The Importance Of Data Cleansing

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Modern businesses are data intensive and data hungry beasts. They use data in many forms and whether your company stores information on existing customers, manages its own lead database, or regularly acquires such databases then you could benefit from high quality data cleansing. This ensures that the information you retain is accurate, useful, and serves a purpose. When it comes time to create reports or use data that you store it is absolutely imperative that you use up to date and clean data - leaving it to chance can cause lost revenue, lost reputation, and lost business.

Poor quality data can cost businesses a lot of money. It can lead to inaccurate reports, the sending of incorrect information, and it can lead to individuals and groups within your organisation acting on poor quality data. Ultimately, this not only means inaccuracies but it can cause leads to become disgruntled and lose patience. It can even mean legal action, especially if you mismanage an email lead database or address database.

Bad data can also prove costly to your business. An address database can provide a good source of information for direct marketing but many of these databases contain inaccurate or incomplete addresses, repeat details, or false names and other information. Attempting to send letters and other correspondence to these details means wasted effort and resources.

Data cleansing can compare an address database to nationally held details to ensure considerably greater accuracy and the use of up to date information. This can help to keep costs to a minimum, reduce errors, and ensure a more accurate and therefore better performing set of data. Reports will provide greater accuracy which will mean that people acting on that data will enjoy improved results for their efforts.

Data cleansing is not reserved solely for address databases and address lists either. You can use similar techniques to cleanse email databases, data warehouse information, and spreadsheets. Rubbish records, repeat information, and other discrepancies can be determined without the use of additional data sets or you can use comparative cleansing techniques that will add even greater accuracy to the data that you use every day.
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