Many organizations today recognize the strategic importance of data. You’ve probably heard the popular catch phrase “Data as an asset” a few times by now. But why, in the era of the cloud, is protecting this precious asset and implementing a data governance framework more important than ever?
When a company purchases an asset such as a truck, plane or building, they put people and processes in place to ensure that it is well maintained and operates efficiently. It is often inspected and repaired. This is how data should be managed as well.
With the emergence of cloud in the business intelligence space it is now possible to access more data than ever before. This presents a new set of challenges that must be addressed while balancing the ever-increasing need for rapid insights. In the traditional data management landscape, it was possible to control how data was captured because you had control of the sources. The data generally applied to your business because it was captured by systems that run your business and you understood the context in which it was captured. With the expanding world of data, it is no longer possible to always know how data was captured and in what context because these systems are not under our control.
Data governance is a set of processes for formally managing data assets. It refers to how your data should be used, monitored, inspected and invested in order to maintain its integrity. Data governance does not mean that we have to follow a traditional approach to data management to bring it into the current data landscape. The promise of new technologies such as Hadoop, means that we can quickly gain insight from new data and apply it to our business processes. It is important to explore new data in a rapid manner to gain a competitive advantage as quickly as possible. The role of data governance is to facilitate the sharing of insights from new data with the broader organization by making it relevant and trustable. Data governance provides the framework to facilitate an “insights-first” approach to data and not impede the ability to gain insights quickly.
The key steps for an insights first approach are:
1. Understand what you are collecting or need to collect
2. Explore the data to understand what insights can be gained
3. Align the data to your organization
4. Make the new insights available to a broader audience to gain tangible benefits from the new insights
5. Manage the data over time to ensure it remains relevant and high quality over time.
Data governance provides the combination of roles and responsibilities to manage this process along with the tools to help manage your data. Key roles include data scientists to understand the data, stewards to define and monitor new data and technology specialists to supply enabling technologies.
Investing wisely in a data governance framework will allow you to get the most out of your data by treating it as an asset.
Be on the look-out for my next blog where I will discuss a framework for rolling out an initial data governance program.
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