Snowflake

My company adopted Snowflake as our first cloud-based data warehouse. It is being used as a central repository for all company data from each business unit for the purposes of business intelligence.

Snowflake is being used on top of our Azure data warehouse. It solves our issue of queries running at the same time and has drastically improved our server performance. All of our reports connect to Snowflake and they all run very fast. It is currently being used across the entire company.

We use Snowflake in our organization as both our data lake & data warehouse. Instead of ETLing from source to a data lake to then architect our data, we have made internal schemas that we can ETL the data into. We then use an on-prem SQL Server to execute our SSIS packages, which support a DSN connection.

So far it's been very easy and very successful.

The analytics and reporting team uses Snowflake as their primary Business Intelligence (BI) tool. Combined with several reporting and charting tools, Snowflake provides insight across all departments in the organisation. Snowflake helps provide the business with crucial analytical understanding of performance which, in turn, influences business strategy for the entire organisation.

Our company has grown organically and by acquisition, and as a result we have a series of disparate software products with around 800 databases across different clouds and different databases - SQL Server, MySQL, Postgres, AWS, Azure, etc.

My challenge was to implement an awesome and consistent reporting suite that allowed customers full access to all of their data across all of our products. While the software development team is working on integrating all these disparate products, that's a significant multi-year challenge.

Implementing a data lake in Snowflake greatly empowered my team to make tremendous reporting, blending data from many sources, without adding any load to the transactional databases. What's more, Snowflake has a vast array of excellent built-in features such as row-level security, data masking, secure sharing, and other items that allowed us to push security right down to the database level so we secure data no matter how customers access it, without relying on complex where clauses, etc., in queries.

The Snowflake model of separating compute from storage and allowing us to have differing workloads for differing usage scenarios is also very helpful.