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Tableau Desktop Review: "Worked superbly for analyzing web traffic data."
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Updated December 29, 2016

Tableau Desktop Review: "Worked superbly for analyzing web traffic data."

Score 10 out of 101
Vetted Review
Verified User
Review Source

Software Version
6.0
Modules Used
Client

Overall Satisfaction with Tableau Desktop

We use Tableau Desktop mainly to analyze operational data for our consumer-facing website. This involves data from our own web application (sometimes via database connection, sometimes via flat file exports) as well as Google Analytics data (both traffic and events data). We have one user (me) who runs weekly reports that mash up the data from the operational systems and Google Analytics, and then syndicate the output via emailing PDFs of the standard reports around. I also do ad hoc analyses from time to time to try and spot patterns, trends, answer specific questions etc. and sometimes those make their way into the standard weekly visualizations shared with the team.
  • Tableau is an excellent tool for quickly making sense of millions of rows of data. It does an excellent job of recognizing facts and dimensions in denormalized data files (say CSV or Excel) as well as connecting to larger databases. The learning curve is slight but not too steep if you are comfortable with Excel Pivot Tables or similar.
  • The visualizations are particularly good as well, as there is a good library of them as well as an auto-suggest feature that for a given series of dimensions and metrics will recommend what chart types might apply. If you have data it recognizes (or is typed) as zip codes for instance it will recommend a geospatial / map visualization.
  • If you have broader enterprise needs for data security and segmentation, heavy duty report customization, or data transformation, this is less comprehensive a tool than other enterprise BI packages (e.g. Business Objects, MicroStrategy, or similar). That said, what it does, it does amazingly well and at a tremendous value.
  • One minor annoyance is that formatting applied to a workbook doesn't carry throughout or get remembered as a template. The default choices for font sizes tend not to export well to presentations or printed text, and having to hand-enlarge every axis label every time gets obnoxious. I've seen third-party tools developed specifically for re-using formatting selections across one or multiple workbooks.
We were interested in expedience at reasonable cost and so didn't do any sort of bakeoff, but tried Tableau first as a potential solution for moving beyond Excel for large scale data analytics. We picked it because it more than met our functional needs at a very reasonable price point. If I were looking again today I would compare Tableau to Qlikview, Birst, and a few other players. But I'm satisfied with the choice we made and results we've gotten from Tableau.
The price is excellent for what the software does, and Tableau continues to listen attentively to customer feedback and makes continuous improvements to the products. At a percentage of the relatively low entry price point, maintenance is a no-brainer and a bargain.
We just have a single user and syndicate reports by emailing PDFs around. This is a cost-effective answer but clearly not scalable for larger organizations who have other options (Tableau Online, Tableau Server, etc)
The variety of sources supported is pretty good and ranges from :
  • standard RDBMS/OLAP to
  • CSV/Excel (with workbook support) to
  • Query-Optimized stores like Vertica, Netezza, etc to
  • Native application connections for Salesforce, Google Analytics, and some others
Specifically the Salesforce connector is particularly useful and saves a lot of export/extract/integration pain and gives you far better visualization capabilities than you'll ever get from Salesforce itself.

All of that said the merging from disparate sources ("Data Blending" in Tableau's nomenclature) can be slow and cumbersome and take a tool that quickly manipulates millions of rows in real-time to a sit-and-wait experience if you're mashing up hundreds of thousands of rows from multiple sources and using Tableau's engine to do it.
Tableau Desktop isn't really designed to be a self-inclusive sharing and collaboration tool for BI. It does however publish seamlessly to Tableau's Server or Online (basically cloud hosted server) editions. But access control, etc. is pretty much handled at the database layer (this is not a data warehouse), and collaboration of the Desktop product is limited to shipping workbooks around (or sharing via Dropbox or similar) so people can use Tableau Reader to see them, or printing to PDF and syndicating that way.
Visualization is where Tableau really shines, and the speed of interactivity (even with large datasets) makes it possible to quickly find the right visualization from the bag of tricks that helps tease out patterns in your underlying data. When you couple speed of interaction with richness of visualization capabilities, it becomes easier to truly explore your data and ask and answer questions that otherwise you might not bother with (just out of sheer complexity of torturing SQL or writing Hadoop code or whatever option might exist).
We were satisfied enough with Tableau that it would take something pretty amazing to get me to switch away from it as a go-to visualization and analysis tool, or "pivot table on steroids". It's best suited though to situations where you have your data either in a single tabular format, or where you can run a single query against a single data source to get a single tabular format answer as the basis for generating your visualizations. Tableau does have a data blending feature that is useful, but if you use it when connecting to multiple large third-party data sources (for instance two connections to Google Analytics, one to get traffic metrics and one to get more detailed event counts and join them up on landing page, channel, etc...) then the data blending process can get pretty cumbersome. It's better to stage your data outside Tableau in one format (be it a single SQL database, CSV, or whatever) via some other ETL process than to try and get that done via data blending in Tableau.

Tableau Desktop Feature Ratings

ETL Capability
Not Rated
Pixel Perfect reports
7
Customizable dashboards
8
Report Formatting Templates
5
Drill-down analysis
10
Formatting capabilities
7
Integration with R or other statistical packages
Not Rated
Report sharing and collaboration
6
Publish to PDF
7
Pre-built visualization formats (heatmaps, scatter plots etc.)
10
Location Analytics / Geographic Visualization
10
Predictive Analytics
Not Rated
Dedicated iOS Application
Not Rated
Dedicated Android Application
Not Rated
Dashboard / Report / Visualization Interactivity on Mobile
Not Rated

Using Tableau Desktop

Users and Roles

4 - Tableau was used by a combination of cross-functional employees including:
  • Business Analytics (primarily management and visualization definition)
  • Finance (report definition and execution to PDF etc.)
  • Business Development (interactive use of dashboards)

Support Headcount Required

2 - Technically savvy business analyst types for Tableau. While hard core DBA skills aren't really required, once you want to get into more complex mash-ups of data from multiple sources you do need someone relatively savvy about data types, queries, etc. You'd need more hardcore DBA types for maintaining actual back-end databases if reporting against SQL-queryable databases of course.

Future Planned Uses

  • As we moved into CPC ads, we might have used Tableau as a quick and dirty ad spend optimization tool by driving into traffic and conversion metrics tied to actual conversion values (the high-level flat dollar amounts you can specify in Google Analytics wouldn't work for our real-time bidding platform we would need to mash up data from Google AdWords and our operational systems and Tableau is excellent at that)

Business Processes Supported

  • We used Tableau to analyze web traffic data, including traffic channels and sources, the conversion funnel, inventory mix and categorization, geographic distribution of inventory and inbound traffic and leads, on a dataset of millions to tens of millions of rows.
  • We also used Tableau to report on operating metric performance to plan though it provided less unique value in that situation

Innovative Uses

  • We were able to very quickly generate geographic heatmaps showing automobile inventories across the US, including the ability to filter/drill on various makes/models
  • Similarly we could generate heatmaps across the US to indicate where web traffic was originating
  • Finally, using calculated fields to mash those two up we could quickly and visually pinpoint where supply/demand imbalances existed to direct our business development efforts (e.g. we need more Toyota dealers providing inventory in Atlanta, and we need to target driving more traffic on BMW related search terms in Chicago, etc.)

Evaluating Tableau Desktop and Competitors

Products Replaced

Yes - Greater ease of data manipulation, visualization, and the ability to handle large data sets with fast performance.

Key Differentiators

  • Price
  • Product Features
  • Product Usability
  • Positive Sales Experience with the Vendor
The usability of Tableau really is second-to-none. While with any Business Intelligence tool you're going to have a learning curve, the main barrier to getting value from BI tools tends to be the steepness of the learning curve. Many BI tools have all the capabilities you'd need, but because there's never enough time to properly learn the tool, I'd argue most BI features wind up as 'shelfware'.

Tableau Desktop, however, has an elegant simplicity that makes it easier to come up the learning curve and start performing more advanced analyses more quickly. That was the main factor driving our decision. The reasonable pricing and very helpful sales process were added bonuses.

Tableau Desktop Implementation

Implementation

7

Implementation Details / Implementation Partner

  • Implemented in-house

Tableau Desktop Training

Training Types Used

  • Self-taught

Ease of Tableau Desktop Training

I would watch and learn from the online tutorials which were probably 75% comprehensive. There were still things we had to figure out around the edges, but just using online documentation and videos and following the examples was adequate. Any time the documentation is lacking, there's a vibrant online community at the ready, and some members even jump in to provide example solutions to problems!

Tableau Desktop Support

Support

9
They actively reached out after we purchased to make sure we were getting value from the software, and any time we had a question they were quick to respond.

Premium Support

Yes

Using Tableau Desktop

Usability

8
It is far better than Excel or other visualization tools, but some of the manipulations of data tables, visualizing underlying data, and more novel visualization methods (dragging dimensions to colors or shapes) behave a bit non-intuitively. The custom logic for field calculation could use a more robust script editor. The definition of multi-table SQL joins using the data import / query builder was pretty rudimentary at the time -- it was easier to create the desired extract or table subset as a set of temp tables or CSVs if the data required complex joins. But overall it is very usable.

Usability Pros and Cons

ProsCons
Like to use
Relatively simple
Easy to use
Well integrated
Consistent
Quick to learn
Convenient
Feel confident using
None

Easy Tasks

  • Drag and drop of dimensions and measures
  • Styling of visualizations of all different types is easy
  • Assembling charts and graphs into composite dashboards

Difficult Tasks

  • There are a few things that should be simple that are cumbersome like data blending can be painful to get right and details like totals on top of stacked bars
  • Formatting does not carry over from sheet to sheet and styles cannot be universally applied to a single visualization much less a dashboard -- lots of repetitive manual work to style things visually

Mobile Interface Availability and Impressions

Yes, but I don't use it

Tableau Desktop Reliability

Scalability

10
Tableau Desktop's scaleability is really limited to the scale of your back-end data systems. If you want to pull down an extract and work quickly in-memory, in my application it scaled to a few tens of millions of rows using the in-memory engine. But it's really only limited by your back-end data store if you have or are willing to invest in an optimized SQL store or purpose-built query engine like Veritca or Netezza or something similar.

Reliability and Availability

10
Using the desktop product, I never hit a bug or had a crash.

Performance

10
I was able to maniupulate 10-30 million rows of data on a Macbook Pro with 4GB memory running in a Parallels Windows XP VM and achieve response times of between 1 and 3 seconds.

Integrating Tableau Desktop

Systems Integrated With

  • MySQL Database
Simple and easy.

Upgrading Tableau Desktop

Upgrade Process

Yes - I have upgraded Tableau several times, since version 4 or 5, and most recently from 8.2 to 9.2.5. I've also migrated from the Windows version on XP to Windows 7, in both cases running in a Parallels VM on OSX, and eventually from the Windows version of Tableau to the Mac version.

Every time I've upgraded it has been completely seamless and I've never felt lost, experienced migration headaches or data loss. It's a real tribute to the quality of Tableau Desktop that every upgrade has been so quick and painless.