Data Analytics (WTP)

2,966.10 Taxes as Applicable(GST)

Course Overview

Course Duration: 100 Hrs. (Concepts + Hands-on Practices + Assignments )

Overview:

The data analytics course provides fundamental concepts of data analytics through real world case studies and examples and gives insights into how to apply data and analytics principles in your business. You’ll learn about project lifecycles, the difference between data analytics, data science, and machine learning; building an analytics framework, and using analytics tools to draw business insights.

Target Audience:

This course is ideal for anyone who wishes to learn the fundamentals of data analytics and pursue a career in this growing field. The course also caters to CXO-level and middle management professionals who want to improve their ability to derive business value and ROI from analytics.

 

Key Learning Outcomes:

When you complete this Introduction to Data Analytics course, you will be able to accomplish the following:

  • Understand how to solve analytical problems in real-world scenarios
  • Define effective objectives for analytics projects
  • Work with different types of data
  • Understand the importance of data visualization to drive more effective business decisions and ROI
  • Understand charts, graphs, and tools used for analytics and use them to gain valuable insights
  • Create an analytics adoption framework Identify upcoming trends in data analytics

Delivery Mode:

 

  • Online Live Instructor led learning.

Syllabus

Module 01 – Data Analytics Overview

 

  • Introduction
  • Data Analytics: Importance
  • Digital Analytics: Impact on Accounting
  • Data Analytics Overview
  • Types of Data Analytics
  • Descriptive Analytics
  • Diagnostic Analytics
  • Predictive Analytics
  • Prescriptive Analytics
  • Data Analytics: Amazon Example
  • Data Analytics Benefits: Decision-making
  • Data Analytics Benefits: Cost Reduction
  • Data Analytics Benefits: Amazon Example
  • Data Analytics: Other Benefits
  • Key Takeaways

 

Module 02 – Dealing with Different Types of Data

 

  • Introduction
  • Terminologies in Data Analytics – Part One
  • Terminologies in Data Analytics – Part Two
  • Types of Data
  • Qualitative and Quantitative Data
  • Data Levels of Measurement
  • Normal Distribution of Data
  • Statistical Parameters
  • Key Takeaways

 

Module 03 – Business Analytics with Excel

  • Functions and Formulas
  • Formulas with Multiple Operators
  • Inserting and Editing a Function
  • Auto Calculate and Manual Calculation
  • Defining Names
  • Using and Managing Defined Names
  • Displaying and Tracing Formulas
  • Understanding Formula Errors
  • Using Logical Functions (IF)
  • Using Financial Functions (PMT)
  • Using Database Functions (DSUM)
  • Using Lookup Functions (VLOOKUP)
  • User Defined and Compatibility Functions
  • Financial Functions
  • Date & Time Functions
  • Math & Trig Functions
  • Statistical Functions
  • Lookup & Reference Functions
  • Database Functions
  • Text Functions
  • Logical Functions
  • Information Functions
  • Engineering and Cube Functions

 

  • Working with Data Ranges
    • Sorting by One Column
    • Sorting by Colors or Icons
    • Sorting by Multiple Columns
    • Sorting by a Custom List
    • Filtering Data
    • Creating a Custom AutoFilter
    • Using an Advanced Filter
  • Working with PivotTables
  • Creating a PivotTable
  • Specifying PivotTable Data
  • Changing a PivotTable’s Calculation
  • Filtering and Sorting a PivotTable
  • Working with PivotTable Layout
  • Grouping PivotTable Items
  • Updating a PivotTable
  • Formatting a PivotTable
  • Creating a PivotChart
  • Using Slicers
  • Sharing Slicers Between PivotTables

 

  • Analyzing and Organizing Data
    • Creating Scenarios
    • Creating a Scenario Report
    • Working with Data Tables
    • Using Goal Seek
    • Using Solver
    • Using Text to Columns
    • Grouping and Outlining Data
    • Using Subtotals
    • Consolidating Data by Position or Category
    • Consolidating Data Using Formulas
  • Working with the Web and External Data
    • Inserting a Hyperlink
    • Importing Data from an Access Database or Text File
    • Importing Data from the Web and Other Sources
    • Working with Existing Data Connections
  • Customizing Excel
    • Customizing the Ribbon
    • Customizing the Quick Access Toolbar
    • Using and Customizing AutoCorrect
    • Changing Excel’s Default Options
    • Creating a Custom AutoFill List
    • Creating a Custom Number Format
  • Working on Live Data and Dashboards
    • Creating dashboards on company specific data
    • Working on Live data
    • Dashboards with the help of Developer Ribbon.
    • Working with critical & Complex formulas
  • Module 04 – Tableau
  • Understand how Tableau Desktop fits within the Tableau family of products
  • Combine data sources for use by Tableau
  • Connect to a variety of sources including flat files and databases
  • Understand data types and roles
  • Use key operations in Tableau – filtering, sorting, grouping and creating sets
  • Work with extracts (file formats used by Tableau)
  • Build and format data visualizations
  • Work with maps and location-based data
  • Create interactive dashboards by using parameters, calculations and actions
  • Publish dashboards and visualizations
  • Working with bins, groups and parameters
  • Working with folders
  • Creating story

Prerequisite

This Introduction to Data Analytics course has been designed for all levels, regardless of prior knowledge of analytics, statistics, or coding. Familiarity with mathematics is helpful for this course.

General Information
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