Data management utilities could cut the cost of data, ease the burden of in-house data management and provide a solution that will deliver data not only to meet the requirements of today’s regulations, but also those of emerging regulations.
Presenting a keynote speech at this week’s A-Team Group Data Management Summit – which for the first time was linked to the company’s Intelligent Trading Technology Summit – in New York, Joseph Turso, vice president at SmartStream, argued the case for data utilities and detailed the Central Data Utility developed and run by SmartStream in conjunction with Euroclear.
Turso set the scene with a quick review of the past 20 years of data management and their sorry end of data stuck in siloed databases that are difficult to integrate and expensive to sustain. He said: “After the financial crisis, the mandate changed. Data management had to be improved and more ETL tools were used, but they didn’t get us where we needed to go. With $125 billion spent on data every year, the drivers behind a new approach to data management include timely trading decisions, best execution and compliance with regulatory requirements. The problem is that the wish list has to be achieved at reduced cost.”
Offering a solution to the problem, Turso suggested data utilities can come into play in data processing and data management operations. Users don’t lose control of their data as they continue to control vendor relationships and contracts; data from different vendors is not comingled but mapped to a common, consolidated data model; and efficiencies are provided by the utility fixing any data issues once for the benefit of all users.
Countering perceptions that utilities curtail the flexibility of data distribution, Turso touched again on user control and the ability to customise data distribution to different platforms, avoiding the complexity of doing this in-house and delivering significant cost savings.
Turning to the structure of the SmartStream Central Data Utility, Turso described a bottom layer that centrally manages data cleansing and mapping for all clients, a variable layer that can be used by clients on an individual basis to define the data integration and cross-referencing they want, and a top layer that can be customised by clients for data distribution.
He concluded: “The utility normalises, cleanses, maps and distributes data, providing clients with costs savings, improved time to market and, in turn, improved business performance.”