From the course: Implementing Data Engineering Solutions Using Microsoft Fabric (DP-700) Cert Prep by Microsoft Press

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Transforming data using Power Query, PySpark, KQL, and T-SQL

Transforming data using Power Query, PySpark, KQL, and T-SQL - Microsoft Fabric Tutorial

From the course: Implementing Data Engineering Solutions Using Microsoft Fabric (DP-700) Cert Prep by Microsoft Press

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Transforming data using Power Query, PySpark, KQL, and T-SQL

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Transforming data by using Power Query, M, PySpark, SQL and KQL. So if we're looking at selecting data using T-SQL, PySpark and KQL, well from a T-SQL perspective we can select, specify our columns and specify our table. From a PySpark perspective, we can select specific columns from a data frame, and in KQL, we're using the project keyword and then specifying our columns. So from our orders table, we can project, i.e. select, our customer ID, order date, and order amount. Now let's look at T-SQL specifically. If we're looking at changing data types, we can use cast to change a column type into another column data type. We can also use convert as well. In our string manipulation, we can use functions like upper and left to modify. So upper, for example, will transform all the values in the string into uppercase. Left on the other hand, will return the left, in this case, five characters from the customer name. There are various functions to do string manipulation. Now for date and…

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