In today’s dynamic world, there are several details an organization needs to be aware of. While many businesses understand the importance of keeping data fresh and meaningful in the era of digital transformation, only a few of them realize that in order to keep up the pace it is also crucial to managing their data lineage.
Many businesses, in their rush to modernize with technology, have assimilated multiple systems with multiple data entry points and transformation rules for data as it moves across the enterprise. If the systems are integrated especially with all these data sources it can be challenging to understand the complex data web they form and getting a simple visual flow may become impossible. That’s why data lineage needs to be tracked. It is crucial for business operations as it can enable them to understand where the data came from, how it is transformed, and in what ways it moves into, laterally and outside the enterprise.
It is increasingly becoming essential for businesses to find new methods of managing the constant flow of data that they receive. According to the IDC, the amount of the newly created data was to see a 44X growth from 2010 to reach 35 zettabytes in 2020. But, in 2018, it was already at 33 zettabytes, because of which the IDC to predict that 175 zettabytes of new data will be created in 2025.
Hence, managing data lineage has become more critical than ever. With data lineage, businesses can track the path of data, and make crucial decisions to improve cost-effectiveness and the efficiency of their business strategies.
Data Lineage Benefits
Let’s take a look at the top three data lineage benefits for businesses across industries all over the world:
Data is important for the survival of every organization. Therefore, it is crucial for businesses to think about the flow of data over multiple systems that help in organizational decision-making.
Businesses must have a grasp on where the data originates from, who all use it, and how it transforms. Moreover, in case of a change in data expectations, data lineage can provide a way to analyze which downstream processes and applications are impacted by the change and this can help plan for application updates.
A good data lineage in place can help organizations verify if the data used by consumers is from authoritative and trusted sources with necessary controls in place to oversee the hand-offs between systems.
An automated data lineage solution can stitch together metadata for validating data usage, and alleviating the risks associated with it. It can also auto-document end-to-end downstream and upstream data lineage, and reveal any changes that were made, by whom, and at what time.
Policy Compliance and Data Pipeline Auditability
Data policies are implemented through the specification of business rules and compliance with these business rules can be tracked via data lineage by embedding auditability and validation controls across data pipelines. This can help generate alerts in case of any non-compliant data instances.
Regulatory compliance demands greater transparency from firms when it comes to auditing and tracing data. Moreover, the organizational stakeholders like the employees, customers, and auditors should be able to trust reported data. Data lineage offers visibility into data pipelines and information flows, and this can prove if the data provided is reflected accurately.