Dec 2022 | Data Quality |

As a marketing or data professional, you may be familiar with the term “data profiling”. It is the process of examining a dataset to glean information about its contents. This can include statistics about the distribution of values, patterns within the data, unusual values or outliers, and in-depth analysis of its accuracy, or quality.

Data profiling can be used to get a better understanding of your data, identify potential issues, and make sure that your data is clean and ready for analysis, or use. In this article, we’ll take a closer look at data profiling and examine some of the common use cases where it is most useful.

Why profile your data?

Before we explore some of the common use cases for data profiling, we’re going to look at the reasons why it can be so beneficial:

  1. Boost accuracy and quality – by the very nature of the processes you undertake when profiling your data you will spot inaccuracies and inconsistencies very quickly. Putting plans in place to fix these errors and long-term plans to prevent the same issue in the future will help you protect the value of your data assets.
  2. Improve decision making – in the same way that Data Profiling can help you spot data inaccuracies, it can also ensure that your core data assets provide more reliable results when used for forecasting or planning. The old adage of “rubbish in / rubbish out” still holds very true and you want to give your organisation the best chance to make the right decisions the first time round.
  3. Understand your data assets – it is extremely common for large and complex organisations to not even fully understand their data landscape. Multiple territories and varying legacy systems that store data lead to data living in silos with varying levels of quality. A Data Quality audit helps you understand what data your organisation holds and how it could be handled going forward (Read our article on the relationship between Master Data Management and Data Quality  for more information on managing large data assets).
Common use cases for Data Profiling

Below, we discuss some of the use cases where Data Profiling offers the most value:

  1. Customer segmentation is an excellent use case for data profiling and something that every organisation should undertake. By segmenting your customer data effectively and building a single customer view you unlock a wealth of insights, such as, who is most likely to purchase your products, where you should put physical store locations, and what marketing channels will be most effective to grow your sales.
  2. Data Migration is a complicated and time consuming process, but one that is essential for large organisations to be proficient at. A common mistake is for organisations to rush the investigatory phase of their migration, shifting to data movement before a true understanding of the data is present. Data Profiling is a crucial stepping stone in the migration process so that you know with supreme clarity what data you have, what will be moving, and where to.
  3. Data Governance is the key to sustainably unlocking the full value of the data you own – so that it can underpin your data strategy, not just today, but on a long-term basis.
Talk to Experian about profiling your data

Experian has a range of tools and services to help you profile your data.

From our award-winning consumer segmentation platform, Mosaic, to our intelligent, self-service data quality and enrichment platform, Aperture Data Studio, we can provide you with all the tools you need to understand and utilise your data assets.

To get started enquire about our bespoke data quality report. This report delves into the state of your data and gives you actionable insights that you can use to build a robust data quality strategy.

Get in touch with the Experian team today to find out more.


Contact Us

By providing your personal information you agree that we may collect and process it in accordance with our Privacy Statement.