Big Data Technologies
This course provides an insight and expertise on how to leveraging big data in business so you can harness the power of analytics and gain a true business advantage. Based on a practical framework with supporting methodology and hands-on exercises, this book helps identify where and how big data can help you transform your business. You'll learn how to exploit new sources of customer, product, and operational data, coupled with advanced analytics and data science, to optimize key processes, uncover monetization opportunities, and create new sources of competitive differentiation. The discussion includes guidelines for operationalizing analytics, optimal organizational structure, and using analytic insights throughout your organization's user experience to customers and front-end employees alike. You'll learn to “think like a data scientist” as you build upon the decisions. Line business no longer need to relinquish control of data and analytics to IT. In fact, they must champion the organization's data collection and analysis efforts. This course is a business approach to analytics, providing the practical understanding you need to convert data into opportunity.
· Understand where and how to leverage big data · Integrate analytics into everyday operations · Structure your organization to drive analytic insights · Optimize processes, uncover opportunities, and stand out from the rest · Help business stakeholders to “think like a data scientist” · Understand appropriate business application of different analytic techniques
At the end of the course students should be able to: · Discovering Big Data’s fundamental concepts and what makes it different from previous forms of data analysis and data science · 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 · Applying computational analysis methods, including machine learning Session Plan
Instructions to students
· Come to class on time. · Maintain proper decorum and create a healthy learning environment inside class. · Always have the text book and a scientific calculator · Cell phones must be switched off during the entire duration of the class and should be kept inside your bag and not on the table. Any student found keeping mobile phone on the table will be marked absent for the day. · No request will be entertained to change the class project or assignment, once finalized by the group, and intimated to the instructor. · Absence from any on-line quiz and test (without any strong reason) is strongly discouraged.
Created By: Alora Kar on 10/18/2019 at 11:28 AM Category: MBA(Exe.)BA-2019-20 T-III Doctype: Document