Analytics.... "The Science of Analysis'...

You can find lots of definition for Analytics. Let’s start the discussion with this simple and best understandable definition that Analytics is "the science of analysis". This is a science of using mathematical techniques to understand data. It may involve using statistics and other related techniques to make conclusions or obtain meaningful information from data to facilitate in making decisions. It might be used as a broader term to include all areas of capturing, storing, retrieving, analysing data.

This can be defined as the science of examining raw data with the purpose of drawing conclusions about the given information. Data analytics is used in many industries to allow companies and organization to make better business decisions and in the sciences to verify or disprove existing models or theories.

Analytics is the sophisticated analysis and use of business data to enable fact-based decision making at every level the organization. Analytics can drive superior performance – from customer management to the supply chain to product/service development to strategic planning.

Common applications of analytics include the study of business data using statistical analysis in order to discover and understand historical patterns with a view to predicting and improving business performance in the future. Also, some people use the term to denote the use of mathematics in business. Others hold that field of analytics includes the use of Operations Research, Statistics and Probability.

Analytics is an extremely vital part of business intelligence and the term "business analytics" is strongly related to this. Business analytics (BA) is the practice of iterative, methodical exploration of an organization’s data with emphasis on statistical analysis.  Successful business analytics depends on data quality, skilled analysts who understand the technologies and the business and an organizational commitment to data-driven decision making.

The use of analytics in business has been around for over two centuries now. Back in the late 1800's, the science of data analysis found use mainly in the development of industrial machinery. It wasn't until the 1960's that organisations realized the potential of analytics and made their first attempts at automating the data analysis process. These efforts included heavy usage of mainframe computers which were assigned the more tedious tasks associated with data storage and processing but these were known as the very first "Decision Support Systems”.

Examples of BA uses include: 

·      Exploring data to find new patterns and relationships (data mining)

·      Explaining why a certain result occurred (statistical analysis, quantitative analysis)

·      Experimenting to test previous decisions (A/B testing, multivariate testing)

·      Forecasting future results (predictive modeling, predictive analytics)

Managers or researchers can use various data mining techniques combined with historical patterns to make predictions about the performance of a particular market or business. This is usually done in an effort to improve an already existing model of operations.