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Easy techniques for managing the quality of your data

Posted by Nicky Hawkins on Feb 27, 2019 10:24:00 AM
How to stay GDPR compliant when collecting customer data

Data is a critical resource for any business. It is the basis for most of the everyday decisions that companies make. Some of this data ends up in the hands of auditors and inspectors who use it to gauge performance. For this reason, enterprises need access to information that is accurate, timely and relevant. Poor quality data will compromise the operations of the whole business.

Unfortunately, companies are faced with numerous data quality issues that range from loss and obsolescence to inaccuracy and duplication. Maintaining a high standard of data requires an enterprise to invest in effective data processes. Employees must also play their part to ensure that the quality of data remains consistent. A few tips can help businesses understand how to approach data quality.

Be clear about the data

With the copious amounts of data that businesses have access to today, relevance can be hard to maintain. An enterprise must first identify the goals for collecting certain information. Knowing the 'why' will direct data gatherers to the right sources. A company can avoid wasting money on data that does not add value to their objectives. Unused information can lower data quality because no one bothers with it, making it possible to have outdated, obsolete or erroneous information in the system.

Efficient data entry

Employees must be trained on the correct methods to enter data. The different departments in an organisation have varied use for the information they collect, and that will determine the entry methods. An enterprise should ensure that its workers know how to gather data in accordance with the various regulations in place like the GDPR. Companies achieve data quality by assigning roles to staff depending on their competencies.

Review regularly

An enterprise can spot anomalies in its data by reviewing it constantly. With new data coming in, it is easy for errors to occur due to data loss and improper conversion. Regular checks provide a company with the opportunity to spot if anything is amiss with the data. Reviewing data helps people to understand it better, making it easy to tell when something doesn't add up. The system administrator can then trace the errors back to the source and apply the necessary corrections.

Standardise data

Enterprises must facilitate the normalisation of data to help with its organisation. When data comes in from different sources, it is imperative to structure it in a way that the system comprehends. Automated systems need data to be normalised to sort through it with more ease. For example, a company can have detail in UK spellings to ensure that no discrepancies arise. Standardisation allows users to access data from a singular point, which saves time and reduces errors.

Find Out More

Data is invaluable to businesses but only if it is of good quality. Poor quality data can be due to many issues that range from data loss to duplication. At Clearview, we offer software solutions to help companies with data quality. Our tools are built to streamline the process of gathering and organising data. Contact one of our sales team on 0845 519 7662 to find out more, or click here to get in touch through our website.

Download the best practice guide to data quality management

Topics: Performance management

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