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Purpose of this document
This study guide provides a summary of the topics covered in the assessment lab, along with additional resources to help you prepare. Note that the learning path on the credential details page may include more modules than the "Tasks performed" to provide a cohesive learning experience.
Tasks at a glance
Prepare a Real-Time Intelligence environment
Create a KQL database
Create lookup tables
Enable data mirroring in OneLake
Create an Eventhouse and add a KQL database
Supporting module (s):
Create and load data from external sources
Load data from a storage account
Create an external table
Validate that data sources are loaded correctly by using a row count, a filtered count, and a group by count
Supporting module (s):
Load and process streaming data by using Eventstreams
Connect a streaming dataset to an Eventstream
Load data directly
Configure event processing
Load data by using windowing
Send data to a KQL database
Supporting module (s):
Explore the data
Convert SQL to KQL
Query data for min/max, median, and summary statistics
Visualize data by using the render operator, including bar, line, column, and scatter charts
Perform row-based calculations
Create relationships between tables
Process free text data by using the parse operator
Manipulate data
Change data types by using a table variable
Group or aggregate data by using the top-nested operator
Perform data cleansing processes on the data, including time-series
Create an update policy
Create a materialized view
Create a user-defined stored function
Supporting module (s):