Increasing amounts of data require holistic management

Effective governance also enables the company to implement and manage internal policies and standards related to data security and use. This not only supports the company’s response to external compliance directives, but also standardizes data for use across the company. Standardized data provides the “single source of truth” needed to make critical business decisions, as well as the data quality and reliability teams need to do their jobs.

Data management challenges

On the surface, implementing data governance may seem obvious and simple, but the act of managing data across a company’s teams and products introduces levels of complexity that many companies either half-heartedly attempt to address or avoid altogether.

Introducing processes, policies and management protections requires new thinking about people, processes and technology. “They don’t convince someone not to do management,” says Syed. “That’s all the work it takes to get the administration in place.”

For many, the approach to data governance is to establish policies that are overseen by individual business sectors, making implementation even more difficult. “Think about all the different teams that do this in a large organization,” explains Syed. “They all have to do that dependency checking, and each team also does separate development work to meet those requirements, which is a lot of duplicated effort.”

A siled data management initiative that requires each team to track its own data dependencies takes time and effort away from other work as well. “It becomes cumbersome to innovate because at every step of the innovation you have to check for dependencies on your management policies,” says Syed.

Siled approaches also introduce the possibility of error and make it difficult to ensure that all management policies are followed consistently, in all cases. These barriers can result in a lack of buy-in from employees and stakeholders, reducing any realized benefits from data management.

A solution for federal management

In many companies, data is viewed as an IT asset, and thus an IT liability. While this may have been true in the past, the volume and velocity of data today, and the innovative ways companies are using their data, means that data is a responsibility – and a driving force – for all business units.

To build an effective data management program that will serve all areas of the business, it is best to centralize the framework to reduce errors and reduce duplication of effort. “For federated teams to be successful in implementing data governance and governance policies, you can’t just set a policy and let each team build the technology to implement it,” says Syed. A centralized approach is less complicated to track, facilitates consistency and accuracy of data, and is easier to make transparent, all of which helps with stakeholder buy-in. “If you have a centrally managed data platform, a centrally managed data ingest pipeline and a centrally managed data policy, then you only make changes to [the data] in one place,” explains Syed. This ensures that data remains compliant, secure and consistent wherever it is used.

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