Accelerate your Snowflake solution with good quality data, so it can work its magic.
So you have bought Snowflake, an excellent choice. You are now cloud native, you have endless scale possibilities and now you want to become more data driven. Stop. You have a problem. The level of readiness Snowflake expects of your data does not exist in your organization. Sure, it works well on Wikipedia data and perfectly prepared datasets, but your data does not look like that.
Snowflake themselves say on their website, "If you want clean data, use Spark." But don't worry, there's a solution. CluedIn's main focus is on preparing data so that platforms like Snowflake can provide their magic.
So why can't you use just any cleaning application to do this? You can, but when you go to operationalize it, it will fail. CluedIn is a platform that connects to source systems and facilitates the full flow of data to Snowflake, but gives tools to stewards so when they clean, they can easily send it off to Snowflake. Most importantly, cleaning is not a once-off thing. It is a continuous stream of data that flows through your business and you want to systematise it.