Reopening the data mart
Master data management starts with a few small steps -- and an updated version of the data mart.
Follow @MobileGalenThe growing acceptance of the SOA approach to enterprise applications has reopened an old IT wound: the sorry state of data in most enterprises. In the 1990s, the data warehouse and the enterprise repository were trumpeted as the solution for getting the entire enterprise on the same page, but these systems quickly became unwieldy dumping grounds, much like the cavernous Indiana Jones warehouse in which the Ark of the Covenant was stored to keep it safely out of reach.
Today, a new approach — often labeled master data management — is emerging, one that takes a modular, orchestration-based approach to rationalizing data strewn across the enterprise in various formats and repositories.
Similar to a complete SOA deployment, however, a complete master data management effort is a huge undertaking, one that takes years and consumes a lot of resources with marginal interim benefit. “You just can’t shut down the enterprise and do this major business re-engineering,” says Don DePalma, chief researcher at IT consultancy Common Sense Advisory. So what is IT to do?
Increasingly, companies are revisiting a mid-1990s approach — the data mart, now often called a system of record — that fell by the wayside during the data warehouse and repository crazes. Creating a system of record is a good way to start down the path of an enterprisewide master data management system. It helps IT get a handle on key data, making it more available to enterprise users and providing a demonstrable ROI in the process.
Data warehouses and enterprise repositories shunted aside the data mart of yore. In most cases, the data mart couldn’t do the job of being a timely data container, DePalma says. “It was a snapshot, so it was outdated,” he notes. But data marts can now be near-real-time repositories, thanks to a variety of advances in the intervening decade. These include standardization of data exchange around ODBC, JDBC, and SQL 99; increased use of Web interfaces for transmittal of real-time information; and better data management tools from vendors such as Business Objects and Informatica, he says.
The result is the improved data mart, or system of record, built using software from companies such as Business Objects, IBM, Informatica, or Oracle. “This is the next step to getting cleansed, standard information of the key information that is important,” DePalma says.
From point solution to architecture
Nationwide Insurance started a data-rationalization effort two years ago, after the CFO decided that having multiple ledger systems — inherited through multiple acquisitions — was interfering with the company’s ability to see the complete financial picture.
Although the insurer could have considered a broad data architecture effort, it had a culture of departmental independence, so it made more sense to solve a specific need than to convince the organization at large to collaborate for an unclear benefit, says Vikas Gopal, director of enterprise financial applications at Nationwide. “On the financial side, there was a realization of the pain that led to the recognition of the need for consistent data translation, which in turn led to a need for data governance,” he says.
With the CFO’s mandate in hand, IT and business analysts dived into all 240 ledger-related systems and the data stored in each and worked with executive management to decide what the enterprisewide ledger system needed.









