SnowConvert AI: Power BI Redshift Repointing¶

Description¶

The Power BI repointing is a feature that provides an easy way to redefine the connections from the M language in the Power Query Editor. This means that the connection parameters will be redefined to point to the Snowflake migration database context. For Redshift, the method in M Language that defined the connection is AmazonRedshift.Database(...). In Snowflake, there is a connector that depends on some other parameters and the main connection is defined by Snowflake.Database(...) method.

Source Pattern Samples¶

Entity Repointing Case: Table¶

This case refers to connections that do not contain embedded SQL. This means that the user has established a connection from Power BI to a table.

Redshift Connection in the Power Query Editor

let
    Source = AmazonRedshift.Database("your_connection","snowconvert"),
    public = Source{[Name="public"]}[Data],
    authors1 = public{[Name="authors"]}[Data]
in
    authors1
Copy

Snowflake Connection in the Power Query Editor

let
    Source = Snowflake.Databases(SF_SERVER_LINK, SF_WAREHOUSE_NAME),
    SourceSfDb = Source{[Name=SF_DB_NAME, Kind="Database"]}[Data],
    SourceSfSchema = SourceSfDb{[Name="public", Kind="Schema"]}[Data],
    SourceSfTbl = SourceSfSchema{[Name="AUTHORS", Kind="Table"]}[Data],
    authors1 = Table.RenameColumns(SourceSfTbl, {{ "AUTHOR_ID", "author_id"}, { "FIRST_NAME", "first_name"}, { "LAST_NAME", "last_name"}, { "BIRTH_YEAR", "birth_year"}})
in
    authors1
Copy

Entity Repointing Case: View¶

This case refers to connections that do not contain embedded SQL. This means that the user has established a connection from Power BI to a view.

Redshift Connection in the Power Query Editor

let
    Source = AmazonRedshift.Database("your_connection","snowconvert"),
    public = Source{[Name="public"]}[Data],
    author_books_view1 = public{[Name="author_books_view"]}[Data]
in
    author_books_view1
Copy

Snowflake Connection in the Power Query Editor

let
    Source = Snowflake.Databases(SF_SERVER_LINK, SF_WAREHOUSE_NAME),
    SourceSfDb = Source{[Name=SF_DB_NAME, Kind="Database"]}[Data],
    SourceSfSchema = SourceSfDb{[Name="public", Kind="Schema"]}[Data],
    SourceSfTbl = SourceSfSchema{[Name="AUTHOR_BOOKS_VIEW", Kind="Table"]}[Data],
    author_books_view1 = Table.RenameColumns(SourceSfTbl, {{ "BOOK_TITLE", "book_title"}, { "AUTHOR_FULL_NAME", "author_full_name"}, { "PUBLICATION_YEAR", "publication_year"}, { "GENRE", "genre"}})
in
    author_books_view1
Copy

Embedded SQL Case¶

This case refers to connections that contain embedded SQL inside them. This sample shows a simple query, but SnowConvert AI covers a range of larger scenarios. Besides, depending on the migrated query, there may be warning messages known as EWI—PRF—FDM. This will help the user identify patterns that need extra attention.

Redshift Connection in the Power Query Editor

let
    Source = Value.NativeQuery(AmazonRedshift.Database("your_connection","snowconvert"), "SELECT * FROM authors LIMIT 5", null, [EnableFolding=true])
in
    Source
Copy

Snowflake Connection in the Power Query Editor

let
    SfSource = Value.NativeQuery(Snowflake.Databases(SF_SERVER_LINK,SF_WAREHOUSE_NAME,[Implementation="2.0"]){[Name=SF_DB_NAME]}[Data], "--** SSC-FDM-0007 - MISSING DEPENDENT OBJECT ""authors"" **
SELECT * FROM
authors
LIMIT 5", null, [EnableFolding=true]),
    Source = Table.RenameColumns(SfSource, {{ "AUTHOR_ID", "author_id"}, { "FIRST_NAME", "first_name"}, { "LAST_NAME", "last_name"}, { "BIRTH_YEAR", "birth_year"}})
in
    Source
Copy
Language: English