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Einstein-Analytics-and-Discovery-Consultant Exam Topics

Data Layer: 24%

  • Given data sources, use Data Manager to extract and load the data into the Einstein Analytics application to create datasets.  Describe how the Salesforce platform features map to the Model-View-Controller (MVC) pattern.
  • Given business needs and consolidated data, implement refreshes, data sync (replication), and/or recipes to appropriately solve the basic business need. Identify the common scenarios for extending an application's capabilities using the AppExchange.
  • Given a situation, demonstrate knowledge of what can be accomplished with the Einstein Analytics API
  • Given a scenario, use Einstein Analytics to design a solution that accommodates dataflow limits.

Security: 11%

  • Given governance and Einstein Analytics asset security requirements, implement necessary security settings including users, groups, and profiles.
  • Given row-based security requirements and security predicates, implement the appropriate dataset security settings.
  • Implement App sharing based on user, role, and group requirements.

Admin: 9%

  • Using change management strategies, manage migration from sandbox to production orgs.
  • Given user requirements or ease of use strategies, manage dataset extended metadata (XMD) by affecting labels, values, and colors.
  • Given a scenario, improve dashboard performance by restructuring the dataset and/or data using lenses, pages, and filters.
  • Given business and access requirements, enable Einstein Analytics, options, and access as expected.

Analytics Dashboard Design: 19%

  • Given a customer situation, determine and define their dashboarding needs.
  • Given customer requirements, create meaningful and relevant dashboards through the application of user experience (UX) design principles and Einstein Analytics best practices.
  • Given business requirements, customize existing Einstein Analytics template apps to meet the business needs.

Analytics Dashboard Implementation: 18%

  • Given business requirements, define lens visualizations such as charts to use and dimensions and measures to display.
  • Given customer business requirements, develop selection and results bindings with static queries.
  • Given business expectations, create a regression time series.
  • Given customer requirements, develop dynamic calculations using compare tables.
  • Given business requirements that are beyond the standard user interface (UI), use Salesforce Analytics Query Language (SAQL) to build lenses, configure joins, or connect data sources.

Einstein Discovery Story Design: 19%

  • Given a dataset, use Einstein Discovery to prepare data for story output by accessing data and adjusting outputs.
  • Given initial customer expectations, analyze the story results and determine suggested improvements that can be presented to the customer.
  • Given derived results and insights, adjust data parameters, add/remove data, and rerun story as needed.
  • Describe the process to perform writebacks to Salesforce objects.

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