it-ebooks - An Introduction to Data Science

From: http://www.saedsayad.com/data_mining_map.htm

> Data Science

Data Science (a.k.a. Data Mining) is about by means of data analysis. Data science is a multi-disciplinary field which combines statistics, machine learning, artificial intelligence and database technology. The value of data science applications is often estimated to be very high. Many businesses have stored large amounts of data over years of operation, and data science is able to extract very valuable knowledge from this data. The businesses are then able to leverage the extracted knowledge into more clients, more sales, and greater profits. This is also true in the engineering and medical fields.

StatisticsThe science of collecting, classifying, summarizing, organizing, analyzing, and interpreting data. Artificial IntelligenceThe study of computer algorithms dealing with the simulation of intelligent behaviors in order to perform those activities that are normally thought to require intelligence. Machine LearningThe study of computer algorithms to learn in order to improve automatically through experience. Database The science and technology of collecting, storing and managing data so users can retrieve, add, update or remove such data. Data warehousingThe science and technology of collecting, storing and managing data with advanced multi-dimensional reporting services in support of the decision making processes. Understanding the project objectives and requirements from a domain perspective and then converting this knowledge into a data science problem definition with a preliminary plan designed to achieve the objectives. Data science projects are often structured around the specific needs of an industry sector (as shown below) or even tailored and built for a single organization. A successful data science project starts from a well defined question or need. Source: KDnuggets

Industries/Fields where you applied Analytics, Data Mining, Data Science in 2016? 2016 % of voters 2015 % of voters 2014 % of voters
CRM/Consumer analytics (90)	16.3% 18.6% 22.2%
Finance (83)	15.0% 15.4% 10.9%
Banking (74)	13.4% 14.3% 16.7%
Advertising (66)	12.0% 8.9% 10.4%
Science (66)	12.0% 11.7% 13.6%
Health care (66)	12.0% 13.4% 16.3%
Fraud Detection (61)	11.1% 10.0% 13.6%
Retail (57)	10.3% 9.1% 13.6%
Insurance (51)	9.2% 7.4% 8.6%
E-commerce (49)	8.9% 10.3% 9.5%
Telecom / Cable (46)	8.3% 7.7% 9.0%
Social Media / Social Networks (46)	8.3% 10.3% 8.6%
Software (40)	7.2% 6.0%