April 12, 2022 4 MIN by Samantha Higgins

Understanding Data Lineage in 2022
Data and data bases Reporting and data analysis

In this article

Data lineage tracks the journey of data from its source to its destination. It helps business to make informed decisions and spot potential issues. Let’s discover various techniques implement data lineage, each with its own pros and cons.

How can you make correct decisions involving data? This is a question you might be asking yourself every day. You no longer have to worry about this because data lineage is the answer. It enables individuals to visualize, record, and analyze data.

For data lineage to be successful, it is vital to ensure that you use suitable techniques. You should also be aware of the source of this data. This process is achievable today due to modern technological advancements.

Several details will help you to understand data lineage in 2022.

Benefits of Data Lineage

It Allows Businesses to Track Data

Data traceability can take business ventures countless hours. In criteria where traceability is wrong, the business will suffer dire consequences. These consequences include penalties and fines. Traceability is crucial as it allows businesses to adhere to regulations.

Courtesy of data lineage, organizations can track data flow from various sources. Lineage tracks data as it flows via different systems as well. Therefore, it is easier for businesses to conduct risk management with data lineage.

It Enables Businesses to Understand and Trust Data

Data lineage in businesses allows a better comprehension of data. It highlights various aspects of data, including the source and destination of the data. Also, it shows various systems that data passes through before reaching its destination.

Data lineage shows how the data is built and the transformations it has gone through over time. This information is crucial as it gives business insights into various aspects. Therefore, the business can determine if its data is trustworthy and accurate. Data lineage allows business ventures to make well-informed data decisions involving data.

It Allows Businesses to Identify Downstream System Changes

The IT department in businesses can conduct data analysis using data lineage. Through this analysis, the business can identify any change in downstream systems. These changes usually arise when there is a change in data.

Failure to identify these changes causes the enterprise to face tremendous losses. Data lineage is instrumental because it saves the IT team time by eliminating manual analysis.

It Allows Strategic Data Reliance in Business

If you want to run your business successfully, you must have reliable data. All businesses, including sales, management, and manufacturing, rely on data. The information a business collects during research improves organizational systems.

Improving organization systems enables the business to provide top-notch services and products. Data lineage provides detailed information that the business needs to understand data validity.

What Are the Techniques of Data Lineage?

Lineage by Parsing

Lineage by Parsing is an advanced form of data lineage techniques. This technique relies on using logic to read processed data. With this technique, you can reverse engineer data transformation logic.

It enables the achievement of end-to-end tracing. The technique is complex because it uses all tools and programming languages, allowing for the movement and transformation of data.

Pattern-Based Lineage

The technique is ideal because it eliminates the use of code in data transformation. It evaluates metadata for business reports, columns, and tables. Pattern-based lineage uses metadata to investigate lineage through identifying patterns.

For instance, this technique links two data sets with similar data values and names in a data lineage chart.

The pattern-based technique is preferable because it uses agnostic technology – this means that it monitors data only. Also, you can use this pattern in various database technologies such as Spark, MySQL, and Oracle. In situations where data processing logic is unclear, this technique might be inaccurate.

Lineage by Data Tagging

Data tagging involves tracking tags from start to finish. It would be best to have a dependable transformation tool that manages data movement for this method to work. The downside of this technique is that it is impossible to conduct a lineage of data that has not been generated by this tool. That is why lineage by data tagging is only applicable in closed data systems.

Self-Contained Lineage

Self-contained lineage is instrumental in organizations because it provides master data management. It provides processing logic and storage as well. Further, it stores data through every step. This technique is unique because it can provide data lineage without external tools. The downside of self-contained lineage is that it can only work within this environment.

Closing Thoughts

For the success of an enterprise today, accurate data-driven decisions are crucial. Nowadays, you can understand data using data lineage because of modern technology. There are several data lineage techniques that business ventures should consider.

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