Big Data Analysis

Description

This course is an introduction to Big Data. The course explains key Big Data concepts, theory and terminology, as well as fundamental technologies and techniques. The course explains how Big Data can propel an organization forward by solving a spectrum of previously intractable business problems. It also introduces key analysis techniques and technologies and show how a Big Data solution environment can be built and integrated to offer competitive advantages.

Program

IS -132 CRs

Objectives

• Discovering Big Data’s fundamental concepts and what makes it different from previous forms of data analysis and data science Analyze typical decision situations to support them with computer technology. Understanding the business motivations and drivers behind Big Data adoption, from operational improvements through innovation. Planning strategic, business-driven Big Data initiatives. Addressing considerations such as data management, governance, and security. Recognizing the 5 “V” characteristics of datasets in Big Data environments: volume, velocity, variety, veracity, and value. Clarifying Big Data’s relationships with OLTP, OLAP, ETL, data warehouses, and data marts. Working with Big Data in structured, unstructured, semi-structured, and metadata formats. Increasing value by integrating Big Data resources with corporate performance monitoring. Understanding how Big Data leverages distributed and parallel processing. Using NoSQL and other technologies to meet Big Data’s distinct data processing requirements. Leveraging statistical approaches of quantitative and qualitative analysis. Applying computational analysis methods, including machine learning.