The future of the operational data warehouse
In the last five years, we’ve seen the cloud data warehouse, exemplified by Snowflake and BigQuery, become the dominant tool for large and small businesses that need to combine and analyze data. The initial use cases are usually classic decision support. What is my revenue? How many customers do I have? How are these metrics changing and why?But the iron law of databases is data attracts workloads. When you have all of your data in one place, clever people in your team will come up with unexpected uses for it. The cloud data warehouse enables these new use cases with its elasticity. As you discover new things you’d like to do with data, you can add new compute capacity, effectively without limit.To read this article in full, please click here
In the last five years, we’ve seen the cloud data warehouse, exemplified by Snowflake and BigQuery, become the dominant tool for large and small businesses that need to combine and analyze data. The initial use cases are usually classic decision support. What is my revenue? How many customers do I have? How are these metrics changing and why?
But the iron law of databases is data attracts workloads. When you have all of your data in one place, clever people in your team will come up with unexpected uses for it. The cloud data warehouse enables these new use cases with its elasticity. As you discover new things you’d like to do with data, you can add new compute capacity, effectively without limit.