Data Analytics+ (Plus)


Data analytics is the science of interpreting vast amounts of complex data to make sound decisions. The MS in data analytics focuses on developing and applying data analytics skills to fulfill significant needs in the business community. Students will integrate business concepts as well as key methods and tools for large-size data modeling, analysis and solving challenging problems involving "Big Data." The program provides a strong foundation in data analytics by bringing together salient techniques from statistics, mathematics, computer science, business, accounting, finance and management in a realistic business context.

Goal of Course

  • Compose query statements to implement the data definition and manipulation.
  • Construct multidimensional data cubes analysis.
  • Apply effective methods for analyzing, presenting and using informational data.
  • Develop meaningful reports and visualization of business data analytics appropriate to a technical and non-technical audience.
  • Articulate forecasting and predictive models for real-world analytical applications.

Key Modules

  • Effective usage of MS Excel
  • Querying Database with MS SQL Server
  • Data Reporting with MS Power Bi
  • Data Handling with Python Programming

Introduction to Data Science - Advanced Analytics

  • Relevance in industry & need of the hour
  • Types of analytics – Marketing, Risk, Operations, etc
  • Business & Technology drivers for analytics
  • Future of analytics & critical requirement
  • Types of problems and business objectives in various industries
  • Different phases of Analytics Project

Effective usage of MS Excel

  • Working with Math, Text, and Date functions
  • Working with IF based Conditions
  • Working with VLookup/HLookup Function
  • Working with Data Validation, Sparklines
  • Working with Conditional Formatting
  • Working with What-If Analysis
  • Working Pivot Table for Data Summarization
  • Implementing Security in Excel File
  • Working with Chart & Dashboard

Querying Database with MS SQL Server

  • SQL Overview, and building the Database Schema
  • Protecting data integrity with constraints
  • Manipulating Data
  • Writing Single & Multi Table Queries
  • Combining results with set operators
  • Employing Functions in Data Retrieval
  • Performing analysis with aggregate functions
  • TSQL Programming, Triggers , Exception Handling

Data Reporting with MS Power Bi

  • Importing Data in MS Power Bi
  • Implementing Data Modeling
  • Managing Queries
  • Creating Charts
  • Using Data Filter Option
  • Creating Conditional Column, DAX
  • Creating Dashboard
  • Publishing Dashboards and Charts

Data Handling with Python Programming

  • Statistics Fundamentals Recap
  • Working with Collections
  • Conditional Statements, Loops, Functions
  • File Handling , Managing MySQL Database
  • Exception/Error Handling
  • Python Library - Pandas, NumPy
  • Python Library - Matplotlib, Seaborn, Plotly
  • API Connectivity, Web Scraping

Note :you can speak to our team for detailed content and available batch timings.