Clarifying Data Analytics Concepts

Clarifying Data Analytics Concepts

1. Data Mining

   • Using algorithms to facilitate the extraction of information, which is stored in a computer.

2. Machine Learning

   • “automatic learning, process by which a functional unit improves its performance by acquiring new knowledge or skills, or by reorganizing existing knowledge or skills”.
     • Supervised Learning
       • predicting an outcome value based on the measures of other input variables.
         • Linear Methods for Regression
         • Linear Method for Classification
         • Decision Tree Based Method
         • Neural Networks
     • Unsupervised Learning
       • description of associations and patterns among a set of input data
         • Principal Component Analysis
         • Association Rules
         • Cluster Analysis
         • Self Organizing Maps

3. Data Analysis

   • Data analytics is therefore composed of: initial standard statistical techniques, such as visualization of data, selection of attributes, discarding outliers etc. in order to construct the initial example set; then, machine learning algorithms construct rules and statistical tests are used to validate them
     • AI
       • AI systems can perform actions such as perception, interpretation, reasoning, learning, communication and decision making to arrive to a solution for a given problem, imitating the intelligent behaviour of human expertise
     • Big Data
       • consists of extensive datasets -primarily in the characteristics of volume, variety, velocity, and/or variabilitythat require a scalable architecture for efficient storage, manipulation, and analysis

4. Extraction of Value From Data

   • Manufacturing companies need to embrace data analytics to remain competitive in the global market