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Dreamforce 2019: Analytics First Impressions

Dreamforce 2019 was a whirlwind of activity and announcements and the analytics space was no exception. While more details will be shared in the coming weeks and months on new features and functions, I thought it would be helpful to share some first impressions.

  • The Einstein team is making a major investment in industry-specific solutions.
    The analytics keynote included demos of the healthcare, manufacturing, financial services, and consumer goods Einstein solutions, all of which are currently available except for consumer goods. Unlike some of the business function focused apps that were previously available (sales, marketing, field service, etc) these new apps are vertical specific, and include prebuilt models and include predictions. These apps could potentially be high-value accelerators for the industries they serve.
  • Einstein has been greatly improved as a data platform.
    We saw a ton of new features related to the Einstein data platform, which reinforces Salesforce’s intent to lead in this space. Some impressive new features include:
    • Data catalog and data lineage visualization tools built into Einstein. (Interestingly, Tableau announced similar functionality at their conference Keynote a few weeks ago.)
    • Additional connectors including Snowflake and Mulesoft and new functionality to direct query non-Einstein datastores such as snowflake, with the promise of more direct query capabilities to come.
    • Intelligent data prep that includes a significantly improved interface, AI-based join suggestions, “Missing Value” suggestions, and built-in sentiment analysis on text fields – All available inside the data prep interface.
    • Data limits raised from 1 billion rows to 10 billion for EA Plus.
  • Ask Einstein – Natural Language Query may deliver on the promise of democratization of analytics.
    The Einstein team has greatly improved the natural language query capabilities of Einstein, including a more intuitive interface that allows you to give feedback to an AI-powered Neural Net engine. This means the AI can learn about how you query your data and will get better the more you use it! We’ve been talking about the democratization of analytics for a long time in the BI space, and I feel advancements in natural language processing and data cataloging may be the path to finally delivering on that promise.
  • Einstein Predictions API improvements allow the use of the Einstein Discovery Engine from other apps.
    Improvements to the Einstein Discovery API will allow for insights and predictions from discovery to be surfaced in other applications, making it easier to surface insights where users work, which is a cornerstone of the intelligent experience.


One theme we saw repeatedly at Dreamforce was Salesforce’s focus on enabling the intelligent experience. Specifically, providing analytics and AI insights within the flow of business, in the context of where decisions are being made, and enabling a seamless flow from insight to action.

It’s going to be an exciting year in the analytics space in 2020. The rate of innovation coming from Salesforce in analytics and AI/ML is unsurpassed and every release brings significant improvements to the platform. Many of the features showcased at Dreamforce are already available or will be available in the next few releases. We’ll keep you updated on new developments as they occur!