Beyond Golden Copy?
March 5, 2010
Interesting reading in a survey put together by Lepus and Thomson Reuters and publicised on Finextra this week. Summary findings:
- Data management budgets are increasing, with 77% of firms intending to increase spend on data quality and consistency and 32% saying spend would increase significantly.
- Tearing down data silos is a key initiative, 70% of firms are looking to revise data management solutions as a result of the crisis, and 31% of firms cited data quality and consistency as the most important driver.
- Data management for risk is the top concern, with 87.25% of firms looking to integrate data repositories in risk, and 62.5% saying that they were close/very close.
This seems to be consistent with another article on Finextra this week, with Deloitte predicting a much greater spend on risk management projects. Putting the marketing aspects aside for a moment, I don't think it is abundantly clear from the actual content of the Lepus survey as to why the title includes the phrase "…Beyond Golden Copy" other than the type of data management they refer to seems to have more emphasis on global/firm-wide data integration than your traditional EDM golden copy data warehouse approach.
It is also interesting to hear so much about consistent data across the entire enterprise (driven by risk and regulation) which seems to echo the "big EDM" projects of old that did prove that successful, and to some degree is at odds with what the likes of Golden Source and Asset Control are currently saying about choosing smaller projects to bite off on rather than the enterprise approach. I would suggest however that there is no issue in having smaller projects in mind so long as they are compatible with the overall goal.
The integration and consistentency of data across front, middle and back office was also interesting, and in particular the front office integration echos some of the things I have been saying about the need for analytics management and the management of front office data as part of the data management process, not something to be ignored in the hope it sorts itself out.