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MicroStrategy vs Tableau

By popular demand, here are my thoughts on comparing the current state of MicroStrategy and Tableau, two of the leaders in the BI market space today. What follows are purely my own opinions from my experiences. This isn’t scientific, it’s my opinion.

My Experience

I’ve used MicroStrategy for 9 years, covering every possible crevice of the software and every possible role at organizations of every size I’ve used Tableau for 2 years, using Desktop as a developer and Server as a consumer, also an administrator and only at 1 large company.

MicroStrategy’s Strengths

MicroStrategy has a 14 year head start as a company over Tableau, and as such has a much larger scope in the solutions they provide. They’re historically Enterprise focused with a shift towards the Desktop Analyst in the last few years.

  • Schema & SQL Engine– This is MicroStrategy’s bread and butter in my opinion.  You provide a relational snowflake data model and it will glide right over it, giving you an easy drag and drop semantic layer to build your reports.  Enterprises love it because this is the start of Self Service, where business users don’t need to know complex definitions or code but can craft reports and drill freely.  IT loves it because they can ensure that logic stays in sharable objects and can be easily maintained.
  • Scalability– MicroStrategy has great SQL optimization for a very wide array of platforms which pushes the demand to the database.  In terms of scaling, it’s really more about database pressure than MicroStrategy pressure.  Intelligent Cubes are an option to cache very large amounts of data in your server’s memory if you do want to share the burden.  My general experience has been that these work fantastically well up to about 2gb, pretty good up to about 15gb, and try your luck after that.  (Of course, I’m of the opinion that at those levels you really should be evaluating your database technology, but that debate is for another day.)
  • Administration– Security, tools, statistics and object management enable administrators to keep everything in order.  While these tools leave a lot to be desired from a convenience and polish perspective, they’re perfectly functional and do pretty much everything you need.
  • SDK / Hackability– This one is borderline for me, but the fact is that while you really can customize anything on the web, the documentation and samples make it pretty much impossible.  That said, I have found what I call MicroStrategy’s “jailbreak” by injecting jQuery into dashboards which let you do some pretty cool things on the fly.  Even though they didn’t intend it, it’s still nice that the platform is flexible enough to hack on.
  • Mobile– I’m not a fan of Mobile BI.  I think the target use case is very niche and it’s just a fancy demo that doesn’t have longevity.  Jaded or not though, there’s no doubt that MicroStrategy has the premiere Mobile BI platform in the market.  I’ve seen some really amazing apps built on it, and without writing a single line of code.  If Mobile BI is your thing, it’s pretty hard not to love it.
  • Emails– If your users love formatted emailed reports, MicroStrategy has a great ability to send out what you see on the web in HTML or PDF form.  They’re still in a weird place after trying to deprecate Narrowcast for 5 years now and still not matching all of its features. (Narrowcast being a more fully featured external email bursting application that was “deprecated” in favor of Distribution Services which is native but lacking most of the flexibility).

MicroStrategy’s Weaknesses

  • Development Environment–  Developing on MicroStrategy has become very painful.  Development can be done in either a Desktop application that is a blast back to 1998 or a Web application that doesn’t have parity with Desktop and worse: many options that do exist in both are in different places with different styled UIs.  The Desktop application is still where you need to do your work but it’s so miserable to develop in that it irritates me to the point I don’t want to open it again.
  • Development Speed– Despite the Schema & SQL Engine being its biggest strength, it’s also its biggest crutch.  As powerful as this concept was, it’s just not where tech and analytics has gone.  It’s a solution for an old age when the user community wasn’t technical, when analysts were better at math than software, and a priesthood had to anoint data in order for normal people to use it.  The most powerful features in MicroStrategy are built on this concept and require a tremendous amount of up front development and design before you can even see the first number.  Businesses move at a faster speed these days, and with consumer technology putting instant access to all of humanity’s knowledge in each of our pockets, we just don’t have the patience anymore.  Visual Insights is MicroStrategy’s solution, but it feels like it’s tacked on and doesn’t have enough of the features you’d need to use it for any real work.
  • Visualizations– The graphics you get out of the box in a MicroStrategy report are unusable, and formatting them to be presentable takes longer than building the schema.  Graphs in the web are actually images returned from the server with image maps overlaid.  This makes tooltips frustratingly useless since you often get a 1 pixel hit box, and the images don’t resize if you’re on a large monitor or small laptop.  There was a short detour into Flash widgets at one point in their history, but these only work in some modes, and with few fancier HTML widgets randomly thrown this all creates a muddled visualization experience.  Since the primary role of a BI tool is to visualize the data, you may think it’s strange that this would be weakness.  I believe the reason is that MicroStrategy was magical at delivering “an answer” in a time when that was not a trivial thing to do.  Now, delivering the answer isn’t enough .. it has to be in a consumable, explorable format that tells a story and guides to results.  A sheet of numbers is never going to do that.
  • Community– With no offense intended to anyone reading this, the MicroStrategy community is non-existent.  There are a few blogs out there with a couple of ideas (not counting mine, which is the best ;), but none that seem to last more than a couple of months.  There are a few people on the forums that diligently help out, but I haven’t posted to it in over 2 years and I’m still the #4 all time contributor.  No one gives back and MicroStrategy doesn’t do anything to encourage a community or support those who do.

Tableau’s Strengths

Tableau started out as a tool for data analysts and has slowly moved into the Enterprise space.

  • Development Speed– Speed kills.  Throw any data at Tableau, in nearly any format, and it can slice it up in a visual manner almost immediately.  If you have decently formatted data, you go from raw to dashboard in minutes.  Even complex tasks are simplified and great visualization practices are baked right in so the default view is pleasing, functional and interactive without having to touch a single formatting control.
  • Development Environment– Developing in Tableau is delightful.  So much care and precision is put into every pixel and interaction of the application, you’d think Apple designed it.  I often joke that the confidence curve for someone learning Tableau starts out (on a scale of 1-10) at a 7, dips to a 4 the more they use it, and then ends at 8.  The reason is because the things you most likely want to do are literally a click away and intuitively where you’d expect, so newbies feel empowered and infinite.  Of course, once you need to do something that’s not a 1-click action, things get complicated and you crash down to reality as you see your limitations (more on that in the weakness section).
  • Visualization– The default visuals you get are pretty much perfect out of the box.  You can of course tweak most of the settings that you want, but it’s just details at that point.  If you never format anything, your dashboards will look great, and with a few basic options in intuitive places, you’ll have rich interactivity like click-to-filter, formatted and responsive tooltips, and responsive web layouts.  Tableau put a ton of research into their tool, and nothing is left to chance.  Even the color palettes are very carefully chosen based on tons of scientific research into the human eye and brain.  (Those are stories for someone else to tell since I’ll mangle them, but that part of their history is really cool).
  • Community– This part is incredible and nearly impossible to describe, but I’ll give it a shot.  I already mentioned the care and level of detail they put into their product, which is the first evidence of their commitment, but they really instill passion in the community.  They have an incredibly active forum, there are thousands of blogs (while my MicroStrategy readers may think I’m special, there are probably 50+ high end blogs in the Tableau community .. that may even be a conservative count).  There are user community meetups in almost every city, people buy and wear t-shirts with Tableau’s logos on it, and the best part of all of this is that Tableau fully embraces it.  They hold community events, they let customers vote on what features they want and they build the top ones, and they honor the top community contributors with insider access and direct feedback lines to name a few things.  Going to a Tableau conference is the best experience you can have if you’re at all interested in data, because the conference is not about Tableau .. it’s about data.  They’re a company that is passionate about data, so they built some tools to help unlock it’s value.  Half of the conference isn’t even about the tools, but the theory of visualization, statistics, and how it interacts with the human element.  The parts that are aren’t really about the product, but how to use them for specific purposes.

Tableau’s Weaknesses

  • Performance– Since Tableau’s roots are for the desktop analyst, they’re very immature at an Enterprise level.  There are very large issues involved with even modest amounts of data by today’s standards.  To get technical for a minute, a dashboard contains multiple components (filters, graphs, tables), and each one executes its query serially.  That means that if there are 4 components that take 2 seconds to load each, the dashboard will take at least 8 seconds.  Worse, while you’re invited so effortlessly to use analytic functions on the fly, they absolutely bury any measure of scalability.  Whereas MicroStrategy isn’t even stretching its legs with a few gigs of in memory data, Tableau starts to fall on its face.
    (Edit: As expected, I got the most feedback on this point.  I think I should restate it a little, but I’ll leave the original post intact.  I think Tableau’s scale problem is not actually Extracts or data volume, but Table Calculation performance.  Those shortcuts which the UI encourages you to use through it’s 1-click nature perform very poorly whether you’re on an Extract or querying live.  In some low sample, highly subjective tests, we’ve found that a 2m row dataset with lots of table calcs can perform way worse than a 100m row dataset with no table calcs.  I think this is why some people have the experience of Tableau not handling anything above an Excel spreadsheet and others saying it scales just fine.  I don’t know enough about Tableau under the hood to say this is definitely the reason, but just remember that data comes in all shapes and sizes.  Rule of thumb, I don’t think anyone is arguing that Performance is generally a weakness for Tableau, especially when compared to MicroStrategy).
  • Complexity– The reason your confidence curve will dip is because as easy as the easy stuff is, the hard stuff is practically impossible.  You’re teased with the promise that it’s just a few clicks away if you could only find the right combination of options, but you’ll eventually start to see the rails you’ve been riding on all this time.  There are some clever hacks and workarounds that the community will come up with, but in the same way that MicroStrategy painfully makes you format visualizations, Tableau painfully makes you figure out how to do intuitive calculations.
  • SQL– Tableau has some very basic support for database joins and in-memory joins, but you practically need to give it your dataset pre-structured for consumption.  What’s shocking to me is that while this isn’t a requirement in MicroStrategy, universally MicroStrategy developers are far better at SQL than Tableau developers (and I have a very large sample set of interviewees).  I personally don’t see how you can use Tableau without a master’s degree in SQL, but most people seem to manage.  It does destroy the principle of “one version of the truth” since nothing is really centralized (you can share data sources, but I haven’t found that very practical).
  • Object Management– Tableau doesn’t have objects in the way MicroStrategy does and doesn’t really have a concept of Dev and Production.  You can download reports and dashboards yourself as files and back them up in a system, but that’s external to Tableau.  There’s no versioning and pushing to production is all or nothing.  Dev is practically your local desktop, so test well and make backups!
  • SDK / Hackability– The Web SDK is pretty bad and effectively useless.  Aside from the strange requirement of needing to wrap your visualization in an html file (which means you can’t host it on your Tableau server with everything else), there just aren’t enough hooks exposed to do anything useful and the ones that are are slow and bulky.  It’s also not hackable at run time because all of the dashboard components are rendered on canvas or as images (even text!) so there’s nothing you can really touch and manipulate.  That said, we have discovered the equivalent of Tableau’s “jailbreak” which promises to usher in a new generation of never before seen hacks (teaser!)

General Design Recommendations for Dashboard

  1. Focus on Data first
  2. Design the dashboard with your target audience in mind
  3. Keep related data on a single screen
  4. Pay Attention to object placement
  5. When possible limit number of metrics
  6. Focus on Important Indicators like Trends, Variances and Performance States
  7. Group Like Items or Comparison Items Together
  8. Use white space or thin grey lines to separate groups of data
  9. Keep simple navigation in mind
  10. Limit the number of fonts in a dashboard

Explain what is Microstrategy?

Microstrategy is an enterprise business intelligence application software vendor. It supports scorecards, interactive dashboards, ad hoc query, high formatted reports, etc.

Mention what specific features and functionality do you get with OLAP services?

With OLAP services users can create a unique report views by removing or adding attributes and metrics contained within the intelligent cube. Without submitting a new request to the data warehouse, the new calculation is performed.

Explain how intelligent cubes are different from ordinary cubes?

Intelligent cubes are generated automatically when a new report is run against the data warehouse. Users don’t have to mention the cube to which they want to connect. Within the Microstrategy platform, the logic to match user requests with the proper intelligent cube is automatically handled. Subsequently the requests made by other users can seamlessly hit this new intelligent cube.

List out the end user products that delivers OLAP Services?

End user product that delivers OLAP services includes

  • Microstrategy Web
  • Microstrategy Desktop
  • Microstrategy Office

They all leverage the functionality enabled by OLAP services

Explain what is the difference between the Report filter and Report limit?
  • Report limit: It determines a set of criteria used to restrict or limit the data returned in the report data set after the report metrics are calculated
  • Report Filter: It applies the where condition to the query sent to the warehouse to retrieve the results
Explain what is Logical view in Microstrategy?

In Microstrategy, logical view is a table that you create by writing the SQL in Microstrategy instead of pulling it out from warehouse catalog.

Explain what is Smart Metrics in Microstrategy?

Smart metric is referred when a compound metric is defined with other metric objects using arithmetic operations like sum M1/M2.

For example: Simple or Compound Metrics Total (profits/unit sold) Smart Metrics: Total (profit)/ Total (sold)

Mention what types of testing can be carried out over the Microstrategy reports?

Microstrategy can carry out test like

  • Naming convention tests
  • Total calculations test
  • SQL query validations
  • Attribute and metric positions in the report
  • Drilling options tests
  • Prompts related verifications
  • Security filter tests
  • Formatting/export functionality tests
  • Threshold testing
Explain what is Microstrategy Narrowcast server?

Microstrategy Narrowcast Server is a software product which monitors and delivers individualized information to users through e-mails, web portals and wireless devices like pagers, PDAs, and phones. Users determine what information they want, when and how they want to receive it, through an easy to use web page.

Explain what are the advantages of dataset compared to file-set?

File set consists of total tables and information while data-set consists of attributes, metrics of a particular report only.

Explain what security does Microstrategy provides?

Microstrategy provides many security options to make sure that data is kept private and confidential. To make easy access and minimum maintenance, Microstrategy desktop synchronize with Windows NT and 2000 security and with Novell directory. Due to that users who have logged into these systems does not have to log on again.

Mention what is the difference between Schema object and Public object?

Schema objects are availed to create Application objects like Attributes, functions & operators, Hierarchies, Tables, etc. While, Public objects are used to create other application objects like Filters, Metrics, Consolidations, etc. Using architect permission schema object can be created while public object can be created by using a schema object only.

Explain what is Listeners?

Listeners allows us to view the result of samplers in the form of trees, graphs, tables or simple text in some log files. They offer visual access to the data collected by JMeter about the test cases as a sampler component of JMeter is executed.

Explain how you can resolve attribute roles?

By creating separate table alias for the same or enabling the automatic attribute role recognition, you can resolve the attribute roles.

Mention what does the predictive modeling capabilities does Microstrategy provides?

Microstrategy can calculate four of the primary data mining functions including network algorithm, regression algorithm, clustering algorithm and tree algorithm.

Explain how you can direct the SQL generated to use a specific table?

We can use alias name of that table and alter the logical size of that alias table dnt then modifies main table and use the alias table.

Explain how you can insert and update a record in the database through Microstrategy?

You can insert and update or even a delete a record by using one of the components of Microstrategy known as an ODBC test tool. You can also alter table specification as per your need.

Mention what is the difference between Microstrategy and Cognos?
                           Microstrategy                                  Cognos
  • Microstrategy is based on single meta-data repository
  • Microstrategy can be operated as web based and a desktop tool
  • There is no cube data-set for Microstrategy, and we obtain latest data-set from data-warehouse automatically
  • Microstrategy reporting is fast
  • Cognos has two meta-data repository based database
  • It can be used as web-base reporting tools
  • Cognos has a cube dataset which needs to be refreshed in order to get current repository values before reporting
  • Compare to Microstrategy, Cognos reporting is slow
Explain how you can create the intelligent cubes in Microstrategy?
  • Intelligent cubes can be made in Microstrategy in the public folder or a particular user folder
  • We can make a report and point the report to a cube or right click in a folder and select the cube option to make a new cube
  • Once the cube is created, select the report objects which is required and save the cube
  • Once the cube is stored and ran to check, one can create multiple reports out of a cube
  • You can also add new attributes and metrics, whenever necessary, and those will be readily available when you run the reports next time
Explain how you can optimize a report in Microstrategy?

VLDB properties enable you to customize the SQL that Microstrategy produces, and determine how data is processed by the Analytical engine.

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