Self-service analytics

For many, the idea of self-service business intelligence, where IT opens up a small menu of capabilities for employees, has not yet produced its promised benefits despite having been around for a few years. It is clearly an improvement on the traditional, IT-run report factory, but it is still too limiting to satisfy people’s ever-growing appetite for information.
So far, self-service BI is more like IKEA’s approach to DIY furniture-making. While it allows us to build our own furniture, it’s limited by factory-manufactured building blocks. As a result, we all end up with the same results despite the process being self-service.
This is not enough when it comes to fostering self-reliance, autonomy, and innovation.
An alternative approach is to give curiosity-driven users a new generation of tools, which will enable them to explore their data and answer their own questions on their own schedules.
This new self-reliant world will become the new normal. Unlike assembling pre-build furniture parts, imagine instead 3D-printing a new coffee table that’s one of a kind and will fit perfectly with your style
Mac Bryla
, here on Tableau’s blog.

There is a movement underway in the BI industry – Self-service Analytics. As described above, it gives the end users freedom to develop their own reports, perhaps only on a small scale of accessibility.

It actually blows me away that it has to take a movement to allow operators to work this way. As an OSS implementer, I’ve had admin-level access on all of the many projects I’ve worked on. With it came the corresponding freedom to run any query or report I wanted, for whatever purpose (diagnostics, gaining insight, reconciliation, recognising associations/patterns, migration, etc), on any data set.

Are OSS operators also so heavily restricted that they need this new movement to unleash them? When specifying / designing canned reports for customers, I assumed that these were to improve the efficiency of repeatedly run data analyses, but that they would be supplementary to operators being able to run ad-hoc reports.

The crux of the self-service analytics movement has a place in OSS too. Rather than having OSS with all of the functionality and logic pre-defined, thus producing swathes of functionality that most customers / operators will never want to use, there is room for simpler tools that allow the enormous flexibility of self-service data interrogation*.

We’re beginning to see it in a relatively new type of tool used in the OSS space. I simply refer to them as data bridges (although I’m sure someone will be able to point me to the name of a more official classification).

* Noting that careful consideration must go into preparation of data views / environments to ensure all this self-service data wrangling doesn’t have a detrimental effect on mission-critical systems (eg production environments).

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