Power BI vs. Tableau (Part 3)

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Feeling the heat, Tableau has come up with an updated Power BI vs. Tableau battle card as one of my clients pointed out. This time designed as a video. I guess the previous “10 Ways Power BI Falls Short” slide deck, which I discussed in the part 1 and part 2 of my “Power BI vs. Tableau” blog , wasn’t effective enough. I concur given the large number of customers abandoning them. Tableau is desperately trying to breathe new life into their aging software by a series of acquisitions to stay competitive but they’re fighting now an uphill battle. And their marketing materials should have a timestamp since Power BI improves every month and points get outdated quickly (see the first part 1 of my blog).

But let’s take a look at the latest battle card so we are better positioned to answer the question asked by Tableau “Which one helped me answer my questions faster?”

  1. 2:17 minute – Tableau shows a bar multiple by Year and Region, with the narrative “it’s surprising that other tools can’t do that”. Here is a similar visual with Power BI.
  2. 4:00 minute – Maps. OK, Tableau is very excited about lassoing points on the map like it’s the Holy Grail of geospatial analytics. What about using authoritative spatial data, such as ArcGIS. Because Tableau its proprietary visualization framework that doesn’t natively support plugins, this is what you have to do to get it with Tableau integrated with ArcGIS. With Power BI, it’s built in a custom visual, which by the way supports lassoing. So, which one helped me answer my questions faster?
  3. 5:30 minute — The high-density outlier pitch. Alas, this time isn’t taking the central stage. As explained here, as of 9/30 all Power BI visuals except maps are high density so it’s a mute point.
  4. 7:11 minute – Tableau pitches they connect to lots of, lots of data but shows less connectors than Power BI. Power BI has 80 connectors and growing every month.
  5. 8:00 minute – Tableau discusses collaboration and how easy it should be to share with coworkers by deploying to on-premises Tableau server. Well, I’d argue that it’s easier to deploy to the cloud, or even better, give the user the choice to deploy to a PaaS platform or to on-premises server.
  6. 10:00 minute – I’m losing the pitch as Tableau is demonstrating how dashboards have full fidelity when published. So, do Power BI reports.
  7. 11:00 minute – Recipients personalizing shared reports and dashboards by creating views. Tableau has a point here, the Power BI sharing story needs consistency. Previously, organizational content packs allowed users to create personal read-write copies but apps, which supersede content packs, don’t have this feature (they are read-only to the recipient). About filtering, users can pass filters on the report URL. And users can create reports from scratch if they have access to the dataset, such as members of a workspace.
  8. 13:12 minute – Sandboxing and lifecycle management. The current Power BI Service story is to use workspaces for different environments, but Power BI Premium would most likely improve on this. On premises, you can use DEV and QA report servers which don’t require licensing. Try to get a free server with Tableau for QA/DEV!
  9. 14:00 minute – Auditing. Power BI supports usage metrics on report and dashboard level. Power BI also has comprehensive and integrated auditing with Office 365.
  10. 15:00 minute – More pitch about the Tableau Server governance. Well, SSRS/Power BI Report Server had this for a long time. But it also supports SSRS traditional reports, Excel reports, and Power BI reports. Speaking of a centralized report management, can you deploy anything else than Tableau reports to the Tableau report server, so it becomes an enterprise report portal for different report types?
  11. 16:00 minute – More about auditing. SSRS/Power BI Report Server has an execution log for this.

Then at the bottom of the page, we have a study by someone ex-Gartner, citing lower TCO for Tableau compared to Power BI. I can’t be reading this right. From the Gartner’s 2017 Magic Quadrant for Business Intelligence and Analytics Platforms, “On an annualized basis, Microsoft Power BI is roughly one-third of the license cost of a three-year perpetual BI license, but 80% lower than other cloud BI products. Low total cost of ownership was cited as the second most important reason for reference customers choosing Microsoft Power BI.” Yet, this researcher has found that “Microsoft Power BI’s total cost of ownership (TCO) to be 29% higher than Tableau”? Pick who to trust. And should business users deal with 20 GB datasets to start with? What about the novel idea of putting all of this data into a centralized semantic layer so we don’t have datasets moving around? Wait, isn’t a Tableau model limited to a single dataset with “data blending” capabilities? What’s the TOC then for all these isolated Tableau spreadmarts?

When you talk to Tableau about Power BI, get them to answer also the points I made in Part 2 of “Power BI vs. Tableau” blog.

Hey Cortana, where is Power BI data?

A Power BI presentation is rarely complete if someone doesn’t ask me to demonstrate the Cortana integration. However, unlike everything else in Power BI that gains features in time, in my opinion the Cortana experience has lost some value. Previously, you could ask natural questions in Cortana across datasets, just like you can use the Power BI Service Q&A to gain insights from dashboards. Unfortunately, Microsoft has removed this feature in favor of searching for report pages that are specifically optimized for Cortana (also known as Cortana answer cards). You can also search dashboards and reports by name but that won’t get you the “vow” effect since 1) you need to know the name and 2) when you click the name Cortana opens Power BI in a separate browser window. So much about natural queries and machine learning. I think the change took place after Microsoft decided to move away from Cortana natural queries to Microsoft’s Azure Search Service.

UPDATE 11/7/2017: I’ve heard from Microsoft about the Cortana change. Previously, you could ask natural questions in Cortana across datasets, just like you can use the Power BI Service Q&A to gain insights from dashboards. However, Microsoft noticed there were a large percentage of cases where customers were enabling Q&A in Cortana simply to search for reports, without intending to ask natural questions. This was resulting in unexpected Q&A ad-hoc results showing up in Cortana answer lists, leading to user confusion. So, Microsoft decided it would be better to restrict results to Cortana answer cards until Power BI supports configuration settings to allow model authors to explicitly control whether ad-hoc answers should be enabled as well.

Back to the Cortana answer cards, they appear to work only for datasets created in Power BI Desktop. They don’t work with the Power BI samples, nor they work in reports connected to dataset created directly in Power BI Service (e.g. by importing an Excel file).

Nevertheless, with the rising popularity of voice technologies (Alexa, Siri, Cortana), you’d probably still get the “vow” effect. And, even better, the reports are now interactive!

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Can’t get enough from Cortana or get it to work at all? Try the “Troubleshoot Cortana for Power BI” article at https://powerbi.microsoft.com/documentation/powerbi-service-cortana-troubleshoot/?

Power BI Service in Get Data

Scenario: You have published a Power BI Desktop file with a report to Power BI Service. You want to give certain users access to some pages in the report. This is not a security mechanism although it could be, if you want to control security at the report layer.

Solution: When a customer asked about this scenario, my first thought was to create reports directly in Power BI Service. For example, the report that’s included in the Power BI Desktop file could have some visuals that you might want to share with everyone. Then, you create additional reports for each group of users and share them via dashboard sharing. This approach will work but if someone nukes the dataset, your reports go down with it. True, you can export a report connected to a dataset created in Power BI Desktop but who bothers to back up reports on a regular basis?

Then it dawned on me that you can connect Power BI Desktop live to a published dataset, just like you can connect to Analysis Services (recall that datasets published to Power BI Service are hosted in Tabular).

The major benefit of using Get Data->Power BI Service is that you can still back up the Power BI Desktop file and your reports with it.

Another benefit is that you can treat the published dataset as a “semantic layer” and let users create reports from it without importing data. For example, instead of asking users to call a stored procedure passing parameters and importing data, you can export all the required data and publish it to Power BI Service. Then, all users have to do is to connect to the dataset and start creating reports.

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