Introduction to Big Data

I am sure some of you reading this will have heard the term “Big Data”. Big Data has been the subject of increasing interest in the IT industry for a number or years and has applications to many fields including healthcare, telecommunications, retail and government.  According to Gartner the Big Data industry will be worth $125 billion USD in 2015 (Press, 2014).  Many of the big IT venders such as Oracle, IBM and SAP are already offering Big Data technologies and services.

One of the questions I had when I started to hear about the term is what exactly is Big Data?  I did some research and what I found were people repeatedly talking about the 3 Vs when referring to Big Data, namely volume, variety ad velocity.  Big Data is data that is characterized by its size (think millions and billions of gigabytes), the variety of sources from which it comes from such as traditional consumer transactions, smartphones, RFID tags  (think internet of things) and the speed in which it is collected and analysed (which is typically in real time) (Gandomi & Heider, 2015).  The name Big Data does tend to focus people’s attention on the size of Big Data however variety and velocity are also just as important as argued by Jagadish (2015).

The concept of Big Data can be seen as far back as the 1940s (Press, 2013).  However the term only started to receive substantial attention in the mid to late 2000s.  Given that Big Data has only been a trend for less than a decade there are still many challenges faced by organisations looking to implement Big Data.  These challenges can be technical, such as what hardware or software to choose and how to configure the infrastructure, or managerial such as how to monetize big data, privacy and lack of skills.  The focus of my blog will be on the managerial challenges related to Big Data hence the title “Big Data 4 Managers”.  Over the next few weeks I will discuss these management challenges and possible ways to address them.

Reference List                                                                                   

Gandomi, A. & Haider, M., 2015. Beyond the hype: Big data concepts, methods, and analytics. International Journal of Information Management, 35(2), pp.137–144. Available at: http://www.sciencedirect.com/science/article/pii/S0268401214001066.

Jagadish, H.V., 2015. Big Data and Science: Myths and Reality. Big Data Research, 2(2), pp.49–52. Available at: http://linkinghub.elsevier.com/retrieve/pii/S2214579615000064.

Press, G., 2013. ‘A very short history of Big Data’. Forbes. Retrieved from http://www.forbes.com/sites/gilpress/2013/05/09/a-very-short-history-of-big-data/.  Date accessed 01 October 2015.

Press, G., 2014. ‘6 Predictions for the $125 billion big data analytics market in 2015’. Forbes. Retrieved from http://www.forbes.com/sites/gilpress/2014/12/11/6-predictions-for-the-125-billion-big-data-analytics-market-in-2015/.  Date accessed 01 October 2015.