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Data Catalogs – Introduction, Challenges, Business, And More


Data Catalogs Definition And Analogy Of The Data Catalog We previously provided a brief definition of the data catalog as an element that uses metadata to help organizations manage their data. But now, we will extend it with the analogy of a library.

When we go to a library and need to find a book, we use the catalog to find out if they have it, what edition they have, where it is located, a description, etc.; that is to say, everything you need to decide if you want it and to search for it in your case.

Challenges That Can Address With A Data Catalogs

Challenges That Can Address With A Data Catalogs

Unfortunately, finding the correct data and accessing it is not without its challenges. Finding the right data has become more challenging than ever as available data increases. On the other hand, there are also more rules and regulations than ever; GDPR is just one of them. So the only challenge is no longer the data but also its governance.

It is essential to know what kind of data you have, who manages it, and how it should protect. But you should also avoid too many layers and wrappers around your data, as they become useless if they become too difficult to use.

  • Waste of time and effort searching for data and accessing it.
  • Data lakes that become data swamps.
  • The absence of a shared commercial vocabulary.
  • The difficulty of understanding “dark data” structure and variety.
  • The difficulty of evaluating provenance, quality, and reliability.
  • The inability to capture tribal or missing knowledge.
  • The difficulty of reusing data and knowledge assets.
  • Manual and ad-hoc data preparation efforts.

Business Needs A Data Catalogs

Business data grows tremendously every day. The global data sphere is expected to expand from 33 Zettabytes (ZB) in 2018 to 175 ZB. Data at this scale is challenging to manage and navigate. Data can be stored across multiple cloud providers, in different formats, with varying storage technologies. And Data quality could degrade over time, as data has a lifetime and data sets constantly change (adding new data sets, getting new data sets from existing data sets, etc.).

It also has different types of users, from data scientists to developers to business users. Each of them has additional requirements and skillsets for data. You can’t always depend on IT to create a new solution every time a business user needs to solve a business problem, so you need a way to manage these issues.

A data catalog is crucial in structuring the data 1logically and witty. It can turn out to be an essential asset for an organization, as it has the following advantages:

  • A source can bend for the data, including information about the data’s quality, structure, usage, and statistics.
  • Users collaborate remotely on data as they access metadata alongside the actual data.
  • Ensure data is accurate and consistent across the atmosphere by updating automatically and frequently
  • You can access data lineage and view information such as data source, modifications, and accesses.
  • Data assets can be securely shared with stakeholders.

Essential Factors Of A Data Catalogs

A data catalog can be created in various ways, but the following factors are necessary to implement an efficient data catalog successfully.

Connectors And Conservation Tools

A data catalog serves as a single, trusted place for data. Since metadata can collect from multiple sources, such as Salesforce, SQL queries, and Business Intelligence data integration tools, it is vital to preserve this data. Connectors map the physical data sets in your database; therefore, it is crucial to have a wide range of connectors to strengthen the data catalog. Validation and certification are essential processes that improve the efficiency of a data catalog and make data governance a sustainable operation.


Automation in data catalogs allows data users to focus on critical processes like validating and correcting it issues, which will improve data catalog speed and agility and enrich it sets within the organization.

Efficient Search Options

Search is the main component of a data catalog. A powerful search capability will offer users a wide range of selection options. Therefore, it is vital to have several parameters to perform advanced searches at once.

Lineage Or Life Cycle Tracking

Lineage offers a glimpse into the life cycle of the data displayed. It will also help you understand the difference between various data sources and types in your organization. In case of discrepancies, data users will be able to use the data catalog to easily trace the lineage to locate the problem and correct it.

Universal Glossary and Data Dictionary

An organization’s data is a large part of its value, so it should be accessible and easy to understand for all stakeholders. Typically, a data catalog comprises a data dictionary and a glossary. The data dictionary is a collection of all the metadata (typically stored in tables) about the data in your catalog, including meaning, relationships to other data, origin, usage, and format. The glossary allows members of the organization to identify the business terms used in the catalog and use them in the same way throughout the company.

Also Read: What Are Navigation Routes?

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