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Analytics: Hang the imposter!

People want to replace the term business intelligence with ''enterprise analytics.'' I don't buy it. At least, not yet.

First, nobody agrees on the meaning of the term ''analytic'' or ''analytics.'' I've polled people in our industry and everyone has a different definition.

Some think ''analytics'' are reports, while others believe they are report components, such as calculations, pivot tables and data access functions. Other people think analytics are key performance indicators or metrics. A few believe they are fancy dashboard graphics (for example, ''stop lights'' or ''car gauges''), and old-timers think analytics refer to sophisticated statistical algorithms or data mining functions.

In my opinion, when something can mean anything, it means nothing.

Then we come to the term ''enterprise analytics.'' Proponents use this to describe next-generation business intelligence capabilities, such as real-time monitoring of key performance indicators and closed-loop processing where the output of analyses are fed back into operational systems. But if this is what ''enterprise analytics'' is, why do we need a new term? Why can't we just call it ''next-generation business intelligence'' and leave it at that?

By now, some of you must be rolling your eyes. So many buzzwords have come and gone in our industry that many of us are numb to them. We mostly ignore them, or we translate them to something with which we are familiar and move on. So what's the big deal?

Despite the industry's constant churning, semantics do matter. Ever since God put Adam in the Garden of Eden, man has gained control over his environment by classifying and labeling things. It's no different today.

Vendors spend a lot of time and money evangelizing terms for new technology sectors, hoping to assert their leadership and steer the market in their general direction. In general, he who coins the terms of the debate defines and controls the market.

Ideally, vendor-neutral organizations, such as The Data Warehousing Institute (TDWI), or analyst groups should classify vendor products and market directions, placing vendor organizations on a level playing field and bringing clarity to the market. (Of course, problems occur when analyst organizations offer competing terms and definitions.)

We all benefit if we can standardize terms and definitions. Many of you are fighting this war within your own organizations. You know the value and business benefits of creating a single version of the truth. What's true for user organizations is also true for markets.

Why business intelligence?
At TDWI, we like the term ''business intelligence'' because its meaning is self-evident. The goal of business intelligence products and services is to make businesses ''more intelligent.''

TDWI formally defines business intelligence as ''The processes, technologies, and tools needed to turn data into information and information into knowledge and plans that drive profitable business action.''

For us, business intelligence is an umbrella term that spans IT-oriented processes and tools to prepare and integrate data for analysis; and user-oriented processes and tools that enable business users to analyze and use information for business gain. To this end, business intelligence encompasses data warehousing and content management, collaboration and knowledge management, ETL and EAI, data mining and text mining, OLAP and portals, and so on.

Unfortunately, most of you may not agree with our definition. Or you may agree, but you don't adhere to it in practice. In conversation, many of us may slip into using the term ''business intelligence'' to refer to front-end analysis tools, such as those from Business Objects or Cognos. This is common, but unfortunate, because it underutilizes the potential of the term. These end-user tools can't work without the underlying data warehousing infrastructure to support them. We can't make businesses more intelligent just by implementing Business Objects -- far from it.

TDWI uses the term ''business analytics'' to refer to end-user analysis tools. We now have a ''Business Analytics'' track at our conferences that contains courses on reporting, data mining, OLAP, visualization, geographic information systems and so on. We think the term Business Analytics is appropriate since the dictionary defines analytic as: ''pertaining to or proceeding by analysis; skilled in or habitually using analysis.'' People use business analytic tools to analyze business data. This makes semantic sense.

However, TDWI is not deluded into thinking we can convince everyone to use our terms and see the world as we do. But we have a professional responsibility to educate our audience and sharpen any fuzziness in the marketplace.

Our task is harder because we (the industry as a whole) have been sloppy in our definition and usage of the term ''business intelligence'' and now we're paying for it. Some want to replace one sloppily defined term with an even sloppier one -- ''enterprise analytics.'' I'll only stomach this semantic sea-change if the definition of 'analytics' becomes crystal clear and there is an undeniable groundswell of support for it.

Until then, come visit me in my Garden of Eden. We'll have plenty of time to enjoy the scenery.

About the Author

Wayne W. Eckerson is director of education and research for The Data Warehousing Institute, where he oversees TDWI's educational curriculum, member publications, and various research and consulting services. He has published and spoken extensively on data warehousing and business intelligence subjects since 1994.

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