Data Analytics
What is analytics?
It is a process of decision making and solving business problems by collection, manipulation and interpretation of data.
Analytics can be defined as, “the systematic computational analysis of data or statistics.”
Unstructured data is very difficult to work with. Both for humans and machines. Lack of structure makes it difficult for the compilation process as well. The most common confusion made by people is identifying the difference between data mining and data analytics. Data Mining is a process of retrieving necessary data from a pile of large raw data, whereas Data analytics strictly involves interpretation of data into meaningful outcome. It’s a step ahead of Data mining.
Big Data
Big data can be defined as,” extremely large data sets that may be analysed computationally to reveal patterns, trends, and associations, especially relating to human behaviour and interactions.”
Big data definition changes from situation to situation and organisation to organisation
Advantages of Data Analytics
Data analytics can open door to unlimited opportunities for organisations at every level. Knowing the outcome is always better reacting to a outcome, this is possible by integrating big data with organisation. Good use of big data is guaranteed to improve overall performance of an organization by allowing them to:
– Improve operational processes by streamlining supply chains and increasing productivity.
– Detect fraud and flaws by keeping a close vigil.
– Refine financial processes by increasing visibility, providing insight and granting better control.
– Reduce risk by being predictive instead of being reactive to environment and change.
– Innovate and create new models for growth.
– Improve IT economics by increasing agility, flexibility and abilities of systems.
– Increase transparency of systems and processes in business.
– Reduce cost of managing systems and operations.
– Make quicker, cost-effective decisions.
– Create products and services based on insights.