How To Make Data Integration Work
By Valerie Valentine, senior editor, Information Management

A recent report from TDWI offers a checklist of 10 best practices that shows it’s time to raise the bar on integration expectations, as the industry’s evolution has outpaced mindsets.

Philip Russom, senior manager for TDWI Research and author of the report, emphasizes that there's no silver bullet for "ideal" data integration. As the report explains, DI is a diverse discipline that makes use of a number of tools, depending on one's business and technological requirements.

DI has undergone an expansion over the last decade and has reached a critical mass of multiple techniques used in diverse applications and business contexts. Vendor products have achieved maturity; users have grown their DI teams to epic proportions; competency centers regularly staff DI work; and DI as a discipline has earned its autonomy from related practices like data warehousing and database administration. Given all this change, it’s not surprising that many DI specialists and the colleagues who depend on them, suffer misconceptions and out-of-date mindsets that need adjustment.

TDWI’s report explains a few things to understand about DI:

1. Data integration is a family of diverse, but related, techniques.
2. Data integration practices reach across both analytics and operations.
3. Data integration is an autonomous data management discipline.
4. Data integration is the repurposing of data, via transformation.
5. Data integration is a value-adding process.
6. Data integration is a green technology that makes data management more sustainable.
7. A data integration solution should have architecture.
8. A data integration solution should be the product of collaboration.
9. Data integration must be coordinated with other data management disciplines.
10. Data integration should be governed, but also contribute to governance.