9 Tips For Data Governance Success- Valutrics

 

Data governance is essential for organizations that rely on consistent, quality data. But embarking on a new data governance project can be a daunting task. Here’s a look at some of the key elements recommended by experts in the field

 

Organizations looking to establish a data governance program are taking on a big project that will become a framework for how data is treated within the organization forever. Such a monumental task must be approached with a real plan and strategy.

Although the task may be daunting, such a data governance framework can be an essential piece of helping an organization work better and scale to meet new business challenges.

The Data Governance Institute defines data governance as “a system of decision rights and accountabilities for information-related processes, executed according to agreed-upon models which describe who can take what actions with what information, and when, under what circumstances, using what methods.”

Without this framework, organizations may end up with bad data, bad data security, and data models that fork and produce differing results depending on the business unit that creates them. Data governance ensures that everyone in the business is on the same page when it comes to data.

Everyone is looking at the same numbers. Everyone is speaking the same language. Decisions are made based on that information. Good data governance protects brands, improves decision making, and mitigates compliance risks. The goal is to get your company to understand data as a strategic asset.

But if you are starting from scratch and have no data governance program in place, where do you begin? What do you need to make sure that your program is a success? Gartner Research VP Svetlana Sicular describes different levels of data governance maturity in a webinar about starting a data governance program.

She defines level 1 organizations — those without a data governance program — as organizations that engage in sporadic efforts to repair data. These organizations have no dedicated or recognized data personnel.

At the other end of the spectrum, level 5 organizations are optimized. These organizations have a dedicated formal team with a balanced mix of data management skills, knowledge, experience, and abilities, she said.