NOW FOR AN ORIGINAL PAPER ASSIGNMENT:Assignment: IT Innovations and Technology

Big data analytics: past and present

The history of big data analytics is inextricably linked with that of data science. The term “big data” was used for the first time in 1997 byMichael Cox andDavid Ellsworth in a paper presented at an IEEE con- ference to explain the visualization of data and the challenges it posed for computer systems (Cox and Ellsworth, 1997). By the end of the 1990s, the rapid IT innovations and technology improvements had en- abled generation of large amount of data but little useable information in comparison. Concepts of business intelligence (BI) created to empha- size the importance of collection, integration, analysis, and interpreta- tion of business information and how this set of process can help businesses makemore appropriate decisions and obtain a better under- standing of market behaviors and trends.

The period of 2001 to 2008was the evolutionary stage for big data development. Big data was first defined in terms of its volume, veloc- ity, and variety (3Vs), after which it became possible to develop more sophisticated software to fulfill the needs of handling informa- tion explosion accordingly. Software and application developments like Extensible Markup Language (XML) Web services, database management systems, and Hadoop added analytics modules and functions to core modules that focused on enhancing usability for end users, and enabled users to process huge amounts of data across and within organizations collaboratively and in real-time. At the same time, healthcare organizations were starting to digitize their medical records and aggregate clinical data in huge electronic data- bases. This development made the health data storable, usable, searchable, and actionable, and helped healthcare providers practice more effective medicine.

At the beginning of 2009, big data analytics entered the revolution- ary stage (Bryant et al., 2008). Not only had big-data computing become a breakthrough innovation for business intelligence, but also re- searchers were predicting that data management and its techniques were about to shift from structured data into unstructured data, and from a static terminal environment to a ubiquitous cloud-based envi- ronment. Big data analytics computing pioneer industries such as banks and e-commercewere beginning to have an impact on improving business processes and workforce effectiveness, reducing enterprise costs and attracting new customers.