A Guide to the Salesforce Einstein Analytics Consultant Certification

*Updated Aug 11, 2021

Are you considering getting a Salesforce Certified Einstein Analytics (now Tableau CRM) and Discovery Consultant Certification? Awesome! No matter where you are in your journey, the goal of this guide is to provide you a centralized resource to access various frameworks so you can nail down that certification. Additionally, I will provide you with conceptual questions and how I prepared for the exam. This guide will also be catered towards Salesforce partners.

I’ve worked alongside Salesforce and have heard it discussed frequently, but I only started exploring it more deeply about three months ago. As a data scientist, I immediately wanted to explore their AI (Einstein) service offerings. This brought me to Einstein Analytics (now Tableau CRM). About 90 days later, here I am- a certified Einstein consultant!

The Definitive Guide

This guide aims to provide the reader with an assortment of helpful links to facilitate preparation for the consultant certification. You don't need to complete everything on the list to be prepared or to become certified. However, the more of these resources you complete, the better your understanding of the tool and what’s required for certification.

That being said- if you want to take a jab at it as quickly as possible, I'd recommend these things in this order:

1. Einstein Training Videos
2. Superbadges - you can complete with their prerequisites, or you can skip to the last step of insights specialist
3. This guide’s Think About section

For partners, I would prioritize the fastpath certification before the training videos. You can also be more selective with what videos you watch. 

About the Exam

Read on for details about the Salesforce Certified Einstein Analytics and Discovery Consultant Certification exam.

• Content: 60 multiple-choice/ multiple-select questions and 5 non-scored questions.
• Time allotted to complete the exam: 90 minutes.
• Passing score: 68%
• Registration fee: $200 USD, plus applicable taxes as required per local law.
• Retake fee: $100 USD, 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.

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%
• Security: 11%
• Administration: 9%
• Analytics Dashboard Design: 19%
• Analytics Dashboard Implementation: 18%
• Einstein Discovery Story Design: 19%

Overall Preparation Resources:

1. Exam Guide 
2. Trailhead Mix
3. Tableau CRM Training Videos 
4. Einstein Learning Map
5. Tableau CRM Developer Portal

If you are a partner, I would recommend the fast track certification videos. There are additional resources for this specific certification that can be found in the partner portal. If you're a salesforce partner, make sure you ask for exam vouchers!

Preparation by Category

Data Layer

This portion of the exam is where you will answer the majority of your questions. First, let’s go over through some valuable resources specific to the data layer. 

The certification expects you to know: 

• Given data sources: How to use data managers to extract and load the data into the EA application to create datasets.
• Given business needs and consolidated data: Implement refreshes, replication, and recipes to appropriately solve the basic business needs.
• Given a situation: Demonstrate knowledge of what can be accomplished using the EA APIs.
• Given a scenario: Use EA to design a solution that accommodates data-flow limits.

**Highly recommended: Tableau CRM Data Preparation Specialist

Key Concepts to remember: Data Sync, Dataflows & Data Recipes, Dataset builder, Transformations

Think about:

1. What’s the difference between dataflows & data recipes?
2. What are the transformations available for dataflows and data recipes? When would you use what transformation? **Extremely important (Situations will be presented. Play close attention to loading data, augment, filter, etc)
3. What is Data Sync? How is it useful? What are best practices and limitations of data syncs?
4. Permissions regarding dataflows and datasets **Important (Situations will be presented)
5. Analytics External Data API, Rest API’s 

Partner Benefit: Pay close attention to the first two videos of Fast Path Certification to Einstein Analytics Consultant. It’s a fantastic resource, so take a lot of notes!

Useful Documentation Resources:

• 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
• Transformations for Analytics Dataflows
• Analytics External Data API Developer Guide

Video Content:  Videos 1-3A (The title of the video will contain the number)

Security User & Administration

The certification expects you to know:

• Given governance and EA asset security requirements, implement necessary security settings including users, groups, and profiles.
• Given row-based security requirements and security predicates, implement the appropriate datasets security settings.
• Implement App-sharing based on user, role, and group requirements.
• Using change management strategies, manage the migration from sandboxes to production organization.
• Given a scenario, improve dashboard performance by restructuring the datasets and data using lenses, pages, and filters.
• Given a user requirement, manage datasets extended metadata by affecting labels, values, and colors.
• Given business and access requirements, enable QA, options, and access as expected.

Key Concepts to remember: Integration User, Security User, Sharing Inheritance, Security Predicates, Limitations of Security, Migrating Assets, Analytics REST API, Change Sets, Modifying XMD (Use Cases)

Think about:

1. What’s the difference between integration and security users?
2. What is sharing inheritance? When can I use it and when does it not work (does it work on all objects?).
3. What are security predicates? How do you use security predicates and sharing inheritance together?
4. Situations will be presented as questions- for example; X cannot see some rows, why can’t X see them?
5. How do you migrate from development to production?
6. How do you change sort orders, values of colors, labels etc? What are the ways you can modify XMD?

Partner Benefit: Pay close attention to the second video of Fast Path Certification to Einstein Analytics Consultant. It’s a fantastic resource- take a lot of notes!

Useful Documentation Resources:

• Manage and Share Einstein Analytics in Apps
• Salesforce Sharing Inheritance for Datasets
• Predicate Expression Syntax for Datasets
• Row-Level Security for Datasets
• 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

Video Content: 20-23, 26 (The title of the video will contain the number)

Analytics Dashboard Design

The certification expects you to know:

• 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.

**Highly recommended: Tableau CRM and Einstein Discovery Insight Specialist

Partner Benefit: Pay close attention to the second and third video of Fast Path Certification to Einstein Analytics Consultant. 

Think about:

1. When to use what type of visualization? When would you use a metric radar chart?
2. Understanding the steps to building a dashboard depending on a client situation.
3. What are apps and when you should use them?
4. Conditional formatting.
5. What is the purpose of JSON files and how do you navigate them?
6. Features of the dashboard inspector.

Useful Documentation Resources:

• Automatically Highlight Data with Conditional Formatting
• Best Practices for Building Your Own Analytics Dashboard
• Run Your Dashboards Faster with the Dashboard Inspector
• Analytics Lookbook
• Salesforce Release NotesManage and Share Einstein Analytics in Apps
• JSON Files
• Create (or update) the WaveTemplate Object
• Best Practices for Building Your Own Analytics Dashboard

Video Content: 5,6,8,12 (The title of the video will contain the number)

Analytics Dashboard Implementation

The certification expects you to know:

• 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.

Partner Benefit: Pay close attention to the third video of Fast Path Certification to Einstein Analytics Consultant. 

Key Concepts: Lens, Queries, Faceting, Binding, SAQL, Time-Series, Calculations and Compare table, joins

Things to think about:

1. Compare Table vs SAQL.
2. Understanding Basic SAQL.
3. Types of bindings and binding syntax. Cell() vs row() vs column() etc.
4. What are the requirements for faceting?
5. When do we use bindings over faceting?
6. How do you run time series, “fix a time-series query”.

Useful Documentation Resources:

• Explore and Visualize Your Data in Einstein Analytics
• Build Einstein Analytics Dashboards
• Progressive Disclosure 
• 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
• Visualize Data With Charts
• Customize Charts with Chart Properties
• SAQL statements
• fill – statement
• Wave Funnel Powered by Custom SAQL
• Navigate Compare Table Columns
• Add Custom Formulas to Columns
• Configure Cross-Dataset Faceting with Connected Data Sources
• Interactions in Analytics Dashboards

Video Content: 4, 7, 8, 9, 10, 24, 25 (The title of the video will contain the number)

Einstein Discovery Story Design

The certification expects you to know:

• 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 improve story as needed.
• Understand models in production and enable prediction features across Salesforce CRM and Einstein Analytics

Partner Benefit: Pay close attention to the third video of Fast Path Certification to Einstein Analytics Consultant. It’s a fantastic resource, so take a lot of notes!

Key Concepts: Einstein Discovery Process, Dataset builder, model metrics, Einstein writeback, different type of insights

Think about:

For this section I would suggest you get familiar with the entire Einstein Discovery interface. Understand how to explain all the insights that Einstein presents to you, along with how to explain them. Understand the steps to write a model back to Salesforce. Be familiar with different model metrics and the concepts of how you choose variables and iterate through different models.

Useful Documentation Resources:

• Prepare Data for Analysis
• Create a Story
• Explore Model Metrics
• Explore Story Insights
• Story Interface
• Display Einstein Predictions Using Custom Fields (Advanced)
• 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

Video Content: 27-32A (The title of the video will contain the number)​

With that, the guide comes to an end. I hope this blog will serve as a good resource for anyone trying to get their certification. The certification can get tricky at times, but if you understand the Tableau CRM ecosystem and how things work (at a high level) you should be successful! Good Luck!

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