Big Data
Analytics
(All unit PPT)
Syllabus
PART A
UNIT1
What is big data? And why is it Important?: A flood of Mythic “start-up” proportions; Big data is more than Merely big; Why now; A convergence of key trends; Relatively speaking; A wider variety of data; The expanding universe of unstructured data; setting the tone at the top.
UNIT2
Industry Examples of Big Data-I: Digital marketing and non – line world; Don’t abdicate relationships; Is IT losing control of web analytics? Database marketers, pioneers of big data; Big data and the new school of marketing; Consumers have changed. So must marketers;
UNIT3
Industry Examples of Big Data-II: The right approach: cross-channel life cycle marketing; Social and affiliate marketing; Empowering marketing with social intelligence; Fraud and big data; Risk and big data; Credit risk management; Big data and algorithmic trading.
UNIT4
Big Data Technology-I: The elephant in the room: Hadoop parallel world old Vs. new approaches; Data discovery: work the way people’s minds work; Open source technology for big data analytics; The cloud and big data; Predictive analytics moves into the limelight; Software as a service BI. Mobile business intelligence is going mainstream; Ease of mobile application deployment; Crowd sourcing analytics; Inter – and Trans-firewall analytics.
PART B
UNIT5
Big Data Technology-II and Information Management: R&D approach helps adopt new technology; Adding big data technology into the mix; Big data technology terms; Data size. The big data foundation; Big data computing platforms; Big data computation; More on big data storage; Big data computational limitations; Big data emerging technologies.
UNIT6
Business Analytics: The last mile in data analysis; Geospatial intelligence will make your life better; Listening: Is it signal of noise?; Consumption of analytics; From creation to consumption; Visualizing: How to make it consumable; Organizations are using data visualization as a way to take immediate action; Moving from sampling to using all the data; Thinking outside the box; 360o modeling; Need for speed; Let’s get scrappy; What technology is available?; Moving from beyond the tools to analytic applications.
UNIT7
The People part of the equation: Rise of the data scientist; Learning over knowing; Agility; Scale and convergence; Multidisciplinary talent; Innovation; Cost effectiveness; Using deep math, science and computer science; The 90/10 rule and critical thinking; Analytic talent and executive buy-in; Developing decision sciences talent; Setting up the right organizational structure for institutionalizing analytics.
UNIT8
Data Privacy and Ethics: The privacy landscape; The great data grab isn’t new; Preferences, personalization and relationships; Rights and responsibility; Playing in a global sandbox; Conscientious and conscious responsibility;
TEXT BOOKS
1. Michael Minelli, Michele Chambers, Big Data, Big Analytics: Emerging Business Intelligence and Analytic Trends for Today's Businesses Hardcover, 1st edition Wiley C/O series, 2013.
REFERENCE BOOKS
1. Viktor Mayer-Schonberger, Kenneth Neil Cukier: Big Data Are volution that Will Transform, How We Live Work And Think, 1st edition, Hachette India, 2013.