Data engineers must collect, transform, and deliver data to different lines of business while keeping up with the latest technology innovations to stay ahead of business demands. However, traditional legacy architectures create challenges every step of the way. Efficient data pipelines can be the difference between an architecture that delivers real value to the business or one that becomes a burden.
In this white paper, you’ll learn how Snowflake can maximize data engineering processes by:
- Handling structured, semi-structured, and unstructured data types easily
- Ingesting data in bulk or near real-time
- Building data pipelines with language of your choice, SQL or Scala
- Extending what your pipelines can do with extensibility features such as Java UDFs and External Functions
- Simplifying data pipelines and architecture with near-zero maintenance
