Frustrated Over Data Disorganization? Why You Need a Data Catalog Now
Data contains the keys to managing your company’s most valuable assets. Businesses use data catalog tools to make crucial decisions, monitor systems, overcome challenges, solve problems and the list goes on. With the mountains of data and materials data users must sift through to find the information they need, it’s not surprising Gartner says that professionals spend 50% of their time searching for information and, on average, take 18 minutes to locate each document. And, when data is disorganized and spread across the organization, is becoming a bigger challenge every day.
So, if executives empower teams to discover, understand, govern and consume the data they need to make better decisions, how are they creating this data-driven culture?
Modern organizations are prioritizing data catalog tools front and center in their data management strategies and using them to drive revenue, higher profits and innovation.
A data catalog is an organized inventory of data assets that enables data consumers to locate, organize, access and evaluate data in a centralized location for insight-driving analysis more quickly and efficiently. By leveraging metadata, it helps organizations manage their data and understand where it came from.
Data catalogs are a requirement in today’s fast-moving and highly competitive enterprise environment, but why?
Metadata is essentially data about data. Metadata is particularly powerful in serving up data that may not have initially been included in a data consumer’s search. Still, it could be relevant, allowing for deeper, more informed data analysis. A data catalog allows users to access metadata alongside data by connecting to and extracting metadata from multiple sources, databases and solutions. Integrating automated metadata and understanding data relationships across their enterprise allows organizations to automatically profile and discover data patterns and descriptors not readily apparent.
Data catalogs enable self-service, allowing teams to easily leverage and understand their data without relying on IT support. Through automated data tagging, classification, and relationship mapping, data users can easily search the data catalog using keywords, filters or parameters to locate, access and understand the impact of data. Data discovery also provides real-time visibility into the data’s current state, such as how it is ingested, aggregated, and used. An automated data catalog will also document whether data is current, outdated or deprecated.
Data lineage represents data’s end-to-end movement across an enterprise and provides an audit trail throughout its lifecycle.
As part of the data catalog, organizations must track data lineage from different perspectives to know the source, the transformations applied, and who has been using it.
Technical data lineage represents detailed technical locations, such as database, field and column information, enabling technical users to understand physical locations of data. Business lineage provides users with clarity into the business context, including data definitions, synonyms and business attributes, helping users understand data’s relationships with other data sets as well as discovering the flow and dependencies of data. Process lineage provides business users data visualization across the business process to understand how data is leveraged in daily operations.
With a 3D view of technical, business and process lineage layered over each other, users can easily attach data assets to a wide array of business processes and use cases, establishing specific business contexts around each data set. As a result, business users immediately derive value from data assets from different views with absolute confidence.
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The connections between building a data catalog and data governance are undeniable. The over-arching data governance framework clarifies data owners, assigned policies and relationships, enabling data consumers to know who to go to with data questions. A data catalog shows the organization’s data assets and location, helping users better handle their data. If there are data questions, they know which data owner to contact for a resolution.
Data governance also provides an enterprise frame of reference that encourages teamwork and collaboration to synthesize the technical and business details surrounding an organization’s data assets across multiple data users in different departments. Breaking down data silos and creating accessible data catalogs allow non-technical data users to locate and utilize data across the enterprise.
A data catalog integrated with data governance starts by automating the discovery of data sources across an enterprise’s systems. Data lineage that includes business, technical and process lineage—a 3D view of lineage—provides complete data transparency, so users understand data’s origins, flow and dependencies and where the data traveled from origination to completion and consumption. As a result, users quickly uncover the impacts of data, where it fits into organizational processes and make more informed data decisions.
Additionally, a complete data governance solution must include end-to-end data quality monitoring, policy management and data access methods to manage any usage restrictions. The right solution will democratize self-service user access to any data while eliminating cumbersome approval workflows and breaking down access silos.
While building a data catalog starts with harvesting and organizing critical data assets, a solution that incorporates data governance, data quality and analytics support offers a best in class solution that helps organizations streamline data efforts to deliver valuable, trustworthy data across the enterprise.
Users can feel confident their data has optimal integrity and if there is another resource available, or more up-to-date assets, they know who owns it, where it’s located and how it was processed. They can, most of all, increase speed and efficiency to drive strategic insights and gain a competitive edge in a secure, compliant environment.
Now the question remains, do you understand your data, where it came from or have a repository for your data’s structure, quality and usage? If not, you need a data catalog now. Read our eBook
To learn more about the basics of what a data catalog tools are, how it works and what business challenges it can help solve, read our eBook Looking for a Data Catalog?