium

SSIS is the most popular on-premises ETL tool. More work is required to bring similar capabilities in the cloud (I think Azure Data Factory is a step backwards)
Self-Service Data Preparation
The drag-and-drop, user-driven data combination of different sources, and the creation of analytic models such as user-defined measures, sets, groups and hierarchies. Advanced capabilities include semantic autodiscovery, intelligent joins, intelligent profiling, hierarchy generation, data lineage and data blending on varied data sources, including multistructured data

High

Power BI Desktop and Excel has a fantastic query editor (originated from Power Query) that scores big with business users. Other vendors that score high in the Magic Quadrant don’t have such native capabilities. Power BI and Excel have best of class self-modeling capabilities (much better than Tableau). Azure Query Catalog can be used for dataset autodiscovery.
Analysis and Content Creation Embedded Advanced Analytics
Enables users to easily access advanced analytics capabilities that are self-contained within the platform itself or available through the import and integration of externally developed models.

High

Not sure what is meant here by “advanced analytics capabilities”. Power BI supports Quick Insights (brute-force machine learning), integration with R, Azure Machine Learning, clustering, forecasting, binning, but I might be missing something.
Analytic Dashboards
The ability to create highly interactive dashboards and content, with visual exploration and embedded advanced and geospatial analytics, to be consumed by others.

High

“Highly interactive dashboards and content” is what Power BI is all about.
Interactive Visual Exploration
Enables the exploration of data via an array of visualization options that go beyond those of basic pie, bar and line charts to include heat and tree maps, geographic maps, scatter plots and other special-purpose visuals. These tools enable users to analyze and manipulate the data by interacting directly with a visual representation of it to display as percentages, bins and groups.

Medium

Power BI covers all stated requirements in this category. However, while its visualization capabilities are improving every week, more work is required to catch up with the Tableau and Qlik in some areas, such as cell drillthrough, ability to repeat visualizations, such as to nest a bar into a table, conditional binding, exression-based properties and filters, and others.
Smart Data Discovery
Automatically finds, visualizes and narrates important findings such as correlations, exceptions, clusters, links and predictions in data that are relevant to users without requiring them to build models or write algorithms. Users explore data via visualizations, natural-language-generated narration, search and NLQ technologies.

Medium to High

Through Quick Insights, Power BI can automatically find correlations, outliers, and other hidden trends. It doesn’t currently have native narrative capabilities, except for the custom visual from Narrative Science. Power BI is one of the few vendors that offers natural queries.
Mobile Exploration and Authoring
Enables organizations to develop and deliver content to mobile devices in a publishing and/or interactive mode, and takes advantage of mobile devices’ native capabilities, such as touchscreen, camera, location awareness and natural-language query

High

Native apps for iOS, Android and Windows to surface both Power BI and SSRS reports.
Sharing of Findings Embedding Analytic Content
Capabilities including a software developer’s kit with APIs and support for open standards for creating and modifying analytic content, visualizations and applications, embedding them into a business process, and/or an application or portal. These capabilities can reside outside the application (reusing the analytic infrastructure), but must be easily and seamlessly accessible from inside the application without forcing users to switch between systems. The capabilities for integrating BI and analytics with the application architecture will enable users to choose where in the business process the analytics should be embedded.

High

An Azure cloud service, Power BI Embedded allows you to embed reports for external users with very appealing cost-effective licensing model. On premises, SSRS offers similar capabilities.
Publish, Share and Collaborate on Analytic Content
Capabilities that allow users to publish, deploy and operationalize analytic content through various output types and distribution methods, with support for content search, scheduling and alerts. Enables users to share, discuss and track information, analysis, analytic content and decisions via discussion threads, chat and annotations.

High

Power BI supports subscriptions and data alerts but we can do better, such as to allow an admin to subscribe other users. Power BI workspaces and groups allow users to share BI artifacts, participate in discussion lists, and share calendars. Power BI Mobile allows users to annotate reports.
Overall platform capabilities Platform Capabilities and Workflow
This capability considers the degree to which capabilities are offered in a single, seamless product or across multiple products with little integration.

Medium to High

The integration hub is Power BI Service which integrates Power BI reports, Excel reports, SSRS reports. More work is required on integration with Excel reports that connect to SSAS models.
Ease of Use and Visual Appeal
Ease of use to administer and deploy the platform, create content, consume and interact with content, as well as the visual appeal.

High

As far as deployment, Power BI is “five seconds to sign up, five minutes to wow!” As far as the visual appeal, beauty is the eye of the beholder but Power BI has done respectable job to follow best visualization practices.

MS BI Events in Atlanta

As you’d probably agree, the BI landscape is fast-moving and it might be overwhelming. If you need any help with planning and implementing your next-generation BI solution, don’t hesitate to contact me. As a Microsoft Gold Partner and premier BI firm, you can trust us to help you plan and implement your data analytics projects, and rest assured that you’ll get the best service.

Regards,

sig-1

Teo Lachev
Prologika, LLC | Making Sense of Data
Microsoft Partner | Gold Data Analytics

Implementing Header-Details in Power BI

Lots of things to like in the just released March update of Power BI Desktop! My favorite? We can now implement header-details text reports using the updated Matrix visual. Previously, Table and Matrix visuals wouldn’t allow you to select a row to cross filter other sections. Now, you can use the Matrix visual for the header section. When you click a row in the “header”, other visuals get cross-filtered. In the screenshot below, the Table visual shows all customers who have purchased the selected product. Also, notice that the Slicer visual has also been upgraded to allow sliding a numeric measure.

030717_0323_Implementin1.png

Gartner’s 2017 BI and Data Analytics Magic Quadrant Shows Microsoft Leading

Power BI is enjoying a tremendous momentum and unprecedented popularity. Just within this month, your humble correspondent has been teaching Power BI four times in a row. It looks like industry observers are taking notice of this momentum. As Kamal Hathi (General Manager, Microsoft BI) announced, the newly released Garner Magic Quadrant for Business Intelligence and Data Analytics gave Microsoft a very high score. The image below shows the Microsoft’s lift between last year and this year in the Gartner magic quadrant.

I’m not surprised about the Qlik drop given they sold out the company. What’s still surprising to me is that Gartner ranked Tableau and Microsoft almost the same on the ability to execute. Although the report is not out yet, judging by the stub, Gartner used the same 14 criteria as last year, but added one more which is unknown at this point (probably real-time where Microsoft can score very high as well). Here are my comments on where Microsoft stands on these 14 criteria. You might also find my two-part blog about Tableau vs. Microsoft useful if you are tasked to compare vendors.

Capability

Teo’s Rank for MS BI

Comments
Infrastructure BI Platform Administration
Capabilities that enable scaling the platform, optimizing performance and ensuring high availability and disaster recovery

High

On premises or cloud, I think the MS BI Platform is second to none
Cloud BI
Platform-as-a-service and analytic-application-as-a-service capabilities for building, deploying and managing analytics and analytic applications in the cloud, based on data both in the cloud and on-premises

High

Power BI supports both pure cloud and hybrid architectures
Security and User Administration
Capabilities that enable platform security, administering users, and auditing platform access and utilization

Medium

More work is required to support external users in Power BI, Power BI Embedded, and SSRS
Data Source Connectivity
Capabilities that allow users to connect to the structured and unstructured data contained within various types of storage platforms, both on-premises and in the cloud.

High

As of this time, Power BI supports close to 70 connectors to let you connect to cloud and on-premises data sources. No scripting required.
Data Management Governance and Metadata Management
Tools for enabling users to share the same systems-of-record semantic model and metadata. These should provide a robust and centralized way for administrators to search, capture, store, reuse and publish metadata objects, such as dimensions, hierarchies, measures, performance metrics/key performance indicators (KPIs) and report layout objects, parameters and so on. Administrators should have the ability to promote a business-user-defined data model to a system-of-record metadata object.

Medium

Power BI has done a good job to provide auditing and admin oversight but more work is required for proactive monitoring and improving its data governance capabilities
Self-Contained Extraction, Transformation and Loading (ETL) and Data Storage
Platform capabilities for accessing, integrating, transforming and loading data into a self-contained storage layer, with the ability to index data and manage data loads and refresh scheduling.

Medium

SSIS is the most popular on-premises ETL tool. More work is required to bring similar capabilities in the cloud (I think Azure Data Factory is a step backwards)
Self-Service Data Preparation
The drag-and-drop, user-driven data combination of different sources, and the creation of analytic models such as user-defined measures, sets, groups and hierarchies. Advanced capabilities include semantic autodiscovery, intelligent joins, intelligent profiling, hierarchy generation, data lineage and data blending on varied data sources, including multistructured data

High

Power BI Desktop and Excel has a fantastic query editor (originated from Power Query) that scores big with business users. Tableau doesn’t have such native capabilities. Power BI and Excel have best of class self-modeling capabilities (much better than Tableau). Azure Query Catalog can be used for dataset autodiscovery.
Analysis and Content Creation Embedded Advanced Analytics
Enables users to easily access advanced analytics capabilities that are self-contained within the platform itself or available through the import and integration of externally developed models.

High

Not sure what is meant here by “advanced analytics capabilities”. Power BI supports integration with R, Azure Machine Learning, clustering, forecasting, binning, but I might be missing something.
Analytic Dashboards
The ability to create highly interactive dashboards and content, with visual exploration and embedded advanced and geospatial analytics, to be consumed by others

High

“Highly interactive dashboards and content” is what Power BI is all about.
Interactive Visual Exploration
Enables the exploration of data via the manipulation of chart images, with the color, brightness, size, shape and motion of visual objects representing aspects of the dataset being analyzed. This includes an array of visualization options that go beyond those of pie, bar and line charts, to include heat and tree maps, geographic maps, scatter plots and other special-purpose visuals. These tools enable users to analyze the data by interacting directly with a visual representation of it

High

According to Gartner’s definition, Power BI should score high but more work is required on the visualization side of things, such as ability to drill through a chart point as we can do in SSRS.
Mobile Exploration and Authoring
Enables organizations to develop and deliver content to mobile devices in a publishing and/or interactive mode, and takes advantage of mobile devices’ native capabilities, such as touchscreen, camera, location awareness and natural-language query

High

Native apps for iOS, Android and Windows to surface both Power BI and SSRS reports.
Sharing of Findings Embedding Analytic Content
Capabilities including a software developer’s kit with APIs and support for open standards for creating and modifying analytic content, visualizations and applications, embedding them into a business process, and/or an application or portal. These capabilities can reside outside the application (reusing the analytic infrastructure), but must be easily and seamlessly accessible from inside the application without forcing users to switch between systems. The capabilities for integrating BI and analytics with the application architecture will enable users to choose where in the business process the analytics should be embedded.

High

An Azure cloud service, Power BI Embedded allows you to do this with an appealing cost-effective licensing model.
Publishing Analytic Content
Capabilities that allow users to publish, deploy and operationalize analytic content through various output types and distribution methods, with support for content search, storytelling, scheduling and alerts.

Medium

Power BI supports subscriptions and data alerts but we can do better, such as to allow an admin to subscribe other users. “Storytelling” can mean different things but I thought the integration with Narrative Science can fall into this category.
Collaboration and Social BI
Enables users to share and discuss information, analysis, analytic content and decisions via discussion threads, chat and annotations

High

Power BI supports this with workspaces and Office 365 unified groups.

Of course, there are many competing definitions of what constitutes a BI and Analytics platform. Again, it looks to me that Gartner has predominantly focused on the self-service BI aspect of it (even there Microsoft should have scored higher) and ignored the SQL Server BI features and all the cloud BI-related products (Azure SQL Database, SQL Data Warehouse, Azure ML, Query Catalog, HDInsight, StreamInsight). If we take them in consideration, where will that dot be?

Types of Power BI Real-time Datasets

Everyone wants real-time BI, even when it doesn’t have to be really “real time”. Today Microsoft announced General Availability of Power BI Real-Time Streaming Datasets. There are actually three types of Power BI real-time datasets, as mentioned in the documentation.

  • Push – Power BI permanently stores the data, enabling historic analysis, and reports creation atop the dataset. Behind the scenes, Power BI provisions an Azure SQL instance when the dataset is created. New data is pushed into SQL. Power BI then connects to that dataset via DirectQuery. Query Refresh (sending new queries to Azure SQL to update dashboard visuals) occurs whenever data is pushed in. When you create the dataset programmatically, you can specify a retention policy (defaultRetentionPolicy setting). When defaultRetentionPolicy is set to None, the dataset accumulates data to the maximum allowed Power BI limit (currently 1 GB). When set to basicFIFO, the dataset holds up to 200,000 rows and after that older rows are pushed out when the new ones come in.
  • Streaming — Power BI stores the data only in a transient cache – this means report creation, historic analysis is disabled, but in return there is consistently lower latency between when the data is pushed in and when the visuals update. The data flows into a Redis cache, and the dashboard visuals directly pull data from that Redis cache. Therefore, consider streaming datasets when you want the lowest latency (we are talking about milliseconds here) but you are limited to a few pre-defined visualizations supported by the Power BI dashboard real-time tiles. You can’t create custom reports.
  • Hybrid — Hybrid datasets send data to both the “push” and “streaming” endpoints, thereby getting the benefits of both at the expense of duplicate storage.

Unless you use StreamInsight (currently, it supports only push datasets) or PubNub (supports streaming datasets), you must create the dataset programmatically using the Power BI REST APIs. Currently, you can’t use Power BI Desktop to create real-time datasets.

Unblocking the On-premises Data Gateway

Scenario: You have configured the Power BI on-premises data gateway for centralized data access and verified that its data sources test just fine. Direct query connections work. However, when you go to Power BI Service and attempt to schedule a data refresh for a dataset, you might find that the data gateway is disabled.

Solution: The most common reasons for Power BI to disable the on-premises data gateway for refresh are:

  1. Unlike the personal gateway, the on-premises data gateway requires you to register data sources. You must go to the gateway properties and create data sources for all data sources used in your Power BI Desktop file. Unfortunately, as it stands Power BI doesn’t allow you to select which data sources in the Power BI Desktop file will be refreshed and which ones don’t require a refresh. It’s all or nothing proposition. So, if one data source is not compatible or can’t be refreshed, the gateway will be disabled.
  2. The connection strings in data sources in the Power BI Desktop file might differ from the settings of the data sources you registered in the on-premises gateway. For example, in Power BI Desktop you might have imported data from a local Excel file. Then, you might have moved the file to a network share and established a gateway data source to point to the network share. Because the connection strings differ, Power BI Service won’t find an on-premises gateway to serve the Excel file and it will disable the gateway for refresh. So, triple-verify the that data sources match.
  3. You might have manually added a table to your model and entered some data using the Power BI Desktop “Enter Data” feature. Because custom tables can’t refresh, Power BI disables the gateway.

012817_0130_Unblockingt1.png

Customer Success Case – ZynBit

One of our customers, ZynBit, made the Power BI blog today! Initially, ZynBit was considering Tableau but abandoned it in favor of Power BI because of the Power BI superior data modeling capabilities and the cost effective licensing model of Power BI Embedded. Prologika helped ZynBit to transition their solution to Power BI, including designing the data model and integrating reports with Power BI Embedded. Read our case study here.

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