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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Layer | 24% | - Data transformation and loading into Einstein datasets - Dataflow configuration for multi-object scenarios - Troubleshooting failed dataflow jobs - Understanding denormalized sequential datasets - Data extraction from sources - Incremental sync configuration |
| Topic 2: Security | 16% | - App sharing based on user and group requirements - Implementing security settings for users, groups, and profiles - Dataset security settings using sharing inheritance and security predicates |
| Topic 3: Analytics Dashboard Design | 13% | - Creating dashboards following CRM Analytics best practices and UX design principles - Scoping, validating, and prioritizing dashboard design requirements - Identifying appropriate use and configuration of standard CRM Analytics templated apps |
| Topic 4: Analytics Dashboard Implementation | 19% | - Configuring dashboards using accurate query types and widget-level parameters - Monitoring and optimizing query performance using Dashboard Inspector - Developing selection/result interactions with different query types - Implementing delivery management strategies using versioning and/or Dashboard Publisher - Using advanced functionality such as windowing and time series analysis in compare tables - Making dashboards actionable and accessible in Lightning pages |
| Topic 5: Einstein Discovery | 12% | - Adjusting data parameters and adding/removing data or columns to improve models - Enabling prediction features on Lightning record pages across Salesforce and CRM Analytics - Analyzing model results and proposing data improvements - Building models by assessing data and selecting prediction types (numeric, binary, multi-classification) - Monitoring and interpreting Model Cards to improve or maintain model performance |
| Topic 6: Administration | 16% | - Embedding analytics in Salesforce - Understanding recipes (Data Prep) for visual ETL interface - Managing CRM Analytics environment and configurations - SAQL query language for dashboard JSON and lens queries |
1. Exhibit:
Which two statements can be determined based on the Why it Happened graphic above' Choose 2 answers
A) The -2.2 Unexplained means there are effects that Einstein will never be able to explain regardless of the dataset.
B) Germany sells more Call Center product and that helps them increase their win rate.
C) Call Center is a generally poor performing product, and since there is more in Germany that has a negative effect.
D) Germany performs lower than average but better when the product is Call Center.
2. A company wants to use Einstein Analytics to analyze the trend of their sales pipeline. The company wants to accelerate the sales process. To do so, they need to know the average time an opportunity spends in each stage. This value is not pre-calculated in Salesforce, so a consultant recommends using a dataflow to calculate it.
How can a dataflow be used to calculate the average time an opportunity spends in each stage?
A) computeRelative Transformation with SAQL Expression to calculate the duration
B) computeRelative Transformation with offset parameter to calculate the duration
C) computeExpression Transformation with SAQL Expression to calculate the duration
D) flatten Transformation with Offset Expressions to calculate the duration
3. Philip adds a recently created Seed Bank Orders dataset to an Einstein Analytics app for which the Mosaic Seed Bank project team has the Viewer app role. How much data in the Seed Bank Orders dataset can a project team member see?
A) Only rows designated by the App Manager
B) All rows and fields in the datasets
C) Only rows designated by the Salesforce administrator
D) None of the data
4. A story created has an AUC of .62.
What two things could be done to possible improve this AUC score?
Choose 2 answers
A) Add more rows of relevant data.
B) Change the order of the story insights to descending.
C) Segment the training set.
D) Run detect sentiment on the dataflow before creating the story.
5. In a dataset, there are multiple boolean fields. When displayed on any dashboard, the boolean fields should all be displayed in the same way: a value of true should result in the display of the word "Yes" in green; a value of false should result in the display of the word "No" in red.
In which two ways can this be accomplished? Choose 2 answers
A) In the explorer, select the boolean fields, then create a derived dimension that references the boolean fields, and then modify the values and colors of the derived dimension.
B) Download the XMD for the dataset and change the values and color for the fields and then upload to the dataset.
C) Create an XMD node in the dataflow to change the label and color of the values in the fields.
D) In the explorer, select the boolean fields and use the "edit values" option on the fields to change values and colors.
Solutions:
| Question # 1 Answer: B,C | Question # 2 Answer: A | Question # 3 Answer: B | Question # 4 Answer: B,D | Question # 5 Answer: B,D |
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