Today, businesses run on data. In 2018, 82% of executives responding to an Accenture Technology survey said that their organizations are "increasingly using data to drive critical and automated decision-making, at unprecedented scale."

The bad news: much of this data is inaccurate, or processed in a way that inevitably produces errors down the line. According to a study published in the Harvard Business Review, only 3% of the executives who reviewed their departments' data records found them to meet the organization's data quality standards.

And the remaining 97%? For them, data errors are a minefield that could blow up a business or department's performance at any time.

The only way to keep a data disaster from hitting the fan is to trust that your KPIs are always clean. At QA2L, we believe that each company or team has a right to trust in their data's quality and integrity. We also believe we have developed a method - and a solution - that automates your data quality efforts, relieving you or your team from the boring, menial QA tasks that take up so much time and are still prone to human error. 

To introduce the topic of Data Quality Sustainability, we have put together a comprehensive e-Guide, which you can preview (first 15 pages) below, or download in its entirety (61 pages, including 12 use cases offering executives, marketers, or data analytics professionals practical solutions to every-day problems).

Any questions or feedback? Please do not hesitate to contact us.