Mparticle Announces Warehouse Sync, the Convenience of Reverse-Etl With the Power of a Real-Time Cdp

Combining data warehouse ingestion with robust data quality protections and rich predictions provides data teams with unmatched activation capabilities.

mParticle, a Customer Data Platform, announced that it is expanding its catalog of data sources to include direct ingestion from data warehouses, beginning with Snowflake, and followed by support for Google BigQuery, Amazon RedShift, and Microsoft Azure. Warehouse Sync delivers cost and time savings for data teams that want to maximize their existing data infrastructure and solve the complexities of utilizing customer data for personalization.

With Warehouse Sync, mParticle enables traditional reverse-ETL flows while also providing a complete data infrastructure to support customers as their business grows. mParticle’s Customer Data Platform goes beyond conventional reverse-ETL with real-time, many-to-many data streams, native identity resolution, integrated privacy and compliance controls, AI-powered predictions, and the ability to build personalized marketing journeys, all from a single, secure platform.

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Warehouse Sync unlocks valuable customer data in data warehouses, making it immediately available across 300+ real-time marketing and customer engagement APIs. With mParticle, data teams can:

• Accelerate all customer data connections, regardless of source, by easily syncing high-quality data to any of mParticle’s 300+ real-time API destinations in a highly-scalable, many-to-many construct.
• Stitch together the entire customer journey into persistent, stable, and real-time customer 360° profiles to navigate a cookieless future.
• Maximize customer lifetime value through rich machine learning models to create better recommendations, high-fidelity predictions, and better uplift models.

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“The cloud data warehouse is an important source of rich customer data which teams need to incorporate into their data strategies,” said Michael Katz, CEO and co-founder of mParticle. “The customer data stack and the data engineering stack are beginning to converge, which we believe will unlock new opportunities for teams of all sizes, and we’re excited to expand our offering with this latest feature.”

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