Changing role of IT in the BI world

BI is Dead, Long live BI

Timo Elliot (blog|twitter) recently published a blog BI is Dead which draws from Gartner’s Magic Quadrant report and a detailed report.

The main take away from the post (which includes references from the Gartner research ,so not all are Timo’s points) include:

  •  The self service analytics tools have matured enough that the involvement of IT in BI and analytics projects is deemed optional. IT don’t need to model the data upfront (which needed gathering all or partial analytics requirements to start with), analysts can prototype and test it themselves.
  •  The balance of power for BI and analytics platform buying decisions has gradually shifted from IT to business.

  • BI and analytics tools which do require intervention from IT are not considered BI anymore; they are Enterprise Reporting Based Platforms. Admittedly, they take most share of the BI market. In other words Gartner has updated the definition of BI.

  • The bold headline – “BI is Dead” – is to gain attention on the changing landscape of BI tools.

  •  Organizations who do not embrace the new definition of BI, run the danger of turning into BI-nosaurs.

  •  Having single view of data through an EDW is pointless/extremely hard. This and this from Curt Monash also support this line of thinking.

  •  Most organizations believe that IT has role to play in BI although majority want the responsibility of authoring the content to end users. This has always been the holy grail of BI.

So it is really dead?

Well-not necessarily. It’s dead in the sense that PCs are dead as we know them from 1980 or before. PCs have clearly evolved: they don’t look like how they used to look and many aspects of PC have been democratized. Trivial things which needed programmer in those days can now be done by users themselves. Heck, you can even upgrade the hardware if you are into that sort of thing.

I think that’s exactly what is happening in the BI and analytics world. The self service analytics tools have evolved to the point that many of the trivial data munging tasks can be done by the analysts themselves and what they can do with these new tools does not look at all like how they have been doing it. Does that mean the BI is dead? No- the fundamental analytics is still the same. It has evolved just like the PCs and the role of IT has changed.

Role of IT in the new BI world

The changing role of IT in BI and analytics can be best described from picture below.

Changing role of IT in the BI world

IT is now viewed as (and rightly so) as data facilitators. They make data available to the analysts in palatable form. The responsibility of modelling it,authoring presentation components and analysis lies with analysts.

Does that mean the job of IT got easier?

Most-Definitely-Not, on the contrary it has got even more complicated. With the influx of new tools, the demand for data has dramatically increased. The analysts want to analyse all sorts of data, from all sorts of unlikely sources and with all sorts of analytical methods. Their expectations from IT is to facilitate this process which is where ITs job has got a lot harder. We have to deal with ever increasing data sizes, from ever expanding sources, and support ever changing analytical tools.

What else is keeping BI alive?

If we assume the following definition of BI,then here are more reasons why BI is definitely not dead in its current incarnation.

BI
:
an umbrella term to describe “concepts and methods to improve business decision making by using fact-based support systems”

1. Not everybody is data scientist

a. Combining data from multiple sources, b. creating data model and c.authoring reports from it, need special skillset. Many a times, analysts just want an Excel connecting to OLAP cube to do their analysis. Traditional BI has a place in this space.

2. Robust production ready solutions

The analysis done in the analysts R code or ipython notebook is not usually production ready. BI will be very much needed when it needs to be productionised.

3. If ETL is part of BI then its here to stay

How else would you provide quality data to analysts otherwise? And if the definition of BI includes methods to improve process of decision making, then we need BI.

4. Operational reporting is a fact of life

As much as we harp about ad-hoc analysis, data science and self-service BI, plain old operational reporting is a big part of any organization. For that we need classic BI.

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