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5 Top Tips for your Data Cleansing Project

KEEPING YOUR DATA CLEAN

Georgina Adamson 4 minute read Data cleansing, Data quality

 

Today we live in a world where data is the foundation on which any profitable organisation is built. However without processes in place to keep data clean, insights and value cannot be extracted and fully utilised. Clean data is a must have for organisations today and data cleansing tools are available to ensure you get the most out of your data.

Here are 5 key things to consider when running a data cleansing project:

1. Know the current state of your data

If you don’t know what state your data is in, it is almost impossible to know the scope of what needs to be done and to be able to measure the ROI of a data cleansing project. Lean on vendors to show you exactly where you are today with the quality of data within your applications.

2. Understand the processes behind your data

Data will flow in and out of your organisation on a daily basis. You need to have a clear understanding of how data enters your organisation, as well as a healthy consideration for both the people and the processes, as they are the shield that protects your investment in any back end data cleansing project. Data can always be cleaned retrospectively, but it is only a short-term benefit if problems at the front end of your core business applications continue to exist.

3. Know the flaws in your data and what needs to change

Poor data can compromise the quality of your reporting and decision making. Identify what problems exist and how they can be fixed. If there are gaps in your data, a cleansing project often makes it possible to add in new information to give you a better insight into customer behaviour. This data might be profiling codes or geographic information, such as customer location. If the data solution to your problem doesn’t seem to exist as a standard product, push suppliers to give you an understanding of what could be available on a ‘bespoke’ basis. Bespoke solutions can often entail more expense, so you need to have a really clear idea of the business case and whether or not the cost of a data cleansing project is justified.

4. Understand the reach of the data in your application

It is important to understand that when cleaning data, particularly contact data, you must take into account how far the data reaches from a geographic perspective. Are you just looking at customers in the UK or are you looking to clean data from a broad range of countries? The more countries involved in your project, the larger the range of reference data you will require which can vary in standard from country to country.

5. Know your end goal and involve other departments

In a project of this nature, it is easy to tackle it from a departmental perspective and take the silo approach. You must certainly consider the business case from your department’s perspective but be sure to take others into account. Ask yourself who else could potentially reap the benefits from a project of this nature and then combine your resources with theirs. Finally, clean data is always the means, never the end in itself. Why do you need to clean up your data? You might be seeking more targeted marketing or better customer service. Whatever your reason, it must always be at the forefront of your mind.

If you're interested in data cleansing you can read more about our tools here.

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