The data lake, a data-centered architecture featuring a repository capable of storing vast quantities of data in various formats, has emerged among IT organizations as a solution to the challenges with existing enterprise data architectures. In the data lake, data itself is no longer restrained by initial schema decisions and can be exploited more freely by the enterprise.
However, the data lake is not without its own challenges. Without adequate data governance, data lakes can rapidly become data swamps, polluted with poor-quality data. Data lake end users, especially business users, may not be able to understand the data they need even if they can find it. Users also may not be able to tell where the data came from or what it looks like, leading to lack of trust in the data. Finally, security and compliance risks can jeopardize the data lake if the data is ingested without any oversight.
So how can organizations tackle these roadblocks and get the most value out of their data lakes? The answer lies in how the data in the lake is managed. Here at Knowledgent, we believe that data lakes should only be populated with data that has been transformed into Managed Information Objects (MIOs). MIOs are data assets that have been ingested into the data lake and meet specific usability criteria.
What are the characteristics that separate MIOs from data assets? Check out this month’s infographic below to learn more:
Do your data assets meet the criteria for MIOs? Share your thoughts in the comments!