Business Analytics & the Big Data

Transcription

1 Business Analytics & the Big Data Data Nubes James Ogunleye, PhD December 2012

2 Overview of presentation The Big Data phenomenon Introduction to business analytics Defining business analytics 'Benefits' of business analytics Business analytics disciplines Importance of: clean, good data, pretesting of data, and skills and expertise Concluding remarks

3 The Big Data The term Big Data is used to refer to data sets that are so large and so massive and most often so complex and moves so fast that it is beyond human capacity or regular or conventional database systems to extract information from or to analyze the data. It has been said that the explosive growth in data took place in the last two years alone. Imagine the amount of data we would create in the next five years mind bogging! The Big Data includes both structured and unstructured data data from business operations, s, web log and social media, to cite a few examples. Business analytics technologies are a response to the recent explosive growth in data; business analytics software is already helping businesses to take the sting of the Big Data mayhem.

4 Introduction to Business Analytics Business analytics is not a new phenomenon in the sense that our capacity for statistical analysis has always been with us. What is new is the explosive growth in data informed by rapidly growing information technologies. Faced with such an explosive growth in data, business analytics literally got 'reconfigured' to enable companies to make sense of the Big Data, extract or collect hitherto hard-to-reach information or get new insights from the analysis of the data as well as make smart, forward-looking decisions. The preceding point about forward-looking decisions is important: business analytics is never about looking into the past even though it is an important tool for evaluating past business events or transactions.

5 Defining Business Analytics In simple terms, business analytics is about making sense of vast array of data. It is an art or is it science? or technique of interrogating and translating large and often complex and mobile data from business operations and further afield (such as social media) into clear, digestible information feed-able into business planning or strategic decision making process. Business analytics involves a mega-understanding of the data as well as the application of skills, expertise and software capability (applications). Smart software vendors often call the latter 'business' or 'enterprise analytics solutions'.

6 'Benefits' of Business Analytics Business Analytics enables companies to base business decisions on hard evidence, informed by data and statistics. When an organization knows more or becomes supremely familiar with its own business operations data, for example, it follows that such an organization should not only gain new or deeper insights there from, but also identify areas of cost savings and efficiency and productivity improvements. Organizations with business analytics solutions in place should also be able to answer with easy what if... questions and thus be able to focus on areas of future business growth. Business analytics helps organizations to look relatively confident into the future this is what is being referred to as 'predictive analytics'.

7 Business Analytics Disciplines Business analytics does not sit or reside in a single discipline this means that a single subject discipline cannot lay claim to it. Business analytics draws from and brings together a diverse body of knowledge including quantitative research methods and analysis (statistics and applied maths), consumer behavior (marketing), supply chain management, risk management and decision making theory (business strategy), operation research, computer science, accounting and finance. By drawing on such a diverse body of knowledge, business analytics solutions can therefore be applied to and implemented in every aspect of organization be it production, marketing, human resources, finance, sales and accountancy.

8 Good data, right skills While business analytics is gaining momentum, it is important for organizations with large data sets to consider the quality of the data they held before investing full blast in business analytics solutions (technologies)! The quality of business analytics solutions (outcome) depends very much on the quality of the input (data). Eager business analytics enthusiast organizations should first invest in their people, to acquire the right skills; have a system in place to assure quality of data and then do some pilot hypothetical testing or conduct feasibility studies on the data sets before paying over the odds for business analytics solutions (technologies).

9 Concluding remarks Do remember that the nature of your business should determine your pilot hypothetical testing ask yourself this simple question: what do you need business analytics solutions for? If you are a retailer, you are likely to do your pilot on supply chain data especially if your goal is to cut spending on supply chain or drastically reduce cycle times.

10 Concluding remarks Now that you have got the gist, go on and capture good quality data, interrogate and make sense of your data. Go on. Thank You. Contact