With more companies expanding their digital horizons, there’s a greater push to capitalize on the data sources at their fingertips. This allows businesses and customers alike to get in on the benefits of more efficient processes regardless of the dataset or the business decision presented.
One of the methods that companies are turning towards is the use of data catalogs to gain new insight into what their organization needs, and what their consumers want. Let’s take a look at what goes into this kind of data management.
How Data Catalogs Work
You might be asking yourself, what is a data catalog? It’s an inventory of a company’s data assets so users can find the information they need fast. Catalogs consist of mostly metadata with basic information, combined with data management and search tools to form a catalog. Data catalog implementation can make a big difference in the speed and quality of data analysis because it helps users find the information they need in real-time.
A data catalog can give users all the right sources in a standardized format. This assures that all the information you have as a company is held in a multi-cloud context that is immediately consumable regardless of the data type.
Beyond offering context to data analysts, data catalogs make it possible to automate metadata management. This automation allows the data catalog to become a single trusted source, collaborative for stakeholders to curate and harvest data as needed.
Catalogs are commonly considered to be a library for datasets. They stock up on assets, requiring a system to organize said information to assure proper data analytics. Regardless of the business purposes, those with access to these data catalogs can curate their search to what they’re seeking and find the information they need based on relevance.
Business Needs for Data Catalogs
With an ever-expanding field of data strategy, a data catalog is a great modern technology that allows businesses to deal with large amounts of data that are only growing in size by the day. An organization’s data assets must be understood to make the most out of any analytics program. Data catalogs are able to store this information through multiple cloud providers. The data quality may wane, which is why a catalog is a key step in developing structure in a logical and resourceful manner.
From data scientists to developers to business users, a transparent procedure for curation has allowed for users to spot data quality issues with greater expedience, preventing any hurdles and taking less time to make business-related decisions.
Users collaborate remotely on the data as they access the metadata alongside actual data. This ensures that the information is accurate and consistent by updating itself automatically. Data catalogs help to access the lineage of the data and view detailed datasets in a secure manner.
Key Factors of a Data Catalog
There are several ways to create a data catalog, but there are factors at play to ensure the successful implementation of a system. Connectors are needed to map the physical datasets in your database, helping to curate this information with proper validation and certification techniques. This paves the way for sustainable data governance for engineers to monitor regularly. The presence of automation for data catalogs allows data users to focus on crucial processes like validation to expedite analytics and capitalize on relevant datasets.
Search is a primary component of a data catalog, making it easier for business users to conduct quick look-ups for the information they need. It’s important that data preparation pays close attention to the lineage and lifecycle of data being put into a platform, allowing users to understand the difference between various data sources. This glossary of data sets makes for easier profiling of this information to understand their key capabilities and how it can advance your business from execs right to the consumer.