An all-too typical data scenario we’ve all likely experienced:
A business user searches their enterprise data catalog to discover a dataset they think is valuable. However, they aren’t sure where the data came from, if they can use it or if it is accurate. The user digs deeper into the data catalog looking for data’s meaning and usage. They are also curious to know if there are any data quality metrics to understand if it’s trustworthy—after all, they want to extract insights for reliable decision-making. But the catalog only contains information on data’s location and technical meaning. Because the data catalog lacks business context, automated data lineage is needed to connect the dots.
Automated data lineage systematically ingests metadata and curates it to deliver business knowledge to the data catalog.
Only achieving a partial view into data meaning leaves other significant information for interpretation and potentially bad decision making. Enabling automated data lineage as part of a data catalog provides all data users insight into their data’s source and its route through processes and systems. The two functions that should be included are technical and business data lineage.
Two Functions of Data Lineage Needed to Achieve 100% Information
Technical data lineage monitors all the elements critical to compliance and operations, including procedures, transformations and data combinations. Technical lineage identifies where sensitive data elements live, their source, how they change, quality levels, who has access and how they’re shared. These key details help ensure regulatory compliance and protect data quality.
Technical data lineage does not address data understanding among business users or provide business context around data. To address this gap, companies must incorporate automated business data lineage into their data catalog.
Business data lineage provides visibility into the data management pipeline. Transparency into the data landscape empowers business users to trace data errors back to their source. It also ensures business users understand their data and have accurate information that generates meaningful business intelligence. This information is critical for business users who need to know how data fits the business and its impact if altered or consumed.
Automated Data Lineage is The Key to a Business Ready Data Catalog
While both aspects of lineage are critical, business lineage can take the data catalog to the next level. By capitalizing on automated data lineage, companies can provide thorough and precise business knowledge around enterprise data assets. With detailed business expertise in a data catalog, companies can cultivate insights for smarter decisions and sustain a competitive edge.
Automated data lineage ingestion capabilities automatically profile and discover data patterns, signatures and descriptors. This information empowers users to document lineage and uncover relationships with business assets, delivering business expertise around the meaning of data. Data users quickly uncover data’s business meaning, learn how data impacts the company and connects data assets to business outcomes and use cases.
By equipping business users with a business intuitive, single source of data knowledge, organizations also eliminate the knowledge gap business users face searching their data catalog. This is especially critical as organizations work with a remote workforce that doesn’t have the luxury of speaking quickly in one’s cubicle or walking down the hall to a colleagues desk to ask a data questions.
How a Business Ready Data Catalog Improves Business
Automated data lineage capabilities redefine the data catalog by enabling data users to fully grasp the dependencies and flow of their data.
For instance, by automatically providing both a comprehensive technical and business view of data lineage, organizations offer a detailed catalog of data assets, knowledge, policies, objectives, metrics, data governance processes, standards, rules and glossaries. Thus, every data user is on the same page, which helps businesses dramatically improve efficiency, streamline workflows and accelerate productivity.
In addition, by including end-to-end automated data lineage, data quality and data knowledge across all data siloes and data systems in a single data catalog, business users can easily access, search and use trustworthy data for all types of business decisions.
Automated data lineage capabilities enable self-service usage without needing to understand coding languages to find valuable information. With a browsable, curated repository of data assets and knowledge, organizations derive business-ready data, with greater precision and speed while having absolute confidence in data quality around analytical models.
Are you looking for additional information about data governance? Check out this press release, above or below, for more detailed information.
For additional information about data lineage and data understanding, check out this article from Inside Big Data: https://insidebigdata.com/2016/11/13/data-lineage-the-key-to-understanding-your-data-landscape/.
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