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.
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.
Viviota's Senior Architect, Dr. Justin Young, presented this week at the National Instruments (NI) summit for LabVIEW architects. This annual event brings together top LabVIEW development talent from around the world to share information and exchange ideas to help build best-of-breed LabVIEW applications for the engineering world. Dr. Young's talk: Migrating a mature application and plugin infrastructure to an architecture based on PPLs covered the following...
The complexity of the electric power industry creates enormous opportunity for Fortune 500 companies and promising technology companies. Increased energy demands, capacity limitations, environmental constraints, varying load shapes, distributed generation and the deployment of new smart technologies all come into play. While new technologies will be developed to build a robust and resilient 21st Century grid, this new grid is still in its infancy and will take years, most likely decades, to reach that utopia of which we dream.
Around the globe, in practically every sector, manufacturing facilities are undergoing a major transformation. Factory 4.0, Smart Factories, is becoming a reality. Digitization is changing the way we process materials and make products. Data and the intelligence it can provide is proving to be the key to completely reshaping manufacturing.
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.
There’s a rumble in the Automotive Industry. A survey of automotive industries stakeholders, conducted by Jabil, showed that automotive companies are shortening product development timelines to meet new market requirements. The automotive industry has undergone a number of industry-shifting developments over the past several years. The introduction of electric vehicles and the continued development of ADAS technologies are leading these transformations. We’ve seen new challengers in the automotive industry popping up, and rapid innovation within leading automotive companies.
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.
Car & Driver's March 2019 issue includes an article on sound Active Noise Cancellation (ANC) and Electronic Sound Synthesis (ESS). With the September 2019 deadline looming for auto manufacturers to meet PEDESTRIAN SAFETY ENHANCEMENT ACT OF 2010 (PSEA), which governs EV & HEV sound emissions, there is opportunity for new automotive products that detect and emit sound at low speeds in these vehicles (< 18.6 mph). There is also the opportunity for the reverse, removing annoying sounds. Innovative sound creation and sound reduction systems are relying on sensor data to determine what sounds to synthesize and what sound to deaden.