Data audits and assessments for your business

A data quality audit is the process where an organisation examines its data for accuracy, completeness and consistency of formatting. The aim of a data quality audit is to improve the quality of the data by spotting and filling gaps, identifying and fixing mistakes and weeding out duplicate records. This process helps better inform an organisation’s decision-making processes.

Because the volume of data an organisation holds is vast, it cannot be audited manually. Rather, it is performed using sophisticated data management tools, including software, to assess the quality, accuracy and trustworthiness of a data set. The formatting of the data is standardised, and reference data used to cross check for errors and inaccuracies. The data can then be enriched with extra data to correct mistakes and fill gaps. Duplicate data can be removed, and records linked where it is useful and appropriate to do so.

A data quality assessment is an analysis of the results of a data audit. It will often include a judgement about the results of the data audit. For example, this might involve making a decision on whether the data is fit for the purposes the organisation uses it. It might also include a judgement about whether the data is vulnerable to security breaches and suggest possible action to improve it. The assessment can also include recommendations about how the data can best be used to inform business decisions.

Data quality assessments can be complex due to the large volume of information many organisations hold. It is commonly carried out by specialised data management companies with the necessary sophisticated tools, software, experience and services.

A data risk assessment is an analysis of where data is vulnerable or weak, and the potential damage this could cause an organisation in the future. For example, the assessment might identify that data security is weak enough to expose an organisation to risk. These risks include breaches, mismanagement or non-compliance to regulatory requirements.

Data profiling is important because it can help an organisation make the most of its data, for example, by using it to identify where it can reduce costs, streamline workflows, find new customers, identify opportunities, enhance its reputation and spot risks before they damage the business. In other words, data profiling helps decision makers understand their organisations batter.

For more information complete your details here.