How to pipe Azure Data Catalog Data to CSV in PowerShell



Use standard PowerShell cmdlets to access Azure Data Catalog tables.

The CData Cmdlets Module for Azure Data Catalog is a standard PowerShell module offering straightforward integration with Azure Data Catalog. Below, you will find examples of using our AzureDataCatalog Cmdlets with native PowerShell cmdlets.

Creating a Connection to Your Azure Data Catalog Data

You can optionally set the following to read the different catalog data returned from Azure Data Catalog.

    CatalogName: Set this to the CatalogName associated with your Azure Data Catalog. To get your Catalog name, navigate to your Azure Portal home page > Data Catalog > Catalog Name

Connect Using OAuth Authentication

You must use OAuth to authenticate with Azure Data Catalog. OAuth requires the authenticating user to interact with Azure Data Catalog using the browser. For more information, refer to the OAuth section in the help documentation.

$conn = Connect-AzureDataCatalog 

Selecting Data

Follow the steps below to retrieve data from the Tables table and pipe the result into to a CSV file:

Select-AzureDataCatalog -Connection $conn -Table Tables | Select -Property * -ExcludeProperty Connection,Table,Columns | Export-Csv -Path c:\myTablesData.csv -NoTypeInformation

You will notice that we piped the results from Select-AzureDataCatalog into a Select-Object cmdlet and excluded some properties before piping them into an Export-Csv cmdlet. We do this because the CData Cmdlets append Connection, Table, and Columns information onto each "row" in the result set, and we do not necessarily want that information in our CSV file.

The Connection, Table, and Columns are appended to the results in order to facilitate piping results from one of the CData Cmdlets directly into another one.

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Azure Data Catalog Icon Azure Data Catalog Data Cmdlets

An easy-to-use set of PowerShell Cmdlets offering real-time access to Azure Data Catalog. The Cmdlets allow users to easily read, write, update, and delete live data - just like working with SQL server.