Data Analytics Course with Excel

Power packed Business Analytics course designed for professionals who want to explore career options in Analytics & Data Science

This course will be ideal:


  • Professional working in IT or any core industry in domains like finance, sales, supply chain, CRM etc.
  • Anyone looking to learn the business analytics but has no prior knowledge of analytics, statistics
  • Anyone who wants to working in Data Science or Business Analytics, Data Visualization
  • Course covers fundamentals of statistics, probability and Analytics, making it apt for professional looking to enter in the field of analytics, business manager who want to understand overall approach without going into programming side of it

    Contextualized course contents with real World Problems to explain concepts


According to IBM, the number of jobs for data professionals in the U.S will increase to 2,720,000 by 2020.
As per Glassdoor, The national average salary for a Data Analytics Analyst is $78,819 in United States.
As per ANALYTICS INDIA SALARY STUDY 2019, Analytics professionals earn 26% more than software engineers in India


Course will help you add skills to your profile
  • Basic Statistical concepts
  • Types of data
  • Data Sampling Techniques
  • Data Manipulation
  • Data Cleaning
  • Data Mapping
  • Data Visualization……


  • Exploratory Data Analysis
  • Hypothesis Testing
  • Linear Regression
  • Multi Linear Regression
  • Time Series Forecasting
  • Dashboards and Reports
  • Excel Storyboarding…….

What you'll Learn

  • In this course, you will learn the importance of data in business
  • Data manipulation, data cleaning, data mapping, exploratory data analysis, data modelling
  • Apply suitable analytic techniques
  • Real world problem solution with data driven decisioning using Excel
  • Discover how to tell a powerful story with data to drive business action
  • Learn how to use data analysis to detect fraud
  • Learn how financial services can apply data analysis to solve real world problems



Target audiences : who should opt for this course

Course is beneficial for both beginners and experienced professionals who are inexperienced or have recently stepped into the field of analytics. Course will help you enhance value of your profile if you are performing any of these roles:

  • Data analysts
  • Junior data scientists
  • Analytics professionals
  • BI and reporting professionals
  • IT developers and testers
  • Project managers
  • Starting your career or Students
  • Operations or business support
  • Professionals working with data in any industry


Business Data analytics with Excel - Course Syllabus



Module 1: Introduction to Business Analytics

• What is Analytics?

• Applications of Analytics: Sample Case studies across industries

• Types of Analytics: Descriptive, Predictive, Prescriptive

• Difference between business analytics and business intelligence

• RPopular tools

Module 2: Data Wrangling using Excel

• Data Manipulation ( Basic functions, If else, date functions, table, filter, Sort etc.)

• Data Cleaning ( Concatenate, left, right, mid, trim, uppercase, lowercase, find, search, Len, replace, and, or, char, substitute, conditional formatting etc.)

• Data Mapping ( V lookup, H lookup, Index Match, offset, named ranges, dropdowns, etc.)

• Case Study

Module 3: Exploratory Data Analysis using Excel

• Aggregating data using Pivot, Calculated Fields

• Data Visualization

• Slicers

• Case Study

Module 4: Statistics with Excel

• Basic Statistics, Introduction to Measures of Central Tendency, Types of data & variables, Probability, Distribution Types, Confidence Interval

• Descriptive Statistics

• Sample, Population, Measures of central tendency

• Hypothesis Testing

• Test of proportion, Test of means, T testing, Type 1 and type 2 error

• Correlation and Covariance

• Case Study: Decision making using advanced excel

Module 5: Data Modelling using Excel

• Linear Regression

• Multiple Linear Regression

• Time Series Forecasting

• Case study: Modelling using Excel

Module 6: Data Visualization

• Basic Charts and Reports

• Dimensions and Measures

• Dashboard design and techniques

• Storyboarding

• Case study: Dashboard designing

Course project

Retail Store chain transformation

Business Intelligence (BI) tools are adopted by more and more companies in the current environment that requires companies to operate as efficiently as possible. The case study investigates a BI adoption in a retail chain. Based on qualitative research methods, it analyses the Business Intelligence life cycle; it evaluates factors impacting the adoption from the Diffusion of Innovations perspective.

The present study tried to help the upcoming retail store to solve the problem of transformation from traditional way of doing business to the digital way. Automate the data collection where available and create integrated set of dashboards that will free up time for the business analysts to get away from some report production time and spend more time on analysis that will greatly benefit the business in the long-term.



Course Certification

At the end you will get course certification from Techcanvass and assessment report on your assignment and projects

In order to get certification of completion:


  • Submit the all class assignment
  • Complete and submit training project
case_study



Business Data Analytics With Excel fee details



Business Data Analytics With Excel
(Live Online Training)
  • Live online training (Weekends)
  • 4 weekends course
  • TechEdge portal access – 1 year
  • Case study
  • Course Projects




Course Price (GST Extra)

Currency:



₹ 14,000

₹ 16,000

(2000/- OFF)

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Upcoming Batches Schedule


Time Zone:



Start Date Days Timings
05 September 2020 Sat -Sunday (EDT/PDT/IST) 07:30 AM - 09:30 AM (IST) Live Online Training
03 October 2020 Sat - Sunday (EST/PST/IST) 07:30 AM - 09:30 AM (IST) Live Online Training
07 November 2020 Sat - Sunday (EDT/PDT/IST) 07:30 AM - 09:30 AM (IST) Live Online Training
05 December 2020 Sat - Sunday (EDT/PDT/IST) 07:30 AM - 09:30 AM (IST) Live Online Training



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