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Tableau CRM and Einstein Discovery Consultant
After passing the Community Cloud Consultant exam in August 2020, I decided my next goal was Tableau CRM and Einstein Discovery Consultant (formerly Einstein Analytics and Discovery Consultant). Demand for this qualification is high. Analytics, Data Science, and Business Intelligence are an important and expanding part of Salesforce offerings.
It took nearly six weeks full-time to get ready for this exam. In this guide I will tell you about the journey, many surprises, and a diverse collection of useful study resources from unexpected places.
The exam will test your knowledge on:
- Security & Access
- Extending Custom Objects & Applications
- Auditing & Monitoring
- Sales Cloud Applications
- Service Cloud Applications
- Data Management
- Content Management
- Change Management
- Analytics, Reports & Dashboards
- Process Automation
Who's the Ideal Candidate?
The ideal candidate for taking the Tableau CRM and Einstein Discovery Consultant certification is someone who has been actively working with the product and has hands-on experience with data ingestion processes, security and access implementations, and dashboard creation.
By taking this credential, you’ll demonstrate your competency to design and build apps, datasets, dashboards in Tableau CRM (formerly Einstein Analytics) and stories in Einstein Discovery.
As always, this exam is made up of topics with varying weightings. It’s important to pay attention to the weightings so that you focus on preparing for topics that will have the greatest number of questions on the exam.
There are six exam topics in the Tableau CRM and Einstein Discovery Consultant exam, and importantly, four of these exam topics represent a fifth of the exam each. Below are the exam topics, presented in the sequence I would suggest you study for the exam.
1. Data Layer 24%
We know Salesforce as a database of tables, or objects, related to each other through record keys, parents, children, related lists, or lookups. Datasets in Einstein are the polar opposite. Einstein datasets are single denormalized sequential lists, optimized by Salesforce for read performance. The Data Layer in Einstein is all about extracting data from sources, then transforming and loading it into Einstein as an Einstein Data Set.
- Extract, transform, and load data into Einstein Analytics
- Name and function of all data transformations
- Create datasets
- Implement refreshes and data sync
- Using the dataset builder
- What is the difference between a recipe and data flow
- Code data flows and recipes.
- What is extended metadata (XMD)
- How to use XMD
- Combine data from multiple datasets or connected objects.
- Write back
2. Analytics Dashboard Design 19%
Dashboard design in Einstein means exactly that. How to design and implement a dashboard that meets a set of requirements.
- How to use templated and pre-built apps
- What are the features and advantages of using templated apps?
- What is a dashboard widget?
- Apply best practices of appearance and design
- Template customization
- Determine the best type of chart for a given problem
- Types of Einstein Discovery charts, such as pie, line, funnel, bar, stacked bar
- What is the Event Monitoring app and how is it set up?
3. Einstein Discovery Story Design 19%
Einstein Discovery is the analytics tool for understanding and interpreting sales data, and making predictions and decisions based on that data. Personally I found this the most interesting part of Einstein. It requires an elevated level of licensing known as Einstein Analytics Plus and there are exam questions about this.
- What is an Einstein story?
- Prepare data for story output
- Analyze story output
- Make appropriate suggestions for improvement based on a story
- Implement Salesforce object write-back
- Explain insights: Descriptive, diagnostic, predictive, prescriptive, selective
- What is an outcome variable in Einstein?
- How does an outcome variable relate to independent and dependent variables?
- What types of insights exist in Einstein Discovery?
- What are over-fitting and under-fitting?
- What is the GINI coefficient?
- What is the difference between Einstein Analytics Platform and Einstein Analytics Plus?
4. Analytics Dashboard Implementation 18%
Dashboards in Einstein are special because they are interactive to a level you do not see in Salesforce. Users can perform what-if analysis and see the results modeled immediately.
- How to use the Event Monitoring Analytics App
- Code lenses and filters
- How to use compare tables
- Trend reports
- What is faceting?
- Time-series analysis reports
- What is a calendar heat map and how is it used?
- What are bindings and interactions?
- Changing cosmetic attributes of charts
- Where are templates stored?
- What is the command syntax to query a template repository?
5. Administration 9%
Einstein is a different product; system administration, management, and security work differently. There are users, profiles, licenses, and permission set licenses to understand.
- Manage dataset extended metadata
- Migration from sandbox to production
- Settings and options to improve dashboard and query performance
- How to use the Dashboard Inspector
- How to use change sets
Elements that can and can not be deployed in a change set
- What are: Integration user, security user, integration user profile, security user profile, integration user license?
- What is the difference between permission sets for Einstein Analytics Platform and Einstein Analytics Plus?
- Currency management
6. Security 11%
Security, just like Administration, is different with Einstein. Field level security (FLS) does not exist. There are still users, groups, and profiles, but there are new standard users, Einstein specific profiles, permission sets, licenses, and Einstein permission set licenses. Security predicates are unique to Einstein. There is app-level sharing and new ways of doing row-level security.
- How to control row, column, data set, and app security
- What is app-level sharing?
- How to use roles to control access?
- How does app-level sharing work?
- What are app-roles: Manager, viewer, editor, and designed
- What is sharing inheritance, how does it work, and how is it different in Einstein?
- What is a security predicate?
- How is a security predicate used?
- How is a security predicate coded?
- Sharing inheritance
Through seven previous exams I developed a three-stage process to study for and pass these exams:
- First study the exam guide, release notes, books, Trailhead, manuals, videos, articles, and blogs with the intention of: 1- understand what the product is all about, 2- identify key study topics, 3- enumerate good learning resources, and 4- put together a study plan.
- Second, execute the study plan.
- Third, get in shape with practice tests. Once practice tests are going well it is time to take the exam.
For EAD things went according to plan, with two caveats. Stage 1, putting the study plan together, took longer than expected; more than half my overall study time. Stage 3 was impossible due to the dearth of good practice tests which forced reliance on Einstein super badges instead.
Salesforce Einstein: A Very Different Animal
Stage one took a long time because Tableau CRM and Discovery (and Monitoring) is so different from the Salesforce we all know and love. Unlike the other consultant exams I have taken, EAD is not an extension or application sitting on Sales, Service or Marketing cloud.
Salesforce is transactional. EAD is historical. It is a completely denormalized repository geared for summarizing tremendous amounts of information and presenting it in concise abbreviated dynamic charts. EAD is best thought of as a two-and-a-half discrete products, 1- Analytics, 2- Discovery, and 3- Monitoring; separate from and only loosely coupled with a Salesforce org.
- Analytics is about using data to understand past behavior
- Discovery is about using data to make predictions about the future, and make recommendations for how to best make future decisions
- Monitoring is an application of analytics to render log file data and usage patterns from your Salesforce org.
Underlying all these technologies, are the principles of statistics. By understanding basic statistical concepts we are leveraging, you will be best placed to interpret results in the real world. I put together questions you may be asked in a data science job interview that will give you a foundation.
Stage 1 - Make the Study Plan
I found three excellent sources of information for mapping out a study plan and identifying good study resources.
These sources are:
- Salesforce Einstein Trail in Trailhead: Study for the Einstein Analytics and Discovery Consultant Exam
- EA Certification Study Guide by Kelsey Shannon
- Einstein Analytics Discovery Consultant Certification Fast Path, with Nicholas Moscaritolo
Using these three sources I was able to put a more comprehensive study plan together and start executing. The key resources I used to study for this exam are:
- Exam guide
- Release note
- Einstein-specific practice orgs
- Kelsey Shannon’s web pages
- Debasis Jena’s Einstein class on Udemy
- Trailhead Study for the Einstein Analytics and Discovery Consultant Exam Trail
- Moscaritolo video and slide deck
- Johan Yu’s book Getting Started with Salesforce Einstein Analytics
- Download and read the Security and User’s guides
- Look over the two Einstein super badges: CRM data preparation specialist, and CRM discovery insights
We’ll dive into each resource in more detail in the “Resources” section of this guide.
Stage 2: Execute the Study Plan
- Read the Exam Guide and Release Note. Create an Einstein practice org.
- Follow Kelsey Shannon’s path. Read every citation. Complete the suggested Trailhead modules.
- After completing each topic section in Kelsey Shannon’s plan, study the Trailhead modules and documentation references cited in the Salesforce Einstein Trail and in Nicholas Moscarilito’s slide deck.
- Study the Einstein Plus Analytics Training from Salesforce video series hosted by Ziad Fayad and Randy Sherwood.
- Do every Trailhead module with ‘Einstein’ in the title!
- Attend no-charge webinar events offered by Salesforce offered through Certification Days, Accelerators, and Circles of Success.
- Take good notes. By exam day I had about 20 pages including a full page exclusively on licenses, profiles, permissions, permission sets, and permission set licenses.
Stage 3: Take the Exam
- Use the two Einstein super badges to gauge when and whether you are ready. When you get to the point of a good understanding of these two superbadges and can complete each one in a day, you are ready for the exam.
- Use your notes, Johan Yu’s book, and the Security manual. Two days before the exam I stopped studying new material. Instead, I spent this time relaxing, reading, and thinking over everything I learned. I re-read Johan’s book several times, went through all my notes, studied questions in the Trailhead Einstein Trail, and read the Einstein Security Guide. On the morning of exam day I read and re-read the notes, and Johan Yu’s chapter on Security, right up until it was time to ‘click to start exam’.
Having now shown you the study plan outline I will tell you in detail about the study resources I found during stage one, and how I used them.
Exam Guide, Release Notes, and Practice Orgs
All certification journeys seem to start with the exam guide, release note, and a developer org. The Einstein Trailhead modules will soon show you how to set up a special Einstein practice org that is primed with practice datasets.
Once the Einstein org is set up, there is a lot of valuable information to be learned by looking in this org at the Einstein specific users, profiles, permissions, permission sets, licenses, and permission set licenses.
It is important to understand the differences between Einstein Analytics Platform, and Einstein Analytics Plus.
This is the best Einstein certification study resource on the planet. Ms. Shannon is an EAD expert working for Indeed in Austin. Her blog details a nicely organized study plan, starting with Data Layer and concluding with Admin and Security.
Hers is the only study plan that cites both Salesforce and outside non-Salesforce learning resources. She cites excellent articles from recognized third-party sources such as Mark Tossell, Rikke Hougaard, and Johan Yu. From her pages I also learned about the Einstein Analytics Plus Training from Salesforce series.
Early in this journey I found an Einstein instructional video on Udemy by Debasis Jena. Having used his resources before to pass the Community Cloud exam, it was a no-brainer to subscribe to this class. It is about 10.5 hours of video and the content is outstanding. He is a bright well-spoken young man, knows Salesforce, and presents in an organized fashion. It served me well trying to gain an overview and understanding of what Einstein is all about.
It seems to me Salesforce really wants people to pass this exam. They do not make it easy, but they furnish an abundance of rich study resources and guidance. They make tons of study material available, and they try to organize paths and trails so you can learn in a coherent sequence. Salesforce provides the Salesforce Einstein Trail in Trailhead; whilst the trail contains much useful information, I recommend you study in the order advised by Kelsey Shannnon.
Further evidence that Salesforce wants you to pass this exam is the excellent, detailed and lengthy Einstein Analytics Plus Training from Salesforce series hosted by Ziad Fayad and Randy Sherwood. There are 44 videos totaling 13 hours. I saw several questions on the exam that were lifted off the pages of this series.
Ziad Fayad presents Analytics through the first 35 clips. Randy Sherwood presents Discovery in the remainder. Both are knowledgeable and speak flawlessly. It is nice to take a class from an excellent instructor and these guys are great.
You will soon learn in your journey through Einstein that Analytics gets excellent coverage, and Discovery, not so much. The Discovery clips presented by Randy Sherwood fill that gap. Given the dearth of Discovery educational resources these recordings warrant careful study.
Randy Sherwood is positively hilarious, at one time equating iterative Einstein Discovery what-if analysis to playing whack-a-mole, advising us with great sincerity that:
“Don’t worry. Here at Salesforce we love our woodland creatures. No moles were harmed in the making of this video”.
He has a bunch of lines like that. You will enjoy his videos.
Einstein Analytics Discovery Certification Fast Path with Nicholas Moscaritolo is a one-hour instructional video on Youtube by Salesforce. Mr. Moscaritolo is Salesforce Director of Cloud Solution Alliances and Einstein Alliances, and an author of the certification exam.
The video presents all topics on the exam. He identifies key topics, important areas to study, and caveats to watch for. At the end of each topic section is a long list of links into Salesforce Help that he suggests be studied.
From my own experience, having taken eight exams now, it looks to me like a lot of exam questions come almost directly from the Salesforce documentation. Here in this video from Salesforce, we have one of the exam authors telling us what to study. I listened carefully.
There is a slide deck that comes with this video. It is in PDF format and all the citations are clickable. The same link is also in the video comment section.
Courtesy of this recent article by Christine Marshall in Salesforce Ben I learned about Salesforce Certification Days. These are no-charge exam review webinars. I attended two cloud consultant sessions. While a bit off topic, every bit of learning helps. I received a discount coupon code, then learned of, and took, a low-cost practice exam through Webassessor.
From the Tableau CRM Trailblazer Community, I learned of Salesforce Circles of Success no-cost webinars. I attended sessions covering EA Monitoring and Einstein Service Cloud Analytics.
There are links to Salesforce Accelerator webinars from the EAD Learning Map. These are no-charge educational web events about Einstein that are informative and useful.
Early in this journey I found Getting Started with Salesforce Einstein Analytics, written by Johan Yu. He is author of the well-known simplysfdc blog. He publishes on Salesforce Ben, and is frequently cited by Kelsey Shannon as a good source of study information.
The book is all about Analytics, not Discovery or Monitoring. It is a nice short easy read and a very good resource to get acquainted with the Analytics part of EAD. The chapter on Security is especially helpful. It is a nice introduction to security in EAD and will help you understand how Einstein security is different from Salesforce.
It is two years old but the only part conspicuously dated is on bindings, now known as interactions. This seems to be OK because the exam had questions about bindings.
Read the Fabulous Manuals
The Salesforce manuals are excellent study resources. I prefer reading the pdf versions of Salesforce manuals, perhaps because I am old and old-fashioned; but they have all the information in one place. I read the User’s guide and the Security guide for this exam. It has been my experience with eight certifications now that exam questions are often lifted from the manuals. Nicholas Moscarlito in his video repeatedly points out that the help documents are excellent study resources, and he is an author of this exam.
When exam day arrives, there are tips gathered over the years to help improve chances of passing.
Keep a “Hot List”
As you work through the study material, keep a list of topics you feel are key, unusually convoluted, or require memorization. My final two days before the exam were tightly choreographed. I did not feel confident. I stopped learning new material and devoted time to reviewing notes, Johan’s book, and the Security manual; all to review, remember, reflect on, and reinforce what I learned. In the final hour before exam time I studied a page of notes with details of licenses, permissions, permission sets, Integration and Security User, and profiles. Memorize these on exam day so they are fresh in your mind.
Study the Question
When reading exam questions, make sure you understand the question. Read it several times. When deciding on answers, use a process of elimination to exclude incorrect ones. Salesforce will include answers with non-existent features or answers that are simply incorrect. They throw curveballs, such as features that are correct but not best practice. Eliminate exogenous answers by focusing on standard Salesforce features that accomplish a task.
Scrutinize Multiple Choice Answers
Most questions require two or three correct answers out of four or five choices. These questions warrant careful examination. There is no partial credit. The question is correct only if all correct answers are selected. People often pass this exam with a thin margin of success, equal to one or two questions.
Manage Exam Time
Manage test time to comfortably work through the exam twice. Quickly answer questions you feel confident about. Leave uncertain questions for the second pass. You will learn things by seeing all exam questions. Use “Mark for Review” for problematic questions and the second pass. There are normally 60 questions, but your exam may have five additional unscored experimental questions. On my exam the experimental questions were pretty obvious. Passing score is 68%. Exam time is normally 90 minutes, 95 minutes if there are these experimental questions. Use all of your allocated time. When you finish, go back and review again. Do not exit the exam early.
Trust Your Judgement
During your review pass through the exam, be cautious about changing answers. Make changes if you have a good reason. If you studied, you probably know more than you think. Your first choice is likely your best choice. If you feel uncertain about many answers or find yourself making frequent changes you did not study enough.
Book Sooner Not Later
When you start to feel confident with the study material, and you are scoring well on practice exams, book the exam a week in advance. If you have been diligent about studying you are probably better prepared than you feel. A scheduled exam date helps you focus.
Please bear in mind this exam covers Analytics, Discovery, and Monitoring. There are many educational resources that cover Analytics. Discovery coverage is thinner, best found in Trailhead and Randy Sherwood’s videos. Do not neglect to study Discovery. Study resources for Monitoring are also thin, but I saw just two questions about it on the exam.
This is a long, effusive article. It describes an immersive six-week journey through EAD; I studied continuously around the clock from mid December through late January. Like Community Cloud, it was challenging. There is a lot to cover, and a lot of study resources. In reality, you are studying for 2 1/2 exams, not 1, on a topic far removed from Salesforce as we know it. That, combined with a higher passing score of 68% (other exams are 65%) means that EAD does take a lot of effort to pass first time.