Data Catalog in Azure

Dec 20
3 minutes

What is Data Catalog?

A data catalog is an organized inventory of data assets such as databases, documents, videos, photos, presentations, spreadsheets, dashboards, and others that include data necessary to an organization's value chain. A data catalog uses metadata to help organizations manage their data. Metadata is information about data or collection of information such as the author, file size, document creation date, and keywords to characterize the document. Data catalog also enables data professionals to collect, organize, access, and enrich metadata to support data discovery and governance.

When you need a shirt, you go to the local store and look for it. It's challenging to find the perfect garment in a single store, so you start looking in other stores in the vicinity. What if you could search for it across the entire city, or maybe the whole country or the whole world? This is where e-commerce sites such as Amazon and Walmart come in. Consider what it would be like if a data engineer could find the perfect data for his needs through a single interface. This is referred to as a data catalog. The data catalog entry for each data asset provides definitions, descriptions, ratings, data owner, and more, making it easy to search for and find the data you need for any given purpose.

Data Catalog Use Cases

As data assists in making better decisions, solving problems, understanding performance, improving procedures, and understanding customers, data is becoming more critical in the industry. The data catalog may be used to maintain such assets in various structured ways. Here are a few examples.

  1. Self-service analytics: A standard dataset file may contain many fields, and it may be difficult for a BI user to understand all of those. It is necessary to better understand the business context surrounding it.

  1. Data change management: Data users frequently want to know where the data is coming from and how it flows through the company. With ever-increasing government rules around data, you often need to verify data provenance, changing how data behaves or is stored or assigned to in the organization.

  1. Cloud modernization: Businesses are speeding up their cloud migration. One difficulty is that many cloud providers have their own metadata management tools. As a result, many businesses are turning to data catalogs to increase data accessibility across on-premises, cloud, and hybrid systems.

Azure Purview

Purview is a popular Microsoft Azure data catalog solution. It is a unified data governance solution that helps manage and govern on-premises, multi-cloud, and software-as-a-service (SaaS) data. [2] It simplifies the finding of data assets. It is a fully managed service that allows registration, enriching, discovery, interpretation, and consuming data sources as an analyst, data scientist, or data developer.

Advantages of Azure Purview

  1. Create a unified map of data: Metadata from hybrid sources can be automated and managed. Additionally, users may classify and label data in SQL Server, Azure, Microsoft 365, and Power BI.

  1. Data discovery: Azure Purview makes it simple to search for and comprehend data using technical or business terminology.

  1. From raw data to business insights: Azure Purview makes it simple to scan the Power BI environment and publish all assets and lineage detected to the Azure Purview Data Map. Users can also connect Azure Purview to Azure Data Factory instances to collect data integration lineage automatically.

Disadvantages of Azure Purview

  1. Azure Purview currently only supports a limited number of data sources, mainly from Azure, and the vast majority of Azure data services are not yet available for scanning. Many prominent content management systems and BI business intelligence tools are not currently supported.

  1. One of its features is to classify data automatically, but It struggles to do on unstructured or semi-structured files in the data lake.

  1. Azure Purview's main selling point is its capacity to search databases, but it is severely constrained. It works fine with dataset names but not with acronyms or other dataset attributes. Suppose a government organization has “Sea Air Land” data, it might not work if you start searching the catalog with the acronym “SEAL” or using the dataset owner name.

  1. Lineage information is only available for data pipelines that have been connected with Azure Data Factory. There is no other method to establish a lineage.

  1. The linkage of asset ownership is simple and is based solely on Azure Active Directory IDs resulting in severely restricted access control and authorization.

To summarise, it appears that Microsoft is attempting to create an ecosystem by forcing consumers to use just Azure and other Microsoft products while offering limited support and flexibility to alternative tools.

Data Catalog by Datalogz

Datalogz is a free web platform that helps data science and analytics teams manage their data without costly IT procedures. This software is simple to use and can help you understand data quicker, generate new insights, and, most importantly, has the most intuitive data catalog on the market. Datalogz, unlike Azure Purview, can connect to a multitude of data sources and makes locating data as simple as a Google search. Datalogz makes it simple to identify and interpret data by collecting vast quantities of metadata using secure protocols. As a result, a business will not have a nightmare while looking at available data. There are various successful features, and frequent additions as Datalogz researches current industry needs and competitors to satisfy consumers.

Advantages of Datalogz

  1. Datalogz supports a large number of databases. Namely: Snowflake, Amazon Redshift, Google Big Query, IBM DS2, Oracle, MS SQL Server, MySQL, PostgreSQL, or just any CSV file. Datalogz becomes a lot more adaptable with this wide variety of integration capabilities.

  1. Datalogz is built on top of Lyft's Open Source Data Catalog Amundsen, which means it is ready to use, has improved collaboration, data governance, and the freedom to adjust to your needs.

  1. Datalogz makes it much easier to search for data by using metadata. Information such as data description, tags, owner/user names, data status (production-ready or under construction), and so on. All of this adds to the improved experience of the data catalog.

  1. Datalogz has the finest-in-class data lineage with a minimalistic design that is informative, making it easy for anybody to comprehend the data flow.

  1. Not only does Datalogz manage data, but it also integrates with major BI tools, including Power BI and Tableau. This makes dashboards, like any other data, easier to handle. In addition, it is possible to interact with NoSQL databases such as DynamoDB, Cassandra, and ScallaDB.

  1. The owner has complete authority over the data and BI dashboards. The owner has the option of granting edit, only-read, or limited rights.

  1. Datalogz distinguishes itself with features such as discussion boards and code templates. Within Datalogz, one may discuss specific data, and a code template will help you get started faster.

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