Data Analysis In Research

m research in machine learning and data mining to discover scalable computational methods for finding useful models from massive amounts of data. Analytics is the discovery and communication of meaningful patterns in data. These models can be used in a variety of tasks, including clustering/discovery, regression/prediction, and classification/ranking. Data Analytics building predictive models and discovering patterns from data.

16.4 Data Analytics: Concept and Process

Firms may commonly apply analytics to business data, to describe, predict, and improve business performance. Specifically, areas within analytics include predictive analytics, enterprise decision management, retail analytics, store assortment and stock-keeping unit optimization,

Such data sets are commonly referred to as big data. Whereas once the problems posed by big data were only found in the scientific community, today big data is a problem for many businesses that operate transactional systems online and, as a result, amass large volumes of data quickly.

The analysis of unstructured data types is another challenge getting attention in the industry. Unstructured data differs from structured data in that its format varies widely and cannot be stored in traditional relational databases without significant effort at data transformation. Sources of unstructured data, such as email, the contents of word processor documents, PDFs, geospatial data, etc., are rapidly becoming a relevant source of business intelligence for businesses, governments and universities. For example, in Britain the discovery that one company was illegally selling fraudulent doctor's notes in order to assist people in defrauding employers and insurance companies, is an opportunity for insurance firms to increase the vigilance of their unstructured data analysis. The McKinsey Global Institute estimates that big data analysis could save the American health care system $300 billion per year and the European public sector €250

That could include Web server logs and Internet click stream data, social media content and social network activity reports, text from customer emails and survey responses, mobile-phone call detail records and machine data captured by sensors connected to the Internet of Things. Some people exclusively associate big data with semi-structured and unstructured data of that sort, but consulting firms like Gartner Inc. and Forrester Research Inc. also consider transactions and other structured data to be valid components of big data analytics