Metadata governance is the systematic approach to managing metadata, or data about data, to ensure it is accurate, consistently formatted, and securely stored. The main goal of metadata governance is to improve data quality, ensure data privacy, and streamline metadata management. As metadata provides the necessary details about data, such as when it was created, by whom, and its content or purpose, it becomes easier for employees to find, understand, and trust the data they use.

Building a data-driven company starts with having a data analytics strategy. An effective data analytics strategy relies on three key components: people, processes, and data infrastructure. This ensures that your analytics strategy is actionable and accessible to everyone who needs it to make decisions. In this post, we’re sharing 12 tips to help you develop an effective data analytics strategy.

Imagine you want to leave a note for someone. You write the message on a piece of paper and put it in an envelope. The envelope around your note keeps the message contained and separate from other things. It's the same idea with terminating string literals. A string literal is like the note you wrote, while terminating it is like sealing the envelope. Here's an example: The phrase "Hello, world!" is the string literal, while the double quotation marks tell the computer where the string begins and ends.

One of the key processes in healthcare data management is integrating data from many patient information sources into a centralized repository. This data comes from various sources, ranging from electronic health records (EHRs) and diagnostic reports to patient feedback and insurance details.

Hakkoda’s 2024 State of Data report found misalignment between data leaders on AI readiness.