Data Quality is a problem for many. We as company owners and operators make thousands of decisions every day – anywhere from C-Suite to the mailroom – by looking at data that may be in our home-grown or SaaS products, in databases or data warehouses, raw or aggregated to KPIs. As we grow more dependent on data in the modern age, there is a growing need for ensuring that the data we look at is of “some” quality. In this article, we take a 5W1H approach to data quality monitoring.
At its most basic, a firewall is the barrier that sits between a private internal network and the public internet. It was invented in the 1980s and soon became the most important line of defense for organizations against cyber attacks. Its main purpose is to keep dangerous traffic out. We took this concept and applied it to data. This means our Data Firewall’s main purpose is to keep bad data out. We profile and analyze your data, ultimately using our understanding to improve your data’s quality by filtering and quarantining the bad data.