MIS2502: Data Analytics

     The Internet of things (IoT) is a term that originated approximately 5 years ago and is growing in popularity. The encyclopedia of Britannica describes it as “a vast network of physical objects with embedded microchips, sensors, and communications capabilities that link people, machines, and entire systems through the Internet” (Graham, 2016). Its function can provide value in many ways, for example, a typical homeowner can benefit from IoT by utilizing devices that regulate temperature, control light switches, or even remotely monitor his camera feeds. However, its biggest contributor to a good return on investment (ROI) is when IoT is coupled with data analytics.

     With IoT the limitations are endless and “Big Data” from all the devices, sensors etc. need to be extracted, transformed, and loaded so it can be analyzed. This is known as Data analytics and it “refers to qualitative and quantitative techniques and processes used to enhance productivity and business gain” (Gong, web). The process allows businesses to solve complex problems using algorithms, visualization, and predictive analytics (Greengard, 2015). However, Dan Graham explains that unlike data extracts from transactional databases, these devices will produce volumes of data in the “petabyte range” (Graham, 2016). Therefore, raw data gets archived into “scaled-out systems (data lakes)” and stored on clouds until architect engineers can validate and design the data warehouse and data cubes that can be utilized (Graham, 2016).

Imagine having the tools to predict part failures on commercial aircrafts, pulling the data in real-time from multiple sensors on planes one can determine which parts are stressed, choose better maintenance schedules, prevent safety related issues, and increase profitability from eliminating downtime that would result from unplanned failure.

Works Cited

GE. (web). Predix. Retrieved from GE Imagination at work: https://www.ge.com/digital/predix

Gong, J. (web). MIS2502 Data Analytics Course Introduction. Philadelphia, PA.

Graham, D. (2016, August 9). How the Internet of Things Changes Big Data Analytics. Retrieved from Data Informed – Big Data and Analytics in the Enterprise: http://data-informed.com/how-the-internet-of-things-changes-big-data-analytics/

Greengard, S. (2015, July 14). The Internet of Things: Year In Review 2015. Retrieved from Britannica: https://www.britannica.com/topic/Internet-of-Things-The-2032782