It’s one thing to talk about orchestrating and automating your organization’s data operations. It is quite another to gain the confidence that comes with having a unified view of your data. This just-in-time view of the truth simultaneously reduces data privacy risk and enables your business to pursue data-driven goals.
We are excited to announce the integration of Tecton’s enterprise feature store and Feast, the popular open source feature store, with Snowflake. The integration, available in preview to all Snowflake customers on AWS, will enable data teams to securely and reliably store, process, and manage the complete lifecycle of machine learning (ML) features for production in Snowflake. Tecton allows data teams to define features as code using Python and SQL.
Please join us on March 24 for Future of Data meetup where we do a deep dive into Iceberg with CDP
A data pipeline is a series of actions that combine data from multiple sources for analysis or visualization.
The first step in most analytical workloads is to ingest the data that you need for your analysis into your data warehouse. For geospatial analysis involving point, line, or polygon data, ingesting data can be complex because geospatial data comes in myriad data formats. Two of the most popular geospatial formats are GeoJSON and GeoJSON-NL (newline-delimited geoJSON).