Dissecting The Need of Data Catalog: Top 5 Reasons

Technological advancement has given us the gift of big data. There is an abundance of data available in the Data Lake, data warehouses, master data directory, etc. It is always difficult to find Nemo in such a big ocean, with so many other fish in the sea. Similar is the case with data. It becomes difficult to find your Nemo-data when there’s so much other data available. But this problem has a solution- Creating a Data catalog.

What is a Data Catalog?

I’m sure you must have put your hands on a catalog at least once in your life. So you know what a catalog is like- it has a list of all the items present in stock, with a small description of it and arranged systematically. So, when you go to the store to purchase any of those items, you don’t have to go through the entire collection, nor does the storekeeper. You can just show them the item from the catalog and they can get it for you directly.

That is exactly what a data catalog does. In a data catalog, the list of the items is metadata, which gives information about a data set or other data. This metadata is then stored in a systematic manner to show the availability of data in the inventory. Just like Meta elements in HTML, giving additional information to the browser. It paves the way for the users to be able to serve themselves. You just need to search the metadata and you will be presented with the results of data that you can then analyze and evaluate.

Data cataloging not only makes things easier for the users but also creates value for them as well as the data. A good data catalog is the result of good data architecture. Think of it as a dashboard on your mobile phone, where you can see your notifications in one glance in real-time.

Now that you know what a data catalog is, Creating a data catalog is the next step.

But it is not as easy as it looks. It is easier. You just need to create a data catalog for your database or your data inventory. How will you do that? The data catalog product is the answer. There are many data catalog companies that provide these products. One such product is Alation. Alation is an application that provides you with a customized collaborative data catalog. How do you use it? All you have to do is connect your data sources to the application and it will use its algorithm to crawl and index all your data assets. It lets you collaborate and share knowledge base across the platform. Its interface is very user-friendly and doesn’t have you breaking your head over complicated SQL queries.

Let’s look at some of the data catalog examples

LinkedIn, eBay, Microsoft Azure, Salesforce, and many other companies have a data catalog for the data their company owns.

  • Azure’s data catalog allows its users to discover, understand, and consume the data. It has a central database that has the list of all the data sets and sources registered. Users can make use of this data with granted permissions and also allows producers to add, create, and manage data.
  • AWS also has a data catalog built to refer to the data. It connects all the data from various data stores and then that data is classified to form the population of the catalog. That classification is in the form of metadata which then forms a repository.

Why do you think it is important to catalog your data?

  • Semantic Integration – Data Catalog not only provides you with the visual representation of the movement of your data, but it also lets various stakeholders of your enterprise integrate necessary business definitions and meanings, element tags, frameworks and workflow models, and different embedding. It allows you to display how and where business terms are used and what they represent. It also shows the established relationships between different systems.
  • Accessibility –Data catalog allows you to give access to users and producers with safety, security, and ease.
  • Recency – Data catalog provides you with the most recent data in your data sources in the enterprise.
  • Expansive – Since the data is ever-growing and ever-expanding, the documentation of the metadata or datasets also increases. The data catalog allows you to do that without much hassle and will produce results when needed.