Harvard Business Review[i] reported that cross-industry studies show, on average, less than half of an organization's structured data is actively used in making decisions—and less than 1% of its unstructured data is analyzed or even used at all.
The recent announcement on Reuters outlining the new partnership between GM and Honda, to bring two EV vehicles to market for a safer world exemplifies the pressures automotive manufacturers are under today. Honda and GM Partner for EV – Reuters, April 2, 2020 This announcement is not surprising as it is drafting behind GM and Honda’s current collaboration on autonomous vehicles and fuel cell vehicle technology. The companies worked together on the design of an autonomous vehicle called Cruise Origin for GM’s majority-owned Cruise Automation unit.
My day job for the past 30 years has been helping people with their sensor data. In my time off I tinker with and build PCs, try my hand at some home improvement projects and stay on top of new technology developments through the consumption of copious amounts of online tech news website articles and YouTube videos. What I have learned—and keep being reminded of time and time again—is that there are plenty of things that I don’t know. And, that sometimes I’m not even aware of things that I don’t know. Let me explain.
Traditionally, the data cleansing is defined as the process of detecting and correcting (or removing) corrupt or inaccurate records from a record set, table, or database and refers to identifying incomplete, incorrect, inaccurate or irrelevant parts of the data and then replacing, modifying, or deleting the dirty or coarse data.