There was a time when browsing a library required visiting a centralized catalog of books in an oversized collection of drawers. This way, readers could quickly locate the text in the genre or style they wished by author or title. Modern businesses are the same. They require just as much direct access to critical data in an organized manner so that all their BI tools and data requests can be optimized in a timely manner. We collect so much information of varying types that without a data catalog, we risk losing critical insight into the overall constructs of an enterprise’s data landscape.
To get the most value from the data you collect, you need reliable data catalogs that will create efficiencies across your organization by deciphering different information based on the predetermined metadata factors you outline. For example. if you have consumer data from one geographic area of your target market, it won’t be mixed in with data from another site requiring different marketing or advertising.
What is a Data Catalog?
The need to organize data is only accelerating. As more automated AI tools become available at cost-effective prices, businesses of every size are collecting all kinds of user, market, internal, and trending data that must be organized effectively to be of any value. Without the proper metadata to inventory what is coming in, it is really difficult to monetize or ensure information is appropriately maintained to your industry’s regulations.
A data catalog is a good way to logically organize different datasets. This is by maintaining an inventory of your data assets and providing context so that your data tools, scientists, stewards, and other critical interested parties can best utilize, find, and create value from data dispersed across and beyond your enterprise
A quality data catalog goes further by not only giving stakeholders context or helping them discover where to locate different data, but also automating metadata management. This improves collaboration because everyone is essentially “on the same page” when identifying and organizing any data collected.
Again, we can rely on our library’s example. If you have a book, you are looking for, you need reference points like the author, date of publication, title, or other critical attributes to locate that book and get the knowledge you seek. Data catalog implementation is much the same. You need associated metadata to retrieve crucial information about processes, marketing results, customers, market trends, and performance issues within your business.
With a robust data catalog, you can link different assets by documentation, general queries, glossaries, historical data, and other metadata attributes. This creates a repository of all the information you have collected from various tools in an easy-to-understand structure that can then be leveraged through analytics.
What are the Differences Between a Data Dictionary, Business Glossary, and a Data Catalog?
Even though all three of these terms seem similar, they offer differences in what benefits they provide and how they are used in practice.
Data Dictionary:
A data dictionary is the technical description of data elements often used as a system catalog or database for IT departments and engineering teams. These are used to understand the physical data assets. It is common to see multiple dictionaries in use that focus on a system or a database. These are maintained or owned by IT teams, DBAs, or operation teams. Most often, these are presented in a spreadsheet format defining each attribute or metadata category needing to be addressed in a system.
Benefits include:
- Helps ensure master data management and data quality.
- Lowers the cost of data initiatives by saving time with predetermined definitions.
- Clarifies requirements for different IT teams working in collaboration.
Business Glossary:
The point of a business glossary is to provide definitions that offer clear and unified terminologies across an entire enterprise. This aids in driving consistency that begins with a line of business and eventually expands to the organization. These are owned and maintained by business teams, which are often updated via shared spaces like Wiki pages where authorized users can enter or improve definitions.
Benefits include:
- Low-cost solution to the general lexicon of an organization that improves collaboration.
- No need to invest in bespoke tech as everything can be maintained through a shared Google Sheet or Wiki space.
- Excellent tool for onboarding temporary or new team members.
Data Catalog:
A data catalog brings data dictionaries and business glossaries together, as well as other curated metadata. It is the unifying, one-stop-shop to organize all data being used, managed, or understood.
While IT is the primary team maintaining a data catalog, having both business and IT collaborate in ownership is beneficial. Common commercial data catalog tools such as Alation and Collibra provide functions to address data search and discovery across the enteprise data. Alternative approaches include leveraging service platforms that help with personalized data catalog usage across the enteprise that may reduce total cost of ownership. Gartner group recently categorized solution providers who deliver services led solution as Serware providers. See reference to Read this informative article from Gartner Data and Analytics Essentials: DataOps – https://www.gartner.com/en/documents/4001505
Benefits include:
- Improves regulatory compliance by directing access and searches to precious data locations.
- Enhances an organization’s trust in data reliance and self-service by giving users exactly what they want with transparency and accuracy.
How Does this Apply to Metadata Management?
Data management, in general, has become more challenging due to the massive amounts being collected across data lakes, self-service, and other tools. However, you need data about data to efficiently manage where it is going, how it is used, and in the case of data catalogs, how it is organized for quick access.
This is done through metadata management. When the entire organization agrees on how best to define data assets, a data catalog can use this metadata to automatically crawl, identify, inventory, and classify assets across various sources.
This makes metadata the foundation of a data catalog. It allows a business to expand on collecting and organizing new data related to searches, datasets, processes, and people. This grows what can be gathered and interpreted by modern tools accessing the different data all because a data catalog has been further developed with more descriptive and detailed metadata.
Data Catalog Use Cases
Data catalogs speed up the access to quality and accurate data assets across an enterprise. This improves access and collaboration by leveraging custom metadata or organization information into easy-to-understand categories and attributes that team members, stakeholders, tools, and others can utilize. That includes improving:
- Self-Service Analytics - An integrated data catalog acts as the traffic director for data by quickly shuffling new data into the correct destinations based on metadata. This helps those users’ running searches or implementing tools find the most relevant data needed in a given situation.
- Improved Regulatory Compliance – Data catalogs include reference metadata outlining the provenance of data sources and the flow of different collected information. This helps ensure the correct data is being viewed by verified users and allows organizations to meet the challenges of ever-increasing government and industry regulations.
- Elevate Data Governance – Data catalogs connect business glossaries with metadata to create taxonomies of scale within an enterprise. This allows outdated spreadsheets scattered around a company to be integrated into a data catalog to improve its function and automation so it can clarify data assets that help build user trust by establishing how those assets are related to the enterprise.
The Power of Metadata through a Data Catalog
Data catalog implementation allows for a centralized cockpit where all data assets can be identified, organized, and classified automatically from whatever sources of collection your organization utilizes. The quicker this data can be accessed and trusted by your users, the more agile your business will be. With robust metadata as guidance, a data catalog is essential to improving your data reliance.
To learn more about how a data catalog can improve your business operations, contact our exceptional team at NextPhase. We have years of experience implementing powerful data management tools that enable your decision-making and allow for valuable insights into the future of your business. Contact us today, and let’s get started building a solution for your specific organization!
Source: https://www.nextphase.ai/blogs/why-is-data-catalog-the-need-of-the-hour-for-organizations/
