RESEARCH & RESOURCES

Data Governance: Bridging the Gap Between Business and IT

By Daniel Teachey, Senior Director of Marketing, DataFlux

Businesses are discovering that their success is increasingly tied to the quality and reliability of their information. As companies collect more and more information about their customers, products, suppliers, inventory, and finances, it becomes more difficult to accurately maintain that information in a usable, logical framework.

The data management challenges facing today’s businesses stem from the way IT systems have evolved. Enterprise data is frequently held in disparate applications across multiple departments and geographies. The confusion caused by this disjointed network of applications leads to poor customer service, redundant marketing campaigns, inaccurate product shipments, and, ultimately, a higher cost of doing business. Add to that a sense of unrest and poor communication between departments about a “single version of the truth,” and you’re at a standstill.

Historically, when talking about data management, organizations focused on data integration and data quality. In this way, they generally focused on a particular application or line of business. When you start talking about things like data governance and master data management, they are by definition more broad-scoped within an organization.

With a broader perspective, however, it can be difficult to find the appropriate resources within the business hierarchy to support the project. There is often confusion about ownership of business elements that span multiple application environments and lines of business. In addition, a line-of-business owner may “own” an application, but the IT group has historically maintained the applications within the IT ecosystem.

Is data governance something that rests with business or IT? Proponents of IT data management argue that only technology-savvy overseers are capable of handling customer, product, and other data; only they have the knowledge and expertise to govern data around the clock.

This control, however, comes at a cost. IT executives often say they don’t have time to manage an entire company’s data. They also argue that they shouldn’t have to clean up the problems caused by ineffectual and poorly designed business processes.

Business executives are often eager to take control because data is essential to their day-to-day operations. Line-of-business staff members can become frustrated that another department is pulling the strings on how quickly data can be integrated, cleansed, and amalgamated to provide reporting and analysis.

However, the business side has a problem, too. Business users typically deal with information within a business silo, which can lead to a fragmented, confused view of the organization. Without IT’s help, they can’t effectively manage data resources in multiple business applications.

The answer is simple: both IT and business sides are responsible for ensuring data quality. But this answer lends another level of complexity. If IT and business haven’t been working together in the past, the best option is to bring in a data steward.

Data stewards can help a company make significant gains in managing data. Simply put, data stewards are people trained to exclusively handle the middle ground between IT and the business. They are technically savvy individuals who understand the corporate goals for the department, division, or enterprise.

The role of a data steward is to govern customer, product, supplier, and other types of data across various silos, including back-end and front-end systems across any department. They are a solution to the IT versus business debate because they’re neutral and can see both sides of the equation.

Even savvy data stewards know that the best technology in the world isn’t enough to ensure smooth data management. In the end, the integrity of a company’s data hinges on the integrity of its practices for collecting and managing data. Enabling an environment conducive to respect and cooperation can go a long way in effecting quality data that drives quality business decisions.


This article originally appeared in the issue of .

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