IHS Markit, is an American-British Services Provider that uses data for business intelligence and empowers its customers to make well-informed decisions with confidence. They have 50,000 customers in over 140 countries, 80% of which are of the Fortune Global 500.
They needed to migrate terabytes of data as quickly as possible into Snowflake, without compromising quality, so their business intelligence users could access it.
How they made it possible – in only 5 hours
Having previously used Denodo, they consolidated multiple databases in preparation for the migration. The team then used FME to migrate 1.5 billion rows from Denodo into Snowflake and chose FME Flow deployed on Kubernetes for the project. The team used FME to split the data and distribute the processing across multiple engines to take advantage of parallel processing.
Using FME Flow’s CPU usage pricing (previous called “Dynamic Engines”) provided IHS Markit with the ability to spin up multiple engines to enable parallel processing and allowed them to keep costs low by only paying for the number of processing hours used. IHS Markit completed its migration to Snowflake in only 5 hours.
Snowflake-ready
Using the pre-built reader and writer from FME, users were able to load virtually any data, including business, structured, and unstructured, into Snowflake in just a few clicks.
By consolidating data into one central cloud data warehouse, the team can provide its business intelligence users with a single source of truth to pull data from.
