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Sharing data

The Data Sharing feature in CDP leverages Snowflake to provide fast and direct access to customer data at scale.

To create meaningful and enriched user experience, organizations need more and more data. However, with the manifold growth of data, organizations find it difficult to transform the data to tangible insights or actions.

The Data Sharing feature allows integration of data from CDP to organizational processes. This feature strives to provide access to clean, processed, and current data, thereby empowering you to make data-driven decisions.

Based on Acquia’s strategic partnership with Snowflake, this feature provides reporting and full SQL access to processed, record-level data in CDP with fast query performance through Snowflake. Therefore, marketing, IT, and data science teams can take advantage of large amount of omnichannel customer data. This data is further enhanced with CDP’s online-offline identity resolution and predictive analytics.

With this feature, data is instantly shared from CDP’s Snowflake account (data provider) to your Snowflake account (data consumer). With secure data sharing, data does not move. This feature eliminates cost and delays associated with legacy data sharing methods. The shared data is immediately available for use in your Snowflake account without any transformation, data movement, loading, or reconstruction.

Use cases

  • Use your own business intelligence and analytics platform: Your team might already be using a BI or analytics tool. While the Metrics feature in CDP is built on an industry-leading analytics platform, Acquia does not expect you to retire your existing analytics tools. With this feature, you get full JDBC and ODBC connectivity to CDP’s shared database along with a host of other interfaces in Snowflake’s ecosystem. For more information, see documentation
  • Analyze CDP’s data with external non-CDP data: CDP might not have all operational data such as financial forecasts, supply chain, and inventory management. Integrating transactional data from a CDP to operational data leads to insightful results. This is much easier when the entire data is available in the same data warehouse. With this feature, you can join multiple databases, including CDP’s shared database, in the same query or report.
  • Build on top of CDP’s data: CDP allows you to build your own machine learning models. The success of any ML project depends on your access to readily-available clean data. With this feature, you get access to enriched data in your Snowflake account. You do not need to depend on your IT team to manage a complex ETL process. Your team can do experiments and build models efficiently leveraging CDP’s data. You can even feed the results of your ML models to CDP for usage in Actions and 360 Profiles.