In the past decades, organizations have come to realize the importance of leveraging data efficiently. We are witnessing a "data race", in which businesses seek to hire the best data talents. The result? businesses are now equipped with data engineers, data scientists, and data analysts, mastering cutting-edge tools to produce meaningful data analysis.
These talented data people are expected to conduct high-quality and valuable data analysis, but the story often unfolds differently. They encounter a great deal of frustration when they realize they spent most of their time dealing with boring questions:
That is, data people are spending more time on metadata management than on meaningful value-generating data analytics work. Thankfully, the enterprise data catalog is a tool that can help with all these questions, allowing data people to focus on the core of their work. This is why data catalogs tools have flourished in the past 10 years, and there are now so many tools to choose from that businesses have a hard time making up their minds. Today, we take on the difficult task of untangling the vibrant data catalog ecosystem.
“A data catalog creates and maintains an inventory of data assets through the discovery, description, and organization of distributed datasets. The data catalog provides context to enable data stewards, data/business analysts, data engineers, data scientists and other data consumers to find and understand relevant datasets for the purpose of extracting business value.”.