Why organizations need a solid data governance strategy
When I started working as a database administrator in 1983, it was all about centralization in technology. Data was safely on the corporate mainframe, and just those programmers who had the skills to navigate prerelational databases could access it. Nearly four decades later, it’s all about data democratization and the need for a strong data governance strategy.
Back in the day, business analysts had to go cap in hand to the IT department because they didn’t know how to navigate an Information Management System database and wouldn’t have been granted access even if they could. The IT department printed off monthly reports and distributed them, like Moses descending from the mountain with tablets of stone.
With the advent of the personal computer, the balance of power shifted radically. Suddenly, businesspeople had access to spreadsheets and could create their own calculations and analyses, even if the data was still mostly out of reach. Then came client/server computing and a rush to decentralize data, bringing giddying new possibilities but also confusion as different versions of data were used by different departments. And analysts fought over whose version was correct. Analytics could now be done by business analysts, but without agreement on the legitimacy of the data sources, chaos ensued.
IT responded with the data warehouse, which would gather up data in disconnected transaction systems for the sole purpose of analytics. Clever reporting tools appeared that made it easier to manipulate, join and summarize raw tables of transactions and maybe even download them to spreadsheets. Sure, the original data was still stored in different applications and formats, but with enough effort, the data warehouse could be coaxed into making sense of all this, providing dimensions like customer, product, asset and location. However, to actually produce consistent lists of customers and products, the inconsistencies of the underlying systems had to be resolved.
Master data management (MDM) was born and, alongside it, the need for a data governance strategy. Business users were encouraged or cajoled into deciding which classifications of customers and products were “golden records” to be held aloft across the enterprise and which were to be cast into the wilderness of department-specific, local terminology.
This was a frequently acrimonious process, with different departments arguing over which was the best way to classify data. Some company cultures suit this approach more than others.
Highly centralized companies are used to having structure dictated from on high, but decentralized ones rail against this and struggle to keep within data governance structures. Analysts in such companies think of themselves as freedom fighters, whereas those in the central office regard them as data terrorists.
The corporate data warehouse has been stretched beyond its natural limits. Data now comes from such a variety of sources that traditional approaches are breaking down. It seems clear that, at least in a lot of companies, the freedom fighters are now in the ascendant. A sign of this is the growing market for data preparation tools.
