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Introduction to Azure Data Catalog

With the rise of self-service business intelligence tools, like Power BI, and an increased engagement with data in the workplace, people’s expectations of where they can find expert information about data has changed. Where previously there would an expert that people would have to book time with in order to understand data, now people expect to get quick and detailed information about the data assets that an enterprise holds and maintains without going through a single contact. With Azure Data Catalog, data consumers can quickly discover data assets and gain knowledge about the data from documentation, tags and glossary terms from the subject matter experts. This post aims to give a brief introduction to Azure Data Catalog and what it can broadly be used for.

What is Azure Data Catalog?

Azure Data Catalog is a fully managed Azure service which is an enterprise-wide metadata catalogue that enables data discovery. With Azure Data Catalog, you register; discover; annotate; and, for some sources, connect to data assets. Azure Data Catalog is designed to manage disparate information about data; to make it easy to find data assets, understand them, and connect to them. Any user (analyst, data scientist, or developer) can discover, understand, and consume data sources. Azure Data Catalog is a one-stop central shop for all users to contribute their knowledge and build a community and culture of data.

What can Azure Data Catalog be used for?

As mentioned in the earlier headings, Azure Data Catalog can be used for data asset management; data governance; and data discovery. For data asset management, this means knowing what data is available and where; for data governance teams, this means answering questions like: where is my customer data? or what does this data model look like?; for data discovery, this means knowing which data is suitable for particular reports and who you can go to if you have any questions. There are some common scenarios for using Azure Data Catalog that Microsoft has put together, and it’s well worth reading to get a fuller understanding of what Azure Data Catalog can be used for.




Data Source Permissions and On-Premises Data Gateway: SQL Server and Analysis Services

In Microsoft’s documentation surrounding the On-Premises Data Gateway, the advice on permissions for the account used to authenticate the Data Source in the Power BI Service can be concerning for most, especially DBAs.

In the Analysis Services section of the documentation, the advice is:

The Windows account you enter must have Server Administrator permissions for the instance you are connecting to. If this account’s password is set to expire, users could get a connection error if the password isn’t updated for the data source.

Server Administrator permissions…? What happened to the principle of least-privilege?

In a practical sense, the On-Premises Data Gateway has to deal with two very different implementations of Analysis Services: Multidimensional and Tabular. Each are setup and configured differently from the other, and the nature of their security models are also different. As a one size fits all approach, it works. As we will soon see, the permissions do not have to be set as Server Admin

The SQL section of the documentation, on the other hand, doesn’t actually specify what permissions are required for the Data Source to be established in the Power BI Service.

Permissions

Exactly what permissions are required for these common data sources, I hear you ask. As data sources are established at a database level, so too are the permissions set.

Data Source

Minimum Permissions Level

SQL Server Database

db_datareader

SSAS Tabular Database

Process database and Read

SSAS Multidimensional Database

Full control (Administrator)

Principle of least-permissions is now restored.

Though there still are the curious incidents of Analysis Services data sources requiring permissions in addition to read. I am unsure, I have my suspicions, and have tried to find out. If you know, please leave a comment below!