Without knowing where your data has come from, or how it passes through your systems, you’ll never truly understand your data governance framework and what insights it holds. That’s why ensuring data lineage is crucial for your business; it offers complete transparency and a foundation for informed change.
Data Lineage describes data origins, movements, characteristics, and quality of data. It's important to understand this data journey so that you can maintain transparency over your data. Data Lineage typically describes where Big Data begins, and how it is changed when presented in its final outcome.
Specifically, data lineage helps you:
However, as much as these benefits are enticing enough to get you started, you’ll first have to navigate the challenges of data lineage.
With regulators needing to know how your sensitive data is being handled throughout its lifecycle, it’s never been more important to track your data lineage.
But, for businesses who don’t yet have a data lineage process in place, it can be difficult to know where to start. Especially when you have thousands of data sources and integrations, isolated data sets and an outdated, manual data management process. However, without overcoming these challenges, you run the risk of facing further problems that’ll only cost your data teams more time and money.
To achieve better transparency, your organization should plan a strategic, step-by-step data lineage approach.
Fortunately, with the right planning, there are many ways to overcome your data lineage challenges:
By creating a data lineage roadmap and covering all your bases, you’ll be able to piece together your data flows efficiently.
Manually creating data lineage flows is a difficult task. The effort it takes to discover your data, let alone assemble it, can be overwhelming for businesses without the time or expertise.
To help ease the process:
A good data lineage process aligns your integrations and allows you to find valuable insights amongst all the noise. However, with the large scale of integrations and sources your organization manages, it’s tricky to map out your workflows.
By following a strategic approach, determining goals, listing processes, assigning responsibilities, and documenting your practices, your data lineage process will stand in better stead. And, by using modern approaches such as data models, you’ll streamline the process, too.
So, are you ready to piece together your data lineage puzzle? If you’d like more advice, please get in touch.