Want Better BI? Roll Up Your Sleeves and Get to Work

Loraine Lawson
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7 Steps to Smarter Integration

Sometimes, change can be worthwhile. The key is knowing what's worth pursuing and what's not.

Wouldn't it be great if you could reap the benefits of whatever you want, without all the hard work? It really would. Unfortunately, that's just not how things work, particularly when it comes to technology.


It seems more companies are (slowly) waking up to the reality that the benefits of business intelligence (BI) won't happen without the hard work of creating cleaner, more integrated data, according to a recent Information Week article.


This year and last, Information Week surveyed IT professionals about their companies' progress on BI. Last year, 534 responded; this year, 410. The surveys found that companies want to be "agile"-meaning, able to learn about and react to changing information-when it comes to BI, but they've been a bit in denial about what it takes to achieve that agility.


The graphs combine the results of last year and this year, so it's not exactly clear why the writer thinks this situation is changing, except he states that when you compare the two years, "... there's a growing realization, or perhaps it's resigned acceptance, that better business intelligence goes hand in hand with the thankless task of better information management."


Let's hope so. It's no big secret among data practitioners that if you want better information, data deduplication, cleansing, quality, governance and, yes, integration are all critical components.


One thing that amused me about the survey was that when queried about the barriers to information management, the top response was "reliable timely data" at 59 percent. I say "amused," because it was followed by cleansing, deduplication and otherwise making data consistent at 51 percent and integrating data and data federation at 49 percent-even though, let's face it, those two are foundational for creating reliable, timely data.


Data quality problems and integration/compatibility issues were also listed among the top three barriers to adopting BI tools across a company.


Despite the fact that integration and data quality ranked so high in concerns, when it comes to actually buying a BI solution or evaluating a vendor, the ability to integrate with enterprise applications such as ERP and CRM ranked fairly low on the list of considerations, with 51 percent citing it as a concern-placing it fifth on the list of seven concerns. It does look like respondents could choose multiple options, but given how high integration and data quality ranked on the other lists, I think the fact it barely garnered a majority reflects that disconnect between wanting better BI and paying attention to the necessary details.


The article offers more than a survey wrap-up, however. It also looks at how different companies are addressing some of these gaps. For instance, Pfizer is replacing ETL with data virtualization using a solution from Composite Software. The company's director of business integration actually refers to ETL as "heavy-iron integration."


Pfizer's alliance with Composite Software's solution and its rejection of ETL goes back a few years, by the way. Still, it's interesting to read how the company is applying virtualization to the problems of data integration.

Meanwhile, for those of you more concerned with data warehouses, the article looks at new options for managing and automating data processes, including what features BI vendors are adding to support better information management.


If you're still not convinced that information management is crucial to better BI, you might want to check out this Information Management report on a study from the University of Texas with the Indian School of Business. The study-sponsored by Sybase-queried more than 150 Fortune 1000 firms and found that if these companies improved how they use existing information assets, they could save hundreds of millions of dollars each year. And yes, integrating data-or at least, pooling your data resources-is part of that, according to Anitesh Barua, lead researcher and distinguished professor at UT-Austin:

Rather than just pumping more money into the top end of a data system to find efficiencies, sometimes combining existing information can find big rewards later on, Barua says. He gave the example of one corporation from the study that compiled a global list of parts providers for their operations. That way, when something breaks down or is needed, the company can quickly and easily find the closest and cheapest spot for that part, saving time and money.

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