For the past 30 years, the primary data source for business intelligence (BI) and data visualization tools has generally been either a data warehouse or a data mart. But as enterprises today struggle to cope with the growing complexity, scale, and speed of data, it’s becoming clear that the data tools of 30 years ago weren’t designed to handle the enterprise data management challenges of today - especially with the growing variety and amounts of data that enterprises are generating.

If you use a data lake, chances are you need a way to keep your data searchable for business users. When combined with the analytics capabilities of a cloud data platform, a data catalog can solve some of the common pain points around “data swamps,” where users fail to gain any meaningful insights from their data. Some of a business’s most valuable assets lie within its data.

Any data-driven organization will tell you that the holy grail is faster time to insights. But the unfortunate truth is that business users often have to wait days — even weeks or months — to analyze the data they need. Behind the scenes, data engineering teams put a lot of work into joining disparate datasets, creating pipelines, and delivering a final data product back to their stakeholders for analysis.