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Einstein ANALYTICS AND DISCOVERY CONSULTANT STUDY GUIDE

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. 

  • Create and Run More Dataflows,
  • Bring Data into Analytics and Track Usage with the Flow Indicator

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.

  • Avoid Data Drift with Periodic Full Sync
  • Sync Salesforce Data Incrementally in Data Sync

Given a situation, demonstrate knowledge of what can be accomplished with the Einstein Analytics API

  • Analytics External Data API Developer Guide 

Given a scenario, use Einstein Analytics to design a solution that accommodates dataflow limits.

  • Manage Datasets
  • Data Integration Guide

SECURITY 11%

Given governance and Einstein Analytics asset security requirements, implement necessary security settings including users, groups, and profiles.

  • Manage and Share Einstein Analytics in Apps

Given row-based security requirements and security predicates, implement the appropriate dataset security settings.

  • Salesforce Sharing Inheritance for Datasets 

Implement App sharing based on user, role, and group requirements.

  • Predicate Expression Syntax for Datasets
  • Row-Level Security for Datasets

ADMIN 9%

Using change management strategies, manage migration from sandbox to production orgs.

  • Set Up the Einstein Analytics Platform
  • Deploy Einstein Analytics Templates

Given user requirements or ease of use strategies, manage dataset extended metadata (XMD) by affecting labels, values, and colors.

  • Analytics Templates Developer Guide 
  • Einstein Analytics Encryption
  • Deploy Your Changes

Given a scenario, improve dashboard performance by restructuring the dataset and/or data using lenses, pages, and filters.

  • Analytics Migration, Packaging, and Distribution
  • Einstein Analytics Limits

Given business and access requirements, enable Einstein Analytics, options, and access as expected.

  • Avoid Data Drift with Periodic Full Sync
  • Sync Salesforce Data Incrementally in Data Sync

ANALYTICS DASHBOARD DESIGN 19%

Given a customer situation, determine and define their dashboarding needs.

  • Analytics Lookbook 

Given customer requirements, create meaningful and relevant dashboards through the application of user experience (UX) design principles and Einstein Analytics best practices.

  • Best Practices for Building Your Own Analytics Dashboard 

Given business requirements, customize existing Einstein Analytics template apps to meet the business needs.

  • Einstein Analytics Tempates

ANALYTICS DASHBOARD IMPLEMENTATION 18%

Given business requirements, define lens visualizations such as charts to use and dimensions and measures to display.

  • Analytics Extended Metadata (XMD) Reference
  • Run Your Dashboards Faster with the Dashboard Inspector

Given customer business requirements, develop selection and results bindings with static queries.

  • Explore and Visualize Your Data in Einstein Analytics
  • Build Einstein Analytics Dashboards

Given business expectations, create a regression time series.

  • Progressive Disclosure
  • Embed and Customize Einstein Analytics

Given customer requirements, develop dynamic calculations using compare tables.

  • Analytics Bindings Developer Guide
  • Analytics REST Query Resource
  • Analytics SAQL Reference 

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.

  • Wave Funnel Powered by Custom SAQL
  • Timeseries SAQL Statement

EINSTEIN DISCOVERY STORY DESIGN 19%

Given a dataset, use Einstein Discovery to prepare data for story output by accessing data and adjusting outputs.

  •  Explore Stories 

Given initial customer expectations, analyze the story results and determine suggested improvements that can be presented to the customer.

  • View Model Metrics 

Given derived results and insights, adjust data parameters, add/remove data, and rerun story as needed.

  • Einstein Discovery Limits
  • Optimize Data for Predictive Analytics 

Describe the process to perform writebacks to Salesforce objects.

  • Display Einstein Discovery Predictions in a Salesforce Object
  • Improve Your Einstein Discovery Models by Investigating Their Metrics and Performance

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