A Condensed Introduction to Data Analytics

A Condensed Introduction to Data Analytics

As you begin the search for a business intelligence platform you will be barraged with a confusing mix of terms. These can include any of the following: data analytics, predictive analytics, data modeling, data mining, data integration, data preparation, and many, many others. Ironically, the nomenclature being used by the software providers peddling their tools must first be simplified in order to extract real business value. First things first, a quick definition:

Business intelligence is the science of analyzing business data wherever it exists within your organization or elsewhere in order to understand what has happened in the past, why it happened in the first place, what can be expected to happen in the future and why that might happen differently given different behavior.

Despite what you hear from other analyst houses and the vendors themselves, analytics is not a solution category, but rather the prominent feature in the overall scheme of business intelligence. In simpler terms, companies do analytics with the aim of acquiring intelligence.

That being said, there are a host of companies who will not mention the term business intelligence at all but rather refer to themselves as an analytics platform or as a modeling, mining or data discovery solution. Again a bit confusing, but keep in mind that the goal throughout your search for a BI provider is to select a solution that helps you establish a needle and then makes it easier for you to move it. Getting all of this data into a place where it can be analyzed is the job of data integration tools, which you may see as an added feature of a business intelligence platform. Additionally, data management platforms help companies organize, clean and store their information for analysis either in real-time or at a later date.

Several evolving circumstances will be driving this category over the next decade. Most notable is the trending concept of big data, which is neatly defined by Wikipedia as “a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications.”

While you will hear lots of talk about BI’s capacity to handle big data, it has been our experience that big data will not be your primary driver as you select an analytics provider today. Another major influence on the BI landscape is the prominence of the cloud. Almost every major BI provider is offering a cloud-based solution; some exclusively and others alongside their on-prem capabilities The main benefit of a Software as a Service approach is the reduction in cost. The balancing consideration for your enterprise is the question of security.

The overriding consideration for everyone looking at an analytics provider is the scope of features each offers. But, as stated at the beginning of this introduction, business intelligence is not a feature; it is a result. Analytics, modeling, reporting, strategic visualization and data mining are all the features you should consider and it will be the strength of those components that will enable the best provider to emerge for you.

Consult our buyer’s guide for an even deeper overview of the BI and analytics marketplace, as well as full, one-page profiles of the top-28 providers.

Tim King
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