Chapter-1: Introduction to Analytics, Data & Basic Statistics
How is Big Data changing the way things were? – Big Data in HR. – How big is Big Data? – Explaining the evolution of Big Data Revolution. Technology Driving Big Data.
What is structured data? – Web 2.0 & Arrival of Big Data. –Unstructured Data. – Semi-Structured Data. Difference between structured and Semistructured Data – Composition of Big Data then and now. – Enterprise Applications & Bespoke IT Applications.
Chapter-2: Demystifying Big data
Characteristics of Big Data. – Deep Web & Surface Web.
Getting Started with Business Intelligence (BI)
Definition of Business Intelligence. – Features of Business Intelligence. – Visibility provided by BI. – Differences between ERP & BI. - Difference between Big Data & Business Intelligence.
Chapter-3: Data Analytics using Microsoft Excel
Use Excel to sort data with pivot tables-create histograms and other charts for data visualization-calculate summary statistics-create indicator variables for qualitative information.
Chapter-4: Measuring association between variables
Visually examine data (via Excel charts, sparklines, etc.) and identify trends-Construct linear regression models in Excel-Evaluate linear regression model quality-Use models to forecast demand and interface with Excel Solver to make operational decisions.
Learn how to forecast sales using trend data - Prepare pro-forma financial statements - Understand the link between growth and financing needs - Learn to calculate sustainable growth rate algebraically and also by using Excel Goal seek.
Forecasting Budgeting numbers
Basics of Time Series, Time Series on Summarised Reports & Forecasting Logistic Regression, Decision Trees, Creating a policy on basics of Analytics.
Chapter-5: Information Management in Analytics
Analytic Software - R, Excel, Solver, Basics of Big Data - Hadoop, HDFS, Hive, Pig, Python.