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For many years now, Business Intelligence (BI) has been among the top priorities on CIOs agendas all over the world. The need to report, to answer business relevant questions, to measure key performance indicators (KPIs), to foreseen trends and predict future results have driven this behavior so far. In short, it has been a quest for planning, monitoring and measuring enabled by BI tools, vendors and specialists.

All well and good, but a first question strikes the mind: what is Business Intelligence to begin with?

What is Business Intelligence?

Besides the original question “what is Business Intelligence?” It is possible to ask further more: what are its boundaries and limits? Where does it ends and other subjects begin? Which tools are encompassed on it? Which concepts are part of it or simply related to it?

Previously mentioned questions will be answered in a simplified manner on this article in order to contextualize the discussion of a possible retirement of Business Intelligence. It is important to highlight that it is not the intention of this short article to answer deeply those questions, which are after all, subject for debate. Having it said, the proposed definition goes as follows.

Business Intelligence is a collection of concepts, tools and software that allows an end-user or an analyst to measure, explore and analyze data with one or more of the following objectives:

  • To comprehend and find patterns (data mining);
  • To automatic create proposal for planning, production and so on;
  • To generate and evaluate trends;
  • To create and analyze historical data;
  • To compare, combine and analyze data from several source systems;
  • To compile and analyze non-structured data;
  • To allow for scenario creation and simulation.

Here, it is worth to say that different software vendors and specialists would include additional objectives on the BI spectrum like planning, forecasting, Balance Scored Card (BSC), Corporate Performance Management (CPM), etc. Others would maybe exclude some of the listed objects under the argument that those are entirely different subjects (like data mining, for instance).

Others would even debate that clearly, from a technical point of view, Business Intelligence also comprehends Data Warehouse (DW) and Extraction, Transformation and Load (ETL) tools, which the proposed definition lives out of the BI umbrella, for choosing to focus on a more end-user perception.

Although it is a relevant and complex discussion, if certain concepts are part or not of the BI definition, it will not be directly relevant to the proposed discussion “Is it time for Business Intelligence to retire?” And for that reason, this discussion will be put aside.

For the sake of our proposed discussion, it is important to understand why Business Intelligence is the way it is today. For that reason, it is worth to invest some time understanding how did we came where we now stand on Business Intelligence terms.

How did we came where we now stand?

It is clear, that the need for Business Intelligence architecture and set up as it now stands, was not entirely driven by business demands. Technology restrictions are deeply embedded into the overnight loads, the different database and application servers, the complex master data handling, the special data modeling and the abundance of reporting tools.

Those technology constrains mentioned above were mainly given by hardware limitations. Such as: the amount of CPU processing power, the amount of memory available, the energy consumption, the energy inefficiency (which resulted in overheating problems), low data transfer rates, low I/O (input/output) rates, components size and many others.

However, there were some other limitations even when from a purely technical standing point, it was possible to deliver a more efficient architecture and set up. One of those factors, were investment costs, for example, which configured itself as a huge and very definite limitation factor.

Moreover, it is not difficult to see that different components of Business Intelligence and its surroundings are delivered today in different maturity levels, which makes its integration far from optimal. While some of its components’ origins can be traced back to the 1980’s like the Data Warehouse, for example; a few are only reaching its, so to speak, puberty towards its full potential, as we can see with In-Memory computing, self-service BI, mobile BI, etc.

Ultimately, business maturity itself is a hard constrain in any technological advantage. Let us not forget that twenty years ago, personal computers were mainly used in organizations for optimize processing time, like for payroll, for example. At that time, it was out of scope for most corporations to apply computers on analytical tasks.

Even today, there are different maturity levels when comparing different organizations and even comparing different departments within the same organization. For that reason, it is important to understand, in general, where Business Intelligence presently stands.

Where do we stand presently?

From a Business Intelligence standing point, I believe we stand in the edge of a technological era. The sign are there to whom is willing to see:

  • Hardware components are exponentially more efficient (faster, more powerful, better energy consumption, etc.);
  • Hardware costs are constantly decreasing and high-end components are now available for a wider base of customers;
  • Software vendors are taking advantage of the new hardware paradigm to propose new and innovative solutions like SAP HANA and Oracle Exalytics;
  • New surrounding technologies are mature to be used: cloud computing (as Amazon and Google are making it popular) and mobile (as Apple and once more Google are changing our every-day reality with those amazing mobile devices) only to mention a couple of examples.

Besides the above listed purely technological signals, organizations are living in the social media era, where getting quality information on time anywhere is a key differentiator. For retail companies, having social intelligence, meaning Business Intelligence on social media information, is no longer a nice to have, but it is a critical business functionality.

Extrapolating even further, Business Intelligence end-users and analysts, also have high standard expectations to be met. We are exposed to high technology products, such as smart phones, smart TVs, tablets only to mention a few examples. And for that reason, we – as customers – are not willing to be satisfied by an old fashioned pie chart.

Which makes us think: what is it coming next? Where are we heading next? That is what we are going to discuss in the next article!

Do you want to read the second part of this post? Check it out at: Is it time for Business Intelligence to retire? - Part II

Best regards for now

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