Winter ’20 Release
Congratulations on taking the next step to prepare for your Salesforce Einstein Analytics and Discovery Consultant credential. This exam guide has the information you need to help you study and prepare for your exam. Let’s get started!
Contents
About the Salesforce Einstein Analytics and Discovery Consultant Credential
Audience Description: Salesforce Einstein Analytics and Discovery Consultant
Purpose of this Exam Guide
About the Exam
Recommended Training and References
Exam Outline
Maintaining Your Certification
About the Salesforce Einstein Analytics and Discovery Consultant Credential
The Salesforce Certified Einstein Analytics and Discovery Consultant credential is intended for individuals who have the knowledge, skills, and experience with data ingestion processes, security and access implementations, and dashboard creation. This credential encompasses the fundamental knowledge and skills to design, build, and support apps, datasets, dashboards and stories in Einstein Analytics and Discovery.
This exam guide provides information about the Salesforce Certified Einstein Analytics and Discovery Consultant exam.
Audience Description: Salesforce Einstein Analytics and Discovery Consultant
The Salesforce Certified Einstein Analytics and Discovery Consultant exam is intended for an individual who has broad knowledge of the Einstein Analytics and Discovery platform and its capabilities, including: dataset management, permissions and security implementations, advanced Salesforce Analytics Query Language (SAQL) coding to support querying and JSON to support dashboard creation on both desktop and mobile devices.
The Salesforce Certified Einstein Analytics and Discovery Consultant generally has a minimum of one year of experience and skills across the Einstein Analytics and Einstein Discovery domains, including:
FRONT END
Select the right charts to satisfy a business requirement.
Create meaningful and relevant dashboards through the application of UX design principles and Einstein Analytics best practices.
Build SAQL powered lenses.
Evaluate which type of binding (selection or result) is needed for a dashboard.
Connect data sources within the UI.
Build and customize template apps.
Develop dynamic calculation using compare tables.
Improve dashboard performance.
Embed pages in dashboards.
Convert dashboard layouts for mobile.
ADMINISTRATIVE/MIDDLE
Employ user provisioning to manage identity and access.
Manage migration from lower environment change sets and API.
Configure and manage integration with source control system.
Incorporate governance of dashboards and datasets to manage and monitor Einstein Analytics.
Employ security predicates and sharing inheritance for datasets.
Manage App permissions.
Apply encryption to a dataset.
Explain uses for the Einstein Analytics API.
BACK END
Load data into Einstein Analytics including CSV uploads, defining connectors to load data from multi-org, and native Salesforce data.
Create dataset recipes.
Enable and use data sync (replication) to run independent data extracts.
Recognize the impact of enabling data sync.
Manage and workaround dataflow and data sync limits.
Implement role hierarchy.
Add derived fields to a dataset.
Einstein Discovery
Export data to Discovery
Prepare data for Discovery.
Examine story statistics and algorithms to make recommendations.
Surface Discovery insights into standard Salesforce pages.
The Salesforce Certified Einstein Analytics and Discovery Consultant candidate has the experience, skills, and knowledge outlined below:
Certification or experience with other business intelligence (BI), extract-transform-load (ETL), analytics, and reporting tools.
Understanding of dashboard/user experience (UX) design and aesthetics for mobile and for desktop.
Competency in reading and writing Salesforce Analytics Query Language (SAQL) and Salesforce Object Query Language (SOQL).
Competency in developing ETL processes for dataset preparation and management.
Understanding of Master Data Management (MDM).
Competency with developing stories in Einstein Discovery.
Working knowledge of data science life cycle.
Working knowledge of statistical analysis.
Working knowledge of data modeling.
Experience leading technical projects.
Competency in administering, configuring, and securing Einstein Analytics.
Optional experience with administration, configuration, and securing Salesforce.
Configure and perform writeback to Salesforce for Discovery models.
A candidate for this exam is not expected to …
Write Apex code.
Use the Einstein Analytics Software Development Kit (SDK).
Write code using the Einstein Analytics API.
Handle large data volumes and data refreshes.
Purpose of this Exam Guide
This exam guide is designed to help you evaluate if you are ready to successfully complete the Salesforce Certified Einstein Analytics and Discovery Consultant exam. This guide provides information about the target audience for the certification exam, recommended training and documentation, and a complete list of exam objectives—all with the intent of helping you achieve a passing score. Salesforce highly recommends a combination of on-the-job experience, course attendance, and self-study to maximize your chances of passing the exam.
About the Exam
Read on for details about the Salesforce Einstein Analytics and Discovery Consultant exam.
Content: 60 multiple-choice/multiple-select questions
Time allotted to complete the exam: 90 minutes
Passing score: 68%
Registration fee: USD 200, plus applicable taxes as required per local law
Retake fee: USD 100, plus applicable taxes as required per local law
Delivery options: Proctored exam delivered onsite at a testing center or in an online proctored environment. Click here for information on scheduling an exam.
References: No hard-copy or online materials may be referenced during the exam.
Prerequisite: None
Recommended Training and References
We recommend a combination of hands-on experience, training course completion, Trailhead trails, and self-study in the areas listed in the Exam Outline section of this exam guide.
The self-study materials recommended for this exam include:
Trailmix: Learn Einstein Analytics Plus
Trailhead Trails:
Explore with Analytics
Gain Insight with Einstein Discovery
Analytics Apps Basics
Build and Administer Analytics
Accelerate Analytics with Apps
Trailhead Superbadges:
Einstein Analytics Data Preparation Specialist
Einstein Analytics and Discovery Insights Specialist Superbadge
To review online Documentation, Tip Sheets, and User Guides, search for the topics listed in the Exam Outline section of this guide and study the information related to those topics. Documentation, Tip Sheets, and User Guides can also be accessed through Help & Training.
Instructor-Led Training Classes:
Mobile and Desktop Exploration in Einstein Analytics (ANC101)
Building Lenses, Dashboards and Apps in Einstein Analytics (ANC201)
Working with Data and Dashboards in Einstein Analytics (ANC301)
Learning Guide:
Einstein Analytics Learning Adventure
Reference Documentation:
Data Layer
Bring Data into Analytics
Create and Run More Dataflows, and Track Usage with the Flow Indicator
Avoid Data Drift with Periodic Full Sync
Sync Salesforce Data Incrementally in Data Sync
Manage Datasets
Data Integration Guide
Analytics External Data API Developer Guide
Security
Manage and Share Einstein Analytics in Apps
Salesforce Sharing Inheritance for Datasets
Predicate Expression Syntax for Datasets
Row-Level Security for Datasets
Admin
Set Up the Einstein Analytics Platform
Deploy Einstein Analytics Templates
Analytics Templates Developer Guide
Einstein Analytics Encryption
Deploy Your Changes
Analytics Migration, Packaging, and Distribution
Einstein Analytics Limits
Avoid Data Drift with Periodic Full Sync
Sync Salesforce Data Incrementally in Data Sync
Analytics Dashboard Design
Analytics Lookbook
Best Practices for Building Your Own Analytics Dashboard
Analytics Dashboard Implementation:
Explore and Visualize Your Data in Einstein Analytics
Build Einstein Analytics Dashboards
Progressive Disclosure (Loading)
Embed and Customize Einstein Analytics
Analytics Bindings Developer Guide
Analytics REST Query Resource
Analytics SAQL Reference
Wave Funnel Powered by Custom SAQL
Timeseries SAQL Statement
Analytics Extended Metadata (XMD) Reference
Run Your Dashboards Faster with the Dashboard Inspector
Einstein Discovery Story Design
Explore Stories
View Model Metrics
Einstein Discovery Limits
Optimize Data for Predictive Analytics
Display Einstein Discovery Predictions in a Salesforce Object
Improve Your Einstein Discovery Models by Investigating Their Metrics and Performance
Exam Outline
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.
Maintaining Your Salesforce Certification
One of the benefits of holding a Salesforce credential is always being up-to-date on new product releases (updates). As such, you will be required to complete the Einstein Analytics and Discovery Consultant certification maintenance modules on Trailhead three times a year.
Don’t let your hard-earned credential expire! If you do not complete all maintenance requirements by the due date, your credential will expire.
Bookmark these useful resources for maintaining your credentials:
Overall Maintenance Requirements
Maintenance Exam Due Dates
Verify Your Certification Status
Certification Expiration Details
QUESTION 1
What is an appropriate response when a client is disappointed that Einstein Discovery only detected patterns that were already known?
A. Highlight that Einstein reduces time to insight, which is much faster than learning experience
B. Recommend using a visualization tool, like Einstein Analytics, to uncover the details
C. Remind them that the technology is only as good as the data
D. Advise them that the use case may not be accurate
Correct Answer: C
QUESTION 2
A consultant created an Einstein Analytics dashboard in a sandbox. Now, the dashboard needs to be migrated into production.
To complete the migration, what are the consultant’s three options? (Choose three.)
A. Ant Migration Tool
B. Change sets
C. Analytics External Data API
D. Analytics REST API
E. Analytics dashboard connector
Correct Answer: ABD
QUESTION 3
Which set of statements generates monthly amount on a cumulative basis annually?
A. result = load “opportunity1”;
result = group result by (‘CloseDate_Year’,’CloseDate_Month’);
result = foreach result generate ‘CloseDate_Year’,’CloseDate_Month’, sum(sum(Amount)) over ([..0]
partition by ‘CloseDate_Year’ order by (‘CloseDate_Year’,’CloseDate_Month’)) as ‘Cumulative Closed
Amount’;
B. result = load “opportunity1”;
result = group result by (‘CloseDate_Year’,’CloseDate_Month’);
result = foreach result generate ‘CloseDate_Year’,’CloseDate_Month’, sum(sum(Amount)) over ([..]
partition by ‘CloseDate_Year’
order by (‘CloseDate_Year’,’CloseDate_Month’)) as ‘Cumulative Closed Amount’;
C. result = load “opportunity1”;
result = group result by (‘CloseDate_Year’,’CloseDate_Month’);
result = foreach result generate ‘CloseDate_Year’,’CloseDate_Month’, sum(sum(Amount)) over ([..0]
partition by all order by (‘CloseDate_Year’,’CloseDate_Month’)) as ‘Cumulative Closed Amount’;
D. result = load “opportunity1”;
result = group result by (‘CloseDate_Year ~ ~ ~ CloseDate_Month’);
result = foreach result generate ‘CloseDate_Year’,’CloseDate_Month’, sum(sum(Amount)) over ([..0]
partition by ‘CloseDate_Year’ order by (‘CloseDate_Year’,’CloseDate_Month’)) as ‘Cumulative Closed
Amount’;
Correct Answer: D
QUESTION 4
Which chart type is suitable for rendering five measures in a lens visualization?
A. Metric Radar chart
B. Scatter chart
C. Treemap chart
D. Stacked Bar chart
Correct Answer: D
QUESTION 5
An Einstein Consultant receives a request from the Marketing department to help them understand lead
conversion. Presently, they are unaware of the percentage of leads that get converted to sales. They hope to
view results by account manager, value, and quarter. The data is there, so the consultant can add it to the marketing dashboard.
How should this metric be calculated?
A. Create a formula field on the lead object in Salesforce and add it to the dataset
B. Create a new step in the dashboard using a compare table and define a formula
C. Create a computeExpression in the dataflow
D. Create a new step in the dashboard using a compare table and the running total function
Correct Answer: D
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