No, not that kind of genie. Salesforce Genie is a real-time hyperscale data platform that enables the delivery of personalized and individualized experiences across sales, marketing, service and commerce. Genie, which runs on Hyperforce brings hyperscale, real-time data – optimized for engagement, optimized for analytics, optimized for AI — deeply connected into the Salesforce platform. But wait, why is this different and/or better than the old way of integrating data through the Force.com platform that’s been around since ~2008? Genie is a completely different architectural and procedural approach to ingesting, harmonizing, sharing and automating data. The old platform approach to data integration was based on transactional data stored in a traditional relational database. Genie uses a data lake to store the data. this opens up several important capabilities. The data lake is based on the lakehouse architecture and has the ability to “learn” Salesforce metadata model, which is the method that all services in Salesforce interact.

First, what is data lakehouse architecture? A lakehouse is a hybrid approach that combines a data lake with the data structures and management capabilities that existed in the older approach to data storage, data warehouses. This hybrid architecture has many advantages and includes:

1. Open standards of data storage formats that enable other data stores like warehouses and lakes, services like machine learning (ML) to directly exchange data in both directions through open storage formats without copying data

2. Data diversity by supporting both structured and unstructured data types

3. Robust governance with compliance built-in, data lineage, consent mapped to models means system can maintain data integrity

4. Direct data access for BI tools and support for data science tools, artificial intelligence (AI) / ML

5. Real-time data streaming

Because of this modern approach to the data lake, Genie has the ability to integrate to any outside services and data repositories like the announced Snowflake integration. It also opens up a myriad of automation capabilities in Salesforce Einstein AI and Salesforce Flow. The architecture opens up the power of real-time and/or near real-time data streaming, which creates a much more complete and usable customer data graph.

If this all sounds a bit like a customer data platform (CDP) to you, you wouldn’t be wrong. It takes the CDP paradigm and extends it beyond marketing into all parts of the CX suite from sales to service. The real-time and near real-time streaming capabilities across the entire CRM / CX suite of applications enables a broad set of automation capabilities and process workflows. This new data foundation for the business creates the ability to have a complete and actionable customer data graph that supports a universal CX strategy.