How Data Lineage Fills the Business Knowledge Gap in Your Data Catalog

Franco PrimavesiJune 23, 2020

Building a data catalog to make massive quantities of data available to a company’s workforce is more important now than ever before due to growth in datasets. Serving as a central repository, data catalogs enable IT teams to easily uncover data lineage, find data’s meaning, uncover bad practices, manage policies and more. And having this single source of truth with an uptick in remote employees ensures that data users can trust their data.

While IT teams assemble data catalogs to document data’s technical meaning and location, trouble abounds when business users also want to utilize their organization’s data catalog to identify and understand what data assets are available.

The trouble is that business users are not as technical as IT teams, and require a business-oriented data catalog that bridges the knowledge gap between business and technical users. This type of business-oriented data catalog details the organization’s data assets, across multiple data dictionaries, into a simple, easy to digest format. Think of this as the difference between the back-end of a coded website vs what a user sees when they visit the URL.

Creating an effective data catalog starts with mastering data management, an often difficult task because of the deluge of data entering an organization from various sources, systems and processes. But equipping business users with trustworthy, detailed business data enable companies to deliver reliable, understandable, easy-to-find business data to data users.

To begin the complex undertaking of data management and delivering business context and meaning around an enterprise data catalog, organizations must prioritize data lineage. This is the identification of data’s origin, where it moves over time and how it exits the organization. Ultimately, capitalizing on automated data lineage is your “golden ticket.”

The Key Role Data Lineage Plays in Building a Business-Friendly Data Catalog

Developing the right data catalog provides a comprehensive and detailed inventory of all enterprise data assets, including business knowledge, policies, objectives, data quality scores, metrics, governance processes, standards, rules, glossaries and a comprehensive technical and business view of an organization’s data lineage.

Data lineage traces the movement of data through different systems, from multiple extractions and ingestion points, through any transformations to its final consumption.

By including in a data catalog technical and business views of data lineage, companies can document data procedures, processes, etc.

For example, IT resources can identify regulated information, control data access, examine procedures, quickly search the entire data catalog and determine the upstream and downstream impact of changes to systems and processes that move or contain data.

In contrast, business users want their data catalog to produce accurate business intelligence that quickly answers questions about data, provides data’s origins and its route to its destination, uncovers detailed business knowledge, develops reliable analytical models, and applies business intelligence speeding up time to insights.

Business users also need a business view of data lineage to trace data errors and ensure they have accurate information they can trust that produces impactful business insights. After all, it’s business users who present data to board members!

By utilizing lineage to establish a data catalog for both business and technical users, companies accelerate productivity, reduce costs and improve collaboration.

Still, automation plays an integral role in providing business context around enterprise data assets.

Automating Lineage to Establish a Single Source of Knowledge 

Ultimately, a modern data catalog should be a single source of business and technical knowledge that provides a full 360-degree view of all enterprise data. Data lineage confirms to data users that their data is coming from a trusted and valid source. Integrating data governance ensures that hand-offs between systems can be trusted, policies and procedures are trusted and the workflow has been documented.

Taking this idea further, to make a modern data catalog a reality, organizations require an integrated data intelligence platform with unified capabilities for data governance, data quality, analytics and automated metadata and data lineage ingestion.

The platform automatically profiles and discovers patterns and descriptors about data. It can infer lineage and relationships with business assets, immediately uncover business context, identify data quality scores, measure knowledge impact and bring the information directly into the catalog.

With a browsable, curated, business intuitive data catalog, companies provide an extensive, centralized source of knowledge of all enterprise data. Business users also immediately derive value from data assets, with greater precision and speed.

Are you looking for more information on automated lineage, business knowledge and data catalogs? Check out the webinar above or below for more information!

For additional resources on data lineage, check out this definition from Techopedia https://www.techopedia.com/definition/28040/data-lineage.

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