DRAG DROP (Drag and Drop is not supported)You have the following table named Employees.You need to calculate the employee_type value based on the hire_date value.How should you complete the Transact-SQL statement? To answer, drag the appropriate values to the correct targets. Each value may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.NOTE: Each correct selection is worth one point.Select and Place:
Answer(s): A
Box 1: CASECASE evaluates a list of conditions and returns one of multiple possible result expressions.CASE can be used in any statement or clause that allows a valid expression. For example, you can use CASE in statements such as SELECT, UPDATE, DELETE and SET, and in clauses such as select_list, IN, WHERE, ORDER BY, and HAVING.Syntax: Simple CASE expression: CASE input_expression WHEN when_expression THEN result_expression [ ...n ] [ ELSE else_result_expression ] END Box 2: ELSE
https://docs.microsoft.com/en-us/sql/t-sql/language-elements/case-transact-sql
DRAG DROP (Drag and Drop is not supported)You have an Azure Synapse Analytics workspace named WS1.You have an Azure Data Lake Storage Gen2 container that contains JSON-formatted files in the following format.You need to use the serverless SQL pool in WS1 to read the files.How should you complete the Transact-SQL statement? To answer, drag the appropriate values to the correct targets. Each value may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.NOTE: Each correct selection is worth one point.Select and Place:
Box 1: openrowsetThe easiest way to see to the content of your CSV file is to provide file URL to OPENROWSET function, specify csv FORMAT.Example:SELECT *FROM OPENROWSET( BULK 'csv/population/population.csv', DATA_SOURCE = 'SqlOnDemandDemo', FORMAT = 'CSV', PARSER_VERSION = '2.0', FIELDTERMINATOR =',', ROWTERMINATOR = '\n'Box 2: openjsonYou can access your JSON files from the Azure File Storage share by using the mapped drive, as shown in the following example:SELECT book.* FROM OPENROWSET(BULK N't:\books\books.json', SINGLE_CLOB) AS json CROSS APPLY OPENJSON(BulkColumn) WITH( id nvarchar(100), name nvarchar(100), price float, pages_i int, author nvarchar(100)) AS book
https://docs.microsoft.com/en-us/azure/synapse-analytics/sql/query-single-csv-filehttps://docs.microsoft.com/en-us/sql/relational-databases/json/import-json-documents-into-sql-server
HOTSPOT (Drag and Drop is not supported)You have an Apache Spark DataFrame named temperatures. A sample of the data is shown in the following table. You need to produce the following table by using a Spark SQL query.How should you complete the query? To answer, drag the appropriate values to the correct targets. Each value may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.NOTE: Each correct selection is worth one point.Select and Place:
Box 1: PIVOTPIVOT rotates a table-valued expression by turning the unique values from one column in the expression into multiple columns in the output. And PIVOT runs aggregations where they're required on any remaining column values that are wanted in the final output.Incorrect Answers:UNPIVOT carries out the opposite operation to PIVOT by rotating columns of a table-valued expression into column values.Box 2: CASTIf you want to convert an integer value to a DECIMAL data type in SQL Server use the CAST() function.Example:SELECTCAST(12 AS DECIMAL(7,2) ) AS decimal_value;Here is the result:decimal_value 12.00
https://learnsql.com/cookbook/how-to-convert-an-integer-to-a-decimal-in-sql-server/https://docs.microsoft.com/en-us/sql/t-sql/queries/from-using-pivot-and-unpivot
You have an Azure Data Factory that contains 10 pipelines.You need to label each pipeline with its main purpose of either ingest, transform, or load. The labels must be available for grouping and filtering when using the monitoring experience in Data Factory.What should you add to each pipeline?
Answer(s): D
Annotations are additional, informative tags that you can add to specific factory resources: pipelines, datasets, linked services, and triggers. By adding annotations, you can easily filter and search for specific factory resources.
https://www.cathrinewilhelmsen.net/annotations-user-properties-azure-data-factory/
HOTSPOT (Drag and Drop is not supported)The following code segment is used to create an Azure Databricks cluster.For each of the following statements, select Yes if the statement is true. Otherwise, select No.NOTE: Each correct selection is worth one point.Hot Area:
Box 1: YesA cluster mode of ‘High Concurrency’ is selected, unlike all the others which are ‘Standard’. This results in a worker type of Standard_DS13_v2.Box 2: NoWhen you run a job on a new cluster, the job is treated as a data engineering (job) workload subject to the job workload pricing. When you run a job on an existing cluster, the job is treated as a data analytics (all-purpose) workload subject to all-purpose workload pricing.Box 3: YesDelta Lake on Databricks allows you to configure Delta Lake based on your workload patterns.
https://adatis.co.uk/databricks-cluster-sizing/https://docs.microsoft.com/en-us/azure/databricks/jobshttps://docs.databricks.com/administration-guide/capacity-planning/cmbp.htmlhttps://docs.databricks.com/delta/index.html
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