Einstein Analytics and Discovery Consultant Preparation Kit
0.0 (0 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
4 students enrolled

Einstein Analytics and Discovery Consultant Preparation Kit

Become a Salesforce Certified Einstein Analytics and Discovery Consultant in no time
New
0.0 (0 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
4 students enrolled
Created by SFDC Guru
Last updated 5/2020
English
Einstein Analytics and Discovery Consultant Preparation Kit
Current price: $12.99 Original price: $49.99 Discount: 74% off
30-Day Money-Back Guarantee
This course includes
  • 2 Practice Tests
  • Full lifetime access
  • Access on mobile
Training 5 or more people?

Get your team access to 4,000+ top Udemy courses anytime, anywhere.

Try Udemy for Business
Requirements
  • Einstein Analytics and Discovery knowledge is preferred
  • Salesforce Consultant experience is preferred
Included in This Course
+ Practice Tests
2 Tests 80 questions

This is to test your skills and understand your weaknesses prior to taking the certification exam

Assessment Set
20 questions

The goal of this practice test is to test your skills on a mock exam that is similar to the certification exam. Good luck!

Practice Test
60 questions
Description

Congratulations on taking the next step to prepare for your Salesforce Certified Einstein Analytics and Discovery Consultant credential. This preparation kit has the information you need to help you study and prepare for your exam.

The Salesforce Einstein Analytics and Discovery Consultant exam measures a candidate’s knowledge and skills related to the following objectives.

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.

Who this course is for:
  • Salesforce Consultants
  • Analytics Consultants
  • Business Analysts