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Blogs Article How Dirty Is Your Data?

How Dirty Is Your Data?

Martin Doyle July 12th, 2021 Article, CRM Data Cleansing, Data Quality
Impacts of dirty data blog

Last week was National Hygiene Week, a particularly pertinent theme given the last year and a half. Due to the Covid-19 pandemic, we’ve all beefed up our individual and collective physical hygiene habits, both in a personal and professional setting.

From face masks and social distancing to singing Happy Birthday while washing our hands and sanitising our cucumbers, we’ve all upped our game to try and keep Covid-19 at bay.

While businesses around the globe have adapted to the presence of a physical threat, many still seem to ignore the impacts of a digital one: dirty data.

In this blog, we’ll be getting down to the nitty gritty and detailing the impacts of dirty data, and our top 5 tips for good data hygiene.

What is dirty data?

Very simply, dirty data is a data record that contains either incomplete or incorrect information. The impacts of dirty data are wide ranging and will manifest themselves differently depending on your industry.

According to research conducted by IBM, businesses in the US lose $3.1 trillion annually due to dirty data and poor data quality.

On a more tangible scale, the most harmful effects of dirty data for your business are the following:

  • Poor quality analysis – If you rely on data to provide analytics to drive your business insights, dirty data will give you the wrong information, potentially resulting in you to making the wrong business decisions.
  • Insults rather than insights – Sticks and stones may break your bones, but insults will lose you customers. Offering someone a service or product they’re not interested in is one thing, offering them one that is downright insulting can lead to a customer walking away and lasting reputational damage.
  • Poor data compliance – If you manage to avoid insulting your customers with your dirty data, this doesn’t mean you’re getting away scot-free.

Sooner or later, you may well find yourself running afoul of the myriad data compliance laws like GDPR, resulting in a hefty fine.

How Can I improve my data hygiene?

If you think your data hygiene could be better, don’t worry, we’re here to help.

By following these simple steps, you’ll have some sparkly clean data, ready to provide you with sensational insights that will push your business to new heights.

  1. Take stock

The first port of call is to figure out what your problem areas are, and you can do this by auditing your current data records.

Figure out what you have and what state it’s in. Look out for incomplete, incorrect, non-compliant or outdated records and cleanse them from your database. If this sounds daunting, or you’re not sure where to start, our data quality improvement sessions will give you actionable solutions to bring your data records up to scratch.

  1. Merge what’s left over

If you’ve taken a “more is better” view on data, you’ll most likely end up with multiple records for the same individual.

One record may have an email address, the other a telephone number. The best thing to do in this situation is to merge the two into one complete file (record) creating a Single Customer View or Master Golden Record containing only the needed information.

  1. Format is key

A quick win on the road to hygienic data is formatting.

For each field, decide a format for them and stick to it. For example, with phone numbers this may mean including international dialling codes.

Doing this will streamline your data into a uniform format, making it easier to spot and correct any pesky inaccurate records in the future.

  1. Create a golden standard

Once you’ve done a spring clean of your current data, it’s then a good idea to consider exactly what data is important to your business.

What fields of information will realistically be helpful? Do you need a telephone number, or will an email address be enough?

Once you’ve decided this, applying it, along with your formatting, to your data collection process will take you once step closer to good data hygiene.

  1. Everyone needs validation

Once you’ve completed the prior steps, the last thing to do is validate your cleansing process.

This will allow you to make sure that all your efforts aren’t in vain and that the data being collected is clean, accurate and good quality.

This should be done regularly to ensure that everything is still running smoothly and that no renegade data records slip through the net.

How DQ Global can help

Unless you’re working with very small amounts of data, maintaining a spic and span data record is a herculean task that will likely consume most of your day.

At DQ Global, we’ve been supporting businesses across the globe with their data quality for over 25 years.

Our award-winning range of solutions and products have helped many recognisable businesses leverage their data into illuminating insights, saving them money, time and mitigating risk.

Not sure where to start? Book a DQ Discovery Call

Looking to unlock the full potential of your customer data, but struggling with data quality issues? Our DQ Discovery Call service is here to help! Our team of experts will analyze the root causes of your data quality challenges and provide you with practical solutions to transform your customer data into a powerful tool for success.

Book Now

If you’re concerned about the quality of your Customer Data, book a DQ Discovery Call with us today


Written by Martin Doyle

Martin is CEO and founder of DQ Global, a Data Quality Software company based in the UK. With an engineering background, Martin previously ran a CRM Software business. He has gained a wealth of knowledge and experience over the years and has established himself as a Data Quality Improvement Evangelist and an industry expert.