Data Preparation

With growing data varieties and volumes, we can help business users prepare data without having to rely on IT

Find out more

What is data preparation and who uses it?

Why is data preparation important?

Data preparation helps organisations to collect, cleanse, and consolidate their data into one, trustworthy file or table.

Business analysts and data stewards use data preparation tools to correct any human or machine input errors, remove duplicates, fill in incomplete data, and merge data from several sources or data formats.

This produces harmonised, standardised and enriched data, that is then analysed to inform business decisions.

Businesses need to have confidence in data to support strategic, operational, and financial decisions.

However, the increasing complexity of data is pressuring organisations to review their data preparation processes. Inconsistent and low-quality data compounds this challenge, making analytics and data mining slow and unreliable.

Preparing data sources has traditionally been an IT responsibility, but growing interest in data analytics is bringing non-IT personnel into data preparation. Self-service data preparation tools reduce the burden on IT, while ensuring data governance is part of the process.

Technology for Data Quality Analysts

As a data practitioner, you are the driving force in your organisation’s quest to create a long-term strategy for data quality management and maturity. Take control of your data assets today - find out how technology can support your data management efforts.

Download the guide Assess your data maturity today

How we can help with your Data Preparation


Quickly and confidently automate what used to be a lengthy and expensive manual process


Create re-usable data transformation rules to save time and effort


Turn your data into immediate value by creating formats and standards specific to your business


Business users can take control over powerful analytical insights without IT support


Move up the Data Quality Maturity Curve by taking the important first steps with your data