{"id":4962,"date":"2023-01-24T13:32:45","date_gmt":"2023-01-24T18:32:45","guid":{"rendered":"https:\/\/solutionsreview.com\/data-management\/?p=4962"},"modified":"2023-02-09T16:58:51","modified_gmt":"2023-02-09T21:58:51","slug":"business-lineage-vs-technical-lineage-whats-the-difference","status":"publish","type":"post","link":"https:\/\/solutionsreview.com\/data-management\/business-lineage-vs-technical-lineage-whats-the-difference\/","title":{"rendered":"Business Lineage vs. Technical Lineage; What’s the Difference?"},"content":{"rendered":"

\"Business<\/p>\n

Solutions Review\u2019s Expert Insights Series is a collection of contributed articles written by industry experts in enterprise software categories. In this feature, data.world<\/a> Co-founder and Chief Product Officer Jon Loyens asks and answers the question: “Business lineage vs. technical lineage; what’s the difference?”<\/strong><\/i><\/p>\n

\"ExpertAsk a random sample of people working in data governance to explain data lineage, and you\u2019ll get an answer along the lines of, \u201clineage shows where data comes from, how it\u2019s been changed, and where it goes.\u201d

In a broad sense, this is true. But explanations from people in your random sample might vary, because the specific definition and makeup of lineage varies depending on the use case.<\/p>\n

Is lineage a map of your data and analytics, a graph of nodes and edges that describes \u2014 and sometimes visually shows \u2014 the journey your data takes, from start to finish, from raw source data, to transformed data, to compute metrics and everything in between?<\/p>\n

Or is it the path from a specific metric, backward to what defines that metric, to the part of your enterprise to which it\u2019s related, to who owns it, to the tables, pipelines, and processes that compute it?

The truth is, data lineage means all those things. Here, I\u2019ll explore the difference between and uses for two frequently used \u2014 and frequently confused \u2014 types of lineage: business lineage and technical lineage.<\/p>\n

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Business Lineage vs. Technical Lineage<\/b><\/h2>\n
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Data lineage delivers a top-down picture of your data and analytics ecosystem. It provides clear visibility into where your data is coming from, where it\u2019s going, and how it\u2019s been changed.<\/p>\n

Lineage can also be thought of as the \u201cprovenance\u201d of the data, with\u00a0\u201cprovenance\u201d\u00a0<\/a>defined as, \u201cthe beginning of something’s existence; something’s origin\u201d or \u201ca record of ownership of a work of art or an antique, used as a guide to authenticity or quality.\u201d Both definitions of provenance apply to data lineage.<\/p>\n

When creating lineage metadata, there are several great open standards you can adopt (One of these is OpenLineage<\/a>, which represents the technical provenance of data, and the systems and processes that move and transform the data into something usable for analysis and data science work). These standards are great if you\u2019re considering only the first definition of provenance. But what if you\u2019re trying to drive trust and understanding along with specifying custody?<\/p>\n

Sometimes we need to be more expansive. For these more extensive lineage requirements, the best option is a standard from the Semantic and Linked Data community that can represent both technical and semantic ideas in a single graph. That standard is\u00a0PROV-O<\/a>, and it\u2019s particularly well-suited to building a representation of technical lineage and representing semantic and business concepts at the same time.<\/p>\n

While both of the most commonly used types of lineage help users understand their data\u2019s origin, and build understanding and trust for its authenticity, veracity, and context, each is designed to serve a different audience:<\/p>\n