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What is one of the workarounds to achieve similar results to cross-dataset joins in Flow.BI?

Creating virtual datasets using SQL queries

Why are cross-dataset joins not currently supported in Flow.BI?

Security concerns

What is the purpose of creating a third virtual dataset in Flow.BI?

To join two separate virtual datasets

What is the main advantage of using virtual datasets in Flow.BI?

Combining data from multiple sources

Which type of dataset is recommended for achieving a cross-dataset join in Flow.BI?

Virtual dataset created using SQL queries

How can virtual datasets be used after combining data from multiple sources?

To create charts, dashboards, and reports

What is the recommended approach for joining datasets inside a SQL query for a virtual dataset in Flow.BI?

Always join inside the SQL query for a virtual dataset

Cross-dataset joins are currently supported in Flow.BI.

False

Virtual datasets in Flow.BI are created using SQL queries.

True

Creating a third virtual dataset to join two virtual datasets together is the only workaround for achieving a cross-dataset join in Flow.BI.

False

It is recommended to join inside the SQL query for a virtual dataset in Flow.BI.

True

Charts, dashboards, and reports can be created directly using the separate virtual datasets without the need for a third virtual dataset.

False

Physical datasets are recommended for achieving a cross-dataset join in Flow.BI.

False

One of the advantages of using virtual datasets in Flow.BI is the ability to combine data from multiple sources into a single dataset.

True

Match the following terms with their correct descriptions in Flow.BI:

Virtual datasets = Datasets created using SQL queries Cross-dataset joins = Currently not supported due to security concerns Separate virtual datasets = Created for each data source Third virtual dataset = Joins the two virtual datasets together

Match the following steps with their correct actions for achieving a cross-dataset join in Flow.BI:

Create a virtual dataset for each data source = First step to combine data from multiple sources Create a third virtual dataset = Joins the two virtual datasets together Join the table data and the column data on the table name column = Example of joining in the third virtual dataset Use the third virtual dataset to create charts, dashboards, and reports = Final step after creating separate virtual datasets

Match the following statements with their correct implications about virtual datasets in Flow.BI:

Charts, dashboards, and reports can be created directly using the separate virtual datasets without the need for a third virtual dataset. = Advantage of using virtual datasets One of the workarounds to achieve similar results to cross-dataset joins in Flow.BI. = Using virtual datasets to combine data from multiple sources Virtual datasets in Flow.BI are created using SQL queries. = How virtual datasets are created Creating a third virtual dataset to join two virtual datasets together is the only workaround for achieving a cross-dataset join in Flow.BI. = Workaround for cross-dataset joins

Match the following recommendations with their correct guidelines for cross-dataset joins in Flow.BI:

It is recommended to join inside the SQL query for a virtual dataset in Flow.BI. = Recommended approach for joining datasets inside a SQL query Always join inside the SQL query for a virtual dataset. = Guideline for joining in a virtual dataset Physical datasets are recommended for achieving a cross-dataset join in Flow.BI. = Incorrect recommendation for cross-dataset joins Cross-dataset joins are currently not supported due to security concerns. = Reason why cross-dataset joins are not currently supported

Learn about workarounds for achieving similar results to cross-dataset joins in Flow.BI. Explore the use of virtual datasets and SQL queries to overcome the current lack of support for cross-dataset joins in Flow.BI.

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