What is Cataloging of Data?
Cataloging your data is the process of creating an ordered inventory of your information. Once the data mapping procedure is complete, the data catalog (think of it as a card catalog in a library) is used to index where everything is stored.
It collects, tags, and stores datasets using metadata (a.k.a. data about your data). Your data may be kept in a data warehouse, a data lake, a master repository, or another type of storage. The majority of enterprise businesses opt for cloud storage for their data.
The greatest benefit of a well-organized data catalog is the insights it provides, now that your data is properly categorized and easily accessible. A data catalog enables you to view all available datasets, instantly identify what you’re looking for, and swiftly and confidently evaluate and analyze.
When done correctly, data cataloging provides visibility into all your data and a centralized source of truth for all your data stores. Essentially, if your business requires the analysis and utilization of an ever-growing reservoir of data, it requires a data catalog.
How do you Create a Data Catalog?
The initial step in cataloging data is to collect metadata, which includes tags, files, labels, and tables. That is the format in which your data catalog will be stored (it will not contain the actual data). You can configure the data cataloging software to crawl your databases for this information, which can come from data warehouses, cloud-based systems such as AWS, data storage platforms such as Hadoop, and other business intelligence solutions, as well as transactional databases that use SQL and NoSQL databases such as MongoDB.
Following that, you’ll create a data dictionary that will act as an index for quick identification and, eventually, retrieval. These have grown in popularity as the use of business intelligence tools such as Dataedo has increased.
Additionally, data analysts and business users recognize the significance of data dictionaries. These less technically savvy people value the ability to quickly assess the importance of a dataset without delving too far. The data catalog then provides context for what is in the dictionary through its enhanced automation, discovery, and classification capabilities.
The next stage is to adopt metadata management software, such as Dataedo, to enable more efficient data interaction. You may manage and expand your data catalog directly within the business intelligence platform.
What Purpose Does Data Cataloging Serve?
Proper data cataloging can assist your organization in easing the strain of data compliance and governance. You can configure data integration tools and labeling that pertain to personally identifiable information (PII), data privacy, and reporting. These may assist you in organizing and retrieving data in a manner that complies with HIPAA, Dodd-Frank, GDPR, and other important standards.
From an accuracy standpoint, data cataloging can assist you in locating the most current and relevant information by standardizing the way data is stored and labeled. You may establish a complete information system that even non-technical people can benefit from by creating clear and consistent definitions and properties.
Another advantage of data cataloging is that it enables you to improve and maintain data quality by assuring the consistent use of data items and promoting transparency. Your data catalog’s users must have confidence that they are not building models and reports with erroneous data.
Catalogs of data types
There is no such thing as a one-size-fits-all solution to data organization. Gartner classifies data catalogs into three main subcategories to help you identify which type is best for your business:
Catalogs of data for certain tools or vendors
These data catalogs may be included in a cloud-based data lake, data preparation tool, or Hadoop distribution. This solution takes minimal organizational effort, but has limitations, as you may wind up with many data catalogs as your vendor list develops. This complicates the process of integrating a business intelligence solution and establishing a single source of truth.
Catalogs of data devoted exclusively to data lakes
Data scientists and data engineers are the primary users of this form of the data catalog. While this type of use case is exhaustive, it is not easily adaptable throughout the enterprise and does not enable business users to easily access and exploit the data for their own digital projects.
Catalogs of enterprise data for study and collaboration
Gartner characterizes these as “generalist, business-oriented data catalogs aimed at the Chief Data Officer (CDO) for broader use in information governance and infonomics.”
Conclusion
A well-organized data catalog puts a clearer, faster, and more transparent analysis at your fingertips. Your data catalog should enable your staff to gain deeper insights into their data and make more informed decisions more rapidly. This will pave the road for your firm to become really data-driven.