Tableau CRM and Einstein Discovery Consultant Certification Exam Guide.
1. About the Tableau CRM and Einstein Discovery Consultant Exam
Salesforce Certified Tableau CRM and Einstein 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 Tableau CRM and Einstein Discovery.
- Content: 60 multiple-choice/multiple-select questions and up to 5 unscored questions
- Time allotted to complete the exam: 90 minutes
- Passing score: 68% (41 Questions out of 60)
- Registration fee: USD 200, plus applicable taxes as required per local law
- Retake fee: USD 100, plus applicable taxes as required per local law
2. Exam Outline
Data Layer: 24%
- Given data sources, use Data Manager to extract and load the data into the Tableau CRM 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 Tableau CRM API
- Given a scenario, use Tableau CRM to design a solution that accommodates dataflow limits.
- Given governance and Tableau CRM 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.
- 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 Tableau CRM, options, and access as expected.
Tableau CRM 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 Tableau CRM best practices.
- Given business requirements, customize existing Tableau CRM template apps to meet the business needs.
Tableau CRM 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 improve story as needed.
- Understand models in production and enable prediction features across Salesforce CRM and Tableau CRM
3. Tableau CRM and Einstein Discovery Certification Exam Guide
4. Tableau CRM and Einstein Discovery Certification Trailmix
4. Important Topics for Tableau CRM and Einstein Discovery Certification exam
4.1 Data Layer – 24% (14 Questions)
4.2 Security – 11% (7 Questions)
- Tableau CRM Users, Groups, and Profiles
- Tableau CRM Platform Licenses and Permission Sets
- The Tableau CRM Growth license (grants access Tableau CRM platform) includes two prebuilt permission sets:
- Tableau CRM Growth Admin
- Tableau CRM Growth User
- The Tableau CRM Plus license (grants access to Einstein Discovery) includes two prebuilt permission sets:
- Tableau CRM Plus Admin
- Tableau CRM Plus User
- The Tableau CRM Growth license (grants access Tableau CRM platform) includes two prebuilt permission sets:
- Security predicates
- Security settings
- App sharing based on User, Role, and Group requirements
- Sharing Inheritance
4.3 Administration – 9% (6 Questions)
- Change management strategies
- Extended metadata (XMD)
- Permissions needed to edit XMD
- Improve dashboard performance
- Event Monitoring Analytics
4.4 Tableau CRM Dashboard Design – 19% (12 Questions)
- Tableau CRM Dashboards
- Tableau CRM Dashboard Best Practices
- Tableau CRM Dashboard Template
- Progressive Disclosure Design Principle
- Tableau CRM Template App – Template Location: /services/data/<version_number>/wave/templates
- template-info.json – manages all elements of your template, including metadata information about the template, the Tableau CRM objects that define dashboards and lenses, and the other files that are part of the template
- ui.json – manages the configuration wizard that drives app creation. It defines the number of wizard pages, the order of wizard questions, and any messages you want the user to see
- variables.json – contains all template variables, including text for wizard questions and specifications for the answers. Variables also define conditional questions. For example, you may want some questions to appear in the wizard only if an org contains certain data. Or you might want to add more specific questions based on the answers to more general wizard questions
- template-to-app-rules.json – defines the rules the template follows. For example, you could define a rule that specifies that if an org doesn’t use certain Salesforce objects, the app won’t refer to them in dashboards or include them in the dataflow. Rules also define how variables are handled. For example, if the wizard asks which fields to include in filters for accounts, template-to-app-rules.json determines how that choice is reflected in dashboards. Note: We abbreviate the name of this file to rules.json in the rest of this module for ease of reading
- folder.json – organises the parts of dashboards, for example letting you set the order of dashboards in an app instead of keeping them in alphabetical order
4.5 Tableau CRM Dashboard Implementation – 18% (9 Questions)
- Lens visualizations
- Chart Types
- How can you post to Chatter from a Dashboard
- Integration User is used to access data from Salesforce objects
- Two types of Binding
- Selection and results bindings with static queries
- Regression time series
- Dynamic calculations using compare tables
- Up to 4 grouping columns in a compare table
- Default rows in compare table – 2,000
- Default rows in a value table – 100
- No of Queries per user per day – 10,000
- Maximum Analytic API Calls per user per hour – 10,000
- Maximum External Files uploaded to Einstein Analytics on rolling 24 hour period – 50 files for dataset
- Timeout for ETL jobs that have been scheduled but not executed – 5 mins
- Maximum number of Objects that can be enabled for Data Sync – 100
- Salesforce Analytics Query Language (SAQL)
- Order of Functions in SAQL – filter and order can be interchanged, offset must be after filter/order and limit must come after offset
- 10 Concurrent Queries per user
- SAQL Functions
- coalesce – get the first non-null value from a list of parameters, or to replace nulls with a different value
- Dataflow Transformations
- append Transformation – combines rows from multiple datasets into a single dataset
- augment Transformation – adds columns to a dataset from another related dataset. The resulting, augmented dataset enables queries across both related input datasets
- computeExpression Transformation – enables you to add derived fields to a dataset. The values for derived fields aren’t extracted from the input data source. Instead, platform generates the values using a SAQL expression, which can be based on one or more fields from the input data or other derived fields
- computeRelative Transformation – analyze trends in your data by adding derived fields to a dataset based on values in other rows
- delta Transformation – calculates changes in the value of a measure column in a dataset over a period of time. The delta transformation generates an output column in the dataset to store the delta for each record
- digest Transformation – extracts synced connected data in a dataflow. Use it to extract data synced from an external Salesforce org, or data synced through an external connection
- dim2mea Transformation – creates a new measure based on a dimension. The transformation adds the new measure column to the dataset
- edgemart Transformation – gives the dataflow access to an existing, registered dataset, which can contain Salesforce data, external data, or a combination of the two
- export Transformation – creates a data file and a schema file from data in a specified source node in your dataflow. After the dataflow runs, Einstein Discovery users can access these files through the public API
- filter Transformation – removes records from an existing dataset. You define a filter condition that specifies which records to retain in the dataset
- flatten Transformation – flattens hierarchical data
- prediction Transformation – makes an Einstein Discovery prediction for a dataset
- sfdcDigest Transformation – generates a dataset based on data that it extracts from a Salesforce object
- sfdcRegister Transformation – registers a dataset to make it available for queries. Users cannot view or run queries against unregistered datasets
- sliceDataset Transformation – removes fields from a dataset in your dataflow, leaving you with a subset of fields for use in a new dataset or in other transformations
- update Transformation – updates the specified field values in an existing dataset based on data from another dataset, which we’ll call the lookup dataset
4.6 Einstein Discovery Story Design – 19% (12 Questions)
- Einstein Discovery – business intelligence with statistical modeling and machine learning to identify, surface, and visualize insights into business data. Einstein Discovery uses:
- Descriptive analytics to learn what happened in your historical data (descriptive insights)
- Predictive analytics to reveal why it happened (diagnostic insights), what could happen (predicted future outcomes based on statistical probabilities), and what is the difference between variables (comparative insights)
- Prescriptive analytics to suggest ways in which to improve your predicted outcomes (improvements)
- Einstein Discovery Story – Einstein Discovery uses a story to perform a comprehensive statistical analysis of data powered by statistics, machine learning, and AI
- 500 max story creations per org per month can be purchased more
- 20 max story creation per org per day
- Order of Einstein Discovery insights – most variation in outcome variable in descending order
- Upper and lower limits on columns (vars) in discovery – 2 column minimum and 50 column maximum
- Predictive Insights
Additional Tableau CRM Resources
- Introduction to Marketing Cloud
- Salesforce Certified Marketing Cloud Consultant Exam Guide
- AWS Certified Cloud Practitioner Exam Guide
- Salesforce Admin Interview Questions
- Salesforce CPQ Interview Questions
- Saleforce Marketing Cloud Interview Questions
- Copado Interview Questions
- MuleSoft Interview Questions