Each week millions of people watch the TV series CSI: Crime Scene Investigation or one of its offspring, CSI: NY and CSI: Miami. The premise of each show is that a group of crime scene investigators use their high-tech gadgets to solve even the most mysterious of murder cases. Using cool tools they can uncover obscure evidence that reveals the true story. Technology plays a starring role in these shows -- it always saves the day. And that's a theme in many American TV shows, movies and books, which is appealing to those of us who work in the IT industry.
The problem with these shows is that they set a false expectation about technology. If cool tools can solve murder mysteries on TV, why can't they solve murder mysteries in real life? Can't the police just call in their CSI unit to figure things out?
It's a similar phenomenon in the IT marketplace, where companies are constantly inundated with new products, product upgrades and acronyms. They're told that the latest and greatest technology is going to save the day by solving data problems that have plagued them for decades. Corporate performance management (CPM), master data management (MDM) and customer data integration (CDI) are the latest to join the fray, promising an immediate single version of the truth simply through the use of the right tools. Mystery solved!
Vendor pitches can be very convincing on PowerPoint slides and in marketing brochures -- especially when customer references and proofs-of-concept reinforce
In reality the single version of the truth takes hard work -- very hard work. If it was only a technology issue many companies would have solved it by now. After all, they've spent a lot of money implementing the latest and greatest data integration tools and what do they have? More data silos than ever before.
Yes, data integration tools can help, but the issues are much deeper and more profound than that. For true data integration it is essential to know what the data represents, when it was captured, how it was transformed and how it was manipulated in the report or analysis performed by the business user. Companies need to ensure data consistency, integrity and quality, and they should be able to track the data from its creation to its consumption.
Data integration tools are only part of the strategy. The other part involves talking to business people to understand and define the data and its usage; creating an architecture to ensure data integration with integrity, consistency and quality; effectively managing resources; training users; and educating both the business groups and the IT organization on what it all means. These steps will help when it comes to making the business case to justify the necessity of data integration.
It's difficult work, but consider some of the outcomes and advantages:
- Easing Sarbanes-Oxley compliance.
- Providing financial transparency.
- Improving interactions with suppliers and partners.
- Improving customer intelligence and customer relationships.
Remember, technology is not a solution -- it's an enabler. Don't ignore the data integration fundamentals. Attractive dashboards and "slicing and dicing" cubes are terrific, but without the right data, your system is doomed. Sure, it's impressive to load millions of rows from dozens of source systems in real time. But if you've scrimped on the architecture and the data's consistency, integrity and quality are questionable, all you've got is a fast garbage truck.
More information on data integration tools
- Data integration tools: Gartner Magic Quadrant names top vendors
- Data integration software vs. hand coding: Balancing costs and benefits
About the author
Rick Sherman is the founder of Athena IT Solutions, a Boston-based consulting firm that provides data warehouse and business intelligence consulting, training and vendor services. In addition to over 20 years in the business, Sherman is also a published author of more than 50 articles, an industry speaker, a DM Review World Class Solution Awards judge and a data management expert at SearchDataManagement.com. Sherman can be found blogging at The Data Doghouse and can be reached at firstname.lastname@example.org.
This was first published in January 2006
This was first published in January 2006