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 In Data Cleaning, Data Matching

automationThese days, it is becoming easier for companies to acquire and store large quantities of data. In turn, these datasets could allow businesses to get richer analytics and to improve their decision making. More recently, you can use these datasets to feed complex machine learning algorithms. Yet, data quality remains one of the biggest concerns. Common errors like missing values, replicated entries of the same entity, typos or mixed formats, often lead to unreliable analysis and incorrect business decisions. This post will discuss why automated data cleansing should be on every company’s list of priorities.

Why should I cleanse my data?

For starters, let’s see why you should use data cleansing.

The answer is simple: by ensuring that your data is cleansed, you can gain important business value. For example, you can avoid significant hassles like high cost due to processing errors, incorrect data on invoices or even ship to wrong addresses. With data cleansing, companies can achieve an impressive range of benefits. Here are the most important three:

Increased revenue

Companies working to cleanse their data and improve its consistency are increasing their response rates which, most often, results in more revenues. For example, cleansed data largely reduces the number of bounces. Also, if you need to channel time-sensitive information to your users, accurate and cleansed data will help you to quickly and conveniently reach your customers.

Increased productivity

With cleansed and up-to-date data sources, you can make sure that your employees are more productive. For example, your sales team will not spend time trying to contact your customers that you registered with incorrect or outdated data. Also, if you sent more than one email to your customers, they might become annoyed. As a result, their interest in your products or services might drop.

Better business decisions

Most often, the foundation for making effective decisions is customer data. But, the amount of data an organization stores is expected to double with every two years. Hence, even if you cleansed and matched your initial data, errors are most likely to appear over time.

Because of the fact that accurate information and quality data are essential to better business decisions, it is key to regularly perform data cleansing activities.

How can I automate my data cleansing process?

The data you store in your databases, CRMs, or any other data sources is continually decaying. Thus, you should constantly update and cleanse your data. This will  allow you to make sure it is always duplicate free.

Surprisingly, there are many companies that fail to take this aspect into account. Even more, many businesses don’t even keep records of the last time they performed data cleansing or data matching.

Probably the main reason here is that running a data cleansing or data matching activity is time-consuming. Moreover, the benefits are not always immediate.

Fortunately, the automation module within WinPure Clean & Match provides you the ability to create and configure your data cleansing and data matching tasks, and automatically schedule them to run at any time.

As we designed our automation module to execute in the background, it is not necessary to run WinPure Clean & Match when an automation task is created. Also, we designed a wizard that will help you configure and run your data cleansing and data matching tasks. It takes just a few tasks in minutes set these tasks up.

With our WinPure Clean & Match automation module, you can be assured that your ever-changing customer data is always cleansed and matched. Also, you don’t have to spend time when you run a data cleansing or a data matching task. We designed the module to use built-in Windows automation mechanisms. Hence, the operating system will automatically execute the task.

Download our WinPure Clean & Match free trial, and see for yourself how our award-winning software can help your company achieve overall operational efficiency by automating your data cleansing and data matching tasks.

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Comments
  • Helena Ricks
    Reply

    Great write up, I found this very interesting. Thanks for sharing.

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