Top tips for pain-free data cleansing - Eurolink

Top tips for pain-free data cleansing

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As conscientious as many of you will have been in working through your business to-do list, it’s unlikely that data cleansing was one of the items you managed to cross off.

This essential, although often daunting, task is more than likely to have been pushed to the bottom of your list, if not ditched altogether, in favour of less tedious items.

But you mustn’t be put off by a task that can quite literally transform your business. Read on to find out where to start.

  1. What is it?

Data cleansing simply means cleaning up your data to remove incorrect, incomplete and duplicate data, as well as out of date information.

  1. Why bother?

Accurate data enables you to mine your data – in other words, to analyse your data – and gain a real time snapshot of your business, which means an insight into your current success and the extent to which your current business strategy is on track.

Accurate data will enable you to, for example, assess how many properties you have in your database, the volume that is currently occupied and the proportion with any rent arrears, enabling you to trouble shoot the causes in a timely manner.

  1. Where do I start?

Your software provider should be your first port of call. Like Eurolink, your provider should be able to offer you a tailored strategy, designed by property market experts, that will guide you from an initial audit through to a thorough cleanse of your data.

  1. Are there any short cuts?

There are countless data cleansing tools available on the market, which can help you to identify incorrect, incomplete and duplicate data. However, the choice is endless and the comparative features are a minefield, so talk to your software provider about the most appropriate way forward for your business.

  1. How often is the data cleansing process necessary?

This depends on a number of factors, from the size of your business to the care with which you and your team input and review the client data in your database. Be honest with yourself about the last time you reviewed your data and about the extent to which you’re able to glean truly useful information from it, and then get to work!



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