Analytics

The simplest definition of Analytics is "the science of analysis". In reality, the word "Analytics" has not been properly defined by the professional community and may mean different things to different people. A simple and practical definition, however, would be how an entity(i.e., business) arrives at the most optimal or realistic decision from a variety of available options, based on existing data. Business managers may choose to make decisions based on past experiences or rule of thumb, or there might be other qualitative aspects to decision making; but unless there is data involved in the process, it would be considered beyond the purview of analytics. Another definition could be that Analytics is a field of study / profession that has applications in any field (business / social / poiltical / home) where data is available.

Common applications of Analytics include the study of business data using statistical analysis in order to discover and understand historical patterns with an eye to predicting and improving business performance in the future. Also, some people use the term "Analytics" to denote the use of mathematics in business. Others hold that field of analytics include the use of Operations Research, Statistics and Probability. However, it would be erroneous to limit the field of analytics to only statistics and mathematics. Good analytics professionals should be well trained in business concepts and the social sciences, as well as have a good grasp of statistics and mathematics. A good analytics professional should be willing and able to work across various fields to come up with the proper solutions. Others argue that an analytics professional should also be cognizant of his data sources, which includes knowledge of his organization's IT infrastructure. That is why analytics is unique and much broader than the use of statistics or mathematics in business.

Analytics closely resembles statistical analysis and data mining, but tends to be based on physics modeling involving extensive computation. Some fields within the area of analytics are enterprise decision management, marketing analytics, predictive science, strategy science, credit risk analysis and fraud analytics.

With the advent and popularity of Business Intelligence (BI) tools, the importance of analytics is increasing in businesses. Analytics has been credited for helping Netflix ward off competition from Blockbuster video and helping Google overtake Yahoo to become the most profitable portal on the internet.

Portfolio analysis
A common application of business analytics is portfolio analysis. In this, a bank or lending agency has a collection of accounts of varying value and risk. The accounts may differ by the social status (wealthy, middle-class, poor, etc.) of the holder, the geographical location, its net value, and many other factors. The lender must balance the return on the loan with the risk of default for each loan. The question is then how to evaluate the portfolio as a whole.

For instance, the least risk loan may be to the very wealthy. However, there are a very limited number of wealthy people. On the other hand there are many poor that can be lent to, but at greater risk. Some balance must be struck that maximizes return and minimizes risk.

The analytics solution may combine time series analysis, with many other issues in order to make decisions on when to lend money to these different borrower segments, or decisions on the interest rate charged to members of a portfolio segment to cover any losses among members in that segment.