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Power BI vs. Tableau (Part 3)

pbivstableau

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 And their marketing materials should have a timestamp since Power BI improves every month and points get outdated quickly (see the first part 1 of my blog).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.

Power BI vs. Tableau (Part 1)

As I mentioned in my blog “Why Business Like Yours Choose Power BI Over SiSense”, expect attack from other vendors to intensify as they find themselves fighting an increasingly uphill battle against Power BI. As we’ve seen, Power BI has indeed disrupted their sales cycles. In this blog, I’m reviewing the “10 Ways Power BI Falls Short” presentation that Tableau has published on their site. Tableau, of course, is a fine tool for what it’s designed to do – mainly self-service BI. But as we’ve all seen tools come and go as seasons. A few years ago it was all about Qlik, then Tableau, and now 2016 seems to be the year of Power BI. My advice has always been that the focus should be on sound strategy, data integration, and data quality, and not tools. The last thing you want is a “cool” tool that over promises but under delivers and you’re left with nothing when you decide to move on (and some of the vendors really cross the line during their sales pitch). So, we have to keep them honest!

Anyway, let’s take a look at some the claims that Tableau has made by going through their slides. This is, of course, a one-sided perspective that extolls the Tableau virtues. I plan a future post “10 Ways Tableau Falls Short” to fill in the gap. Also, Tableau should get in the habit to update this document frequently given the fact that Power BI changes weekly and some of the claims are no longer valid.

  1. Missing outliers are lost insights – Tableau has a point here. For some obscure reason, Power BI developers has decided to apply a data reduction algorithm to favor performance over details. True, this might result in lost outliers with thousands of data points. I recommend Microsoft allow end users to adjust the data reduction settings. I know this limitation is high on the wish list and I expect it to be addressed/lifted really soon. UPDATE 9/13/2017 – As of this date, all Power BI visuals except map supports rendering of all data points.
  2. Difficult to answer easy questions – This refers to the fact that currently Power BI doesn’t support auto-generating common calculations. Fair enough, Power BI doesn’t support this yet but the statement “you’ll need to learn DAX first” is somewhat overloaded. There are plenty of DAX examples online of how to implement common calculations so there isn’t that much to learn. And DAX is much more powerful than Tableau expressions. UPDATE 10/1/2016 – Power BI introduced Quick Calc with the Percentage of Total being the only one currently available. UPDATE 4/3/2017 – Better yet, Power BI introduced Quick Measures, which supports various prepackaged calculations and show the DAX formula.
  3. No trends or forecasting available – Power BI just added trendlines. For now, forecasting needs to be done either in Excel or R. I don’t know why Power BI still hasn’t picked the linear forecasting capabilities that Power BI for Office 365 had. Another feature that is very high on the wish list so I don’t expect you have to wait long for forecasting. UPDATE 10/1/2016 – Power BI added forecasting.
  4. You can’t compare several categories – If I understand this correctly, it refers to ability to drill down across multiple categories. Power BI matrix reports should get the job done. Also, Power BI has recently added the ability to drill through chart data points.
    050416_0229_PowerBIvsTa1.png
  5. Filtering is tough – Tableau is correct that Power BI doesn’t support context filtering but the statement “You’d have to take the time to filter everything around it, one-by-one, instead” is overloaded. It shouldn’t be that difficult to filter out values using visual-level, page, or report filters. It might take a few more clicks, but I won’t consider this to be a major limitation.
  6. Half the details = Half the insight. True, Power BI tooltips are not yet customizable. Should important information be in tooltips though and require hovering from one point to next? UPDATE 10/1/2016 – Tooltips are now customizable.
  7. Organizing your data is difficult – True, Power BI doesn’t support dynamic groups, e.g. by lassoing some scatter points. I personally haven’t heard users complaining or asking about it so I don’t consider it to be a major limitation. Power BI does support hierarchies. UPDATE 11/1/2016 Power BI Desktop October Release introduced dynamic groups and binning in charts.
  8. No offline iterations allowed – “In Power BI, you can do some basic web editing, but you can’t download it to your desktop or work offline” This is incorrect. First, web report editing it’s on a par with desktop editing. Second, a best practice is to create your reports in Power BI Desktop and upload to powerbi.com. If you do this, you can download the pbix file and work offline. Moreover, Tableau web editing has more limitations than Power BI.
  9. You can’t tell a story – Outdated. Power BI added a Narratives for Power BI. Coupled with Quick Insights, these features surpass the Tableau capabilities. UPDATE 10/9/2017 Power BI also added bookmarks, selection pane, and spotlight.
    050416_0229_PowerBIvsTa2.png
  10. You can’t ask what-if questions – True, Power BI doesn’t support What-If natively yet. If this is important, you can export the visual data to Excel and use the Excel what-if, goal seek, and scenario capabilities. UPDATE 9/13/2017 – August release introduced What-If parameters and analysis

Overall, I believe that some of the points Tableau makes are insignificant while Power BI has already addressed others. Agree? Stay tuned for a “10 Ways Tableau Falls Short” blog.