If you’re responsible for data governance, you’re likely all too familiar with the task of data lake management, as organizations are rapidly transitioning solutions that make your job even more important and complex.
Big data solutions are opening up the potential to create insights and business outcomes that were previously impossible, but big data solutions that offer deep analytical capabilities over broader, richer data sets include both structured and unstructured data. As data variety, veracity and volume increases, big data tools and technologies have emerged as a clear winner for many organizations.
But what about managing all of that data? At the intersection of governance and big data are daunting challenges, often threatening to turn that data lake into a “data swamp,” by inhibiting efficiency. One of those challenges is that the rigor of data governance is often at odds with the speed demands of big data.
To reconcile this conflict and others, understand the business needs, identify what meets those needs and align new technologies to address governance concerns. Sounds simple, right? Ahead, four keys to make data lake management easier.
You’ve probably realized as the scope of data increases, so does the time required to manage the data, placing a huge burden on the data steward. At the same time, big data solutions focus on analytics and data science, forcing governance process to balance rigorously certifying data and granting access to unfiltered data.
To address these challenges, the duties of data stewardship need to be more efficient, and tools are available to assist:
Collibra® centralizes data stewardship activities, workflow management and the business glossary.
Navigator® offers data management and enforcement where policies are easily set, monitored and enforced.
Apache Knox™ offers a single point of authentication and access.
These tools dramatically reduce the amount of the data steward’s manual labor.
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