What is your data story?

What about data?

In today’s post, we’ll start with the real, tangible value of the data that’s unique to your business. Data has become the currency of digital transformation. Whether it’s uncovering new insights, improving decision-making, or driving better outcomes, the push to unlock the power of data has never been stronger.

That’s exactly why data governance matters. Good governance helps ensure the data across your business is optimised for use—so teams can access trustworthy information, work across organisational boundaries, and generate deeper insights.

Over the years, working with different organisations, industries, and teams around the world, we’ve found that many clients get stuck on a few basic questions about their data. Since data is one of an organisation’s most important assets, it’s worth revisiting it:

• Who created the data?

• What information does it contain?

• Where is it stored?

• When was it created?

• Why does it exist?

To answer these, let’s start with a common industry term: data lineage.

Data lineage

Data lineage describes the lifecycle of data—from creation through processing and transformation to archiving. In practice, it’s about understanding, documenting, storing, and visualising how data moves and changes over time.

When you have a clear lineage, you gain a factual view of what happened to the data at every step. That makes it easier to:

• Trace and fix data quality issues

• Confirm the data comes from a reliable, stable source

• Validate that transformations were applied correctly

• Ensure data was loaded to the right target location

  
  

Here are some of the key questions that data lineage helps answer.

Who is using the data?

When analysing data, one of the first questions a data analyst asks is: who is using this data, and where?

With a data lineage view (often a lineage graph), it becomes much easier to track usage and understand which people, systems, or downstream reports rely on a specific dataset.

When was the data created or updated?

When data is created, key parameters and ownership details are usually defined.

The data owner is responsible for storing the data in the right place and granting appropriate access. Knowing who owns the data is critical: it clarifies who maintains it and who users should contact if something needs to be corrected.

What information does it contain?

Before defining access policies, you need a clear understanding of what information a dataset contains.

That helps with data classification, so you can apply the right policies and protect sensitive information appropriately.

How is it being used?

Within an organisation, data is used to generate reports that support decisions and drive growth. Those reports often rely on multiple datasets.

A data lineage diagram can show which datasets feed which reports. And if a report looks wrong, lineage can help you trace the issue back to the source.

Why is it stored or used?

A final (and often overlooked) question is: why does this data exist?

It matters because if a dataset is no longer needed, keeping it can waste time and money. Understanding what’s stored—and why—helps prevent unnecessary retention and reduces clutter and risk.

Data lineage valuation model

• Intrinsic Value: How complete, correct, and scarce is this data?

• Business Value: How relevant is this data for specific purposes?

• Economic Value: How does this data contribute to revenue, savings, or expenses?

• Performance Value: How does this data impact business outcomes?

• Cost Value: What did it cost to collect this data—or what would it cost the business if we lost it?

• Market Value: What could we gain by selling this data?