EINSTEIN-ANALYTICS-AND-DISCOVERY-CONSULTANT Dumps PDF Free Download

QUESTION: 26

The Universal Containers company uses a Microsoft Azure SQL Data Warehouse to gather information about sales representatives' objectives. They want to use Einstein Analytics to gain insights from this data; therefore, they need to automatically load the warehouse's data into an Einstein Analytics dataset on a daily basis. The data also needs to be transformed and merged with data from the company's org.
Which three Einstein Analytics user interface features can be used to complete these requirements? Choose 3 answers

Dataflow
Microsoft Azure SQL Data Warehouse Connector
Einstein Analytics Connector for Excel
Recipes
Analytics REST API

Answer(s): A,B,D

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QUESTION: 27

What are the two main parts of a lens/exploration?

Query
Visualization
Dataset
Measure
Grouping

Answer(s): B,E

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QUESTION: 28

Which statement best describes how to ensure Einstein Analytics dashboards are easily used across both desktop and mobile devices?

Create multiple layouts, and reorder all the widgets so that they fit nicely within the new default width.
Create a single layout and allow Einstein Analytics to automatically organize dashboard contents to be optimal for the device type.
Create a single layout and reorder all the widgets so that they fit nicely when viewing on either device.
Create multiple layouts, ensure the layout selectors match the device, and resize/hide widgets as necessary to ensure the content is appropriate for the device screen size.

Answer(s): D

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QUESTION: 29

The client is trying to create a SAQL step to predict sales in each sales region. They cannot get the query to return any results, but have identified that the error is in the time series statement. They have asked an Einstein Consultant to review the following query and fix any errors.

Which timeseries statement will fix the query'

q = timeseries q generate 'sum_Sales' as Forecasted_Sales' with (dateCols=('Date_Year, Date_Quarter', "Y-Q"), partition=Region', ignoreLast=true);
q = timeseries q generate 'sum_Sales' as Forecasted_Sales' with (Iength = 12, dateCols=('Date_Year', 'Date_Month". "Y-M"), partition='Region');
q = timeseries q generate 'sum_Sales' as Torecasted_Sales' with (dateCols=('Date_Year', Date_Quarter', "Y-Q"), partition='Region', seasonality=4);
q = timeseries q generate 'sum_Sales' as Torecasted_Sales' with (dateCols=('Date_Year', Date_Quarter', "Y-Q"), partition='Region');

Answer(s): B

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