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The analytics team at your organization has created Power Bl reports that enrich data about your accounts from Dynamics 365 Sales with data NOT contained in Dynamics 365 Sales. The Power Bl reports are referenced by your executive leadership as the primary source of truth about account success metrics. Sales leadership has requested that sales users can see these insights about the accounts they have access to within Dynamics 365 Sales. You need to enable the insights to be available to sales users in Dynamics 365 Sales. What should you do?
To make Power BI insights available within Dynamics 365 Sales, specifically contextualized for accounts, you should embed the Power BI report with contextual filtering. This ensures that the report dynamically adjusts based on the specific account record a user is viewing.
Embedding with contextual filtering enables sales users to see account-specific insights directly within the Dynamics 365 interface, improving accessibility and relevance.
A company uses Microsoft SharePoint document management in Dynamics 365 Sales to store contracts.
The company wants only the contracts team to have access to the documents. The contracts team has a custom security role.
You need to restrict privileges to secure the documents.
What should you do?
Since the company uses Microsoft SharePoint for document storage, access to documents is controlled through SharePoint permissions rather than Dynamics 365 security roles.
To restrict document access to only the contracts team, you should update the users list in the SharePoint site where the documents are stored. This involves configuring SharePoint permissions to ensure that only the contracts team (or a specific SharePoint group associated with them) has access to the document library where contracts are stored.
A company's IT department has a .CSV file stored on one of their Shared Documents folders within their Microsoft SharePoint sites. The data from the .CSV file is ingested into Dynamics 365 Customer Insights - Data.
The file contains a row header and columns of different types, such as quantities and prices. The file also contains some rows with a high proportion of nulls.
You need to clean and transform the data in Customer Insights - Data to be ready for unification.
Solution: Transform the first row to be used as headers, remove rows that contain null values, and name the query. Select Next and your data is now ready for unification.
Does this meet the goal?
Transforming the first row to be used as headers, removing rows with null values, and naming the query prepares the data appropriately for unification in Customer Insights - Data.
By setting the headers and removing rows with high proportions of nulls, the data becomes cleaner and more structured, which is essential for successful unification in Customer Insights. Therefore, this solution meets the goal of preparing the data for unification.
An organization is using Microsoft Power Query when connecting to data sources in Dynamics 365 Customer Insights - Dat
a. You need to load contacts to Customer Insights - Data using Power Query. Which is an appropriate action to take when using Power Query to ingest data?
In Dynamics 365 Customer Insights - Data, when using Power Query to ingest data, the Get Data functionality allows users to add multiple tables from various data sources.
This flexibility enables users to enrich the dataset by pulling in additional tables that may be related or necessary for the data unification process.
Power Query in Customer Insights supports creating robust data flows by allowing multiple tables to be added within a single data source setup, providing a comprehensive data modeling environment.
A company's IT department has a .CSV file stored on one of their Shared Documents folders within their Microsoft SharePoint sites. The data from the .CSV file is ingested into Dynamics 365 Customer Insights - Data.
The file contains a row header and columns of different types, such as quantities and prices. The file also contains some rows with a high proportion of nulls.
You need to clean and transform the data in Customer Insights - Data to be ready for unification.
Solution: Transform the first row to be used as headers, define column types to be the appropriate field types and name the query. Select Next and your data is now ready for unification.
Does this meet the goal?
While transforming the first row to be used as headers and defining column types are necessary steps, the solution does not address removing rows with high proportions of nulls. Rows with significant null values can interfere with the quality of the unification process in Customer Insights - Data.
Therefore, this solution does not fully meet the goal as it does not handle data quality issues caused by null values.
