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Excel for Data Analysis. Learn the Art of Excel Analytics.

Name: Excel for Data Analysis. Learn the Art of Excel Analytics.
Rating: 3.8 (50 reviews)

Learn the art of data science using Excel. Do the data analytics and Visualizations. Best Data Literacy Course in Excel.

Created byPiyush S | insightEdge100.com

Last updated 10/2024

English

What you'll learn

Art of Data Analysis on the Real world data sets.
Data manipulation techniques and reporting to business users.
Ways and techniques to find the business insights from the raw data.
Data Visualisazations , Pivot , Vlookup etc.
Complex formulae , sorting and filtering with short cut keys
Acquisition Analytics to find out which customer segment is the profitable
Report making techniques for business users.
Investment Case Study to identify the top3 countries and investment type to help the Asset Management Company to understand the global trends

Course content

10 sections • 60 lectures • 4h 26m total length

Course Outline1:40
Understanding Excel Interface - 14:20
Understanding Excel Interface - 24:39
Basic Excel formatting : IMDB Movies -110:34
Format IMDb movies data in Excel by centering headers, applying borders, wrapping text, and setting date and currency formats; use shortcuts to navigate and edit cells for clean analysis.
Basic Excel formatting : IMDB Movies - 210:06
Formulae start with an equal sign '='. Recall that:
Cells are named as a combination of the respective rows and columns i.e. the cell at the intersection of Column A and Row 2 is named as A2.
Formulae can use cell references. Copy and Pasting formulae adjust the input cells references appropriately.
Double Click on the Autofill square at the bottom right of a cell to fill an entire range. Excel is smart enough to change the input references for each cell.

Data Understanding, Sorting & Filtering13:19
Key Items in Report Making1:46
Report Making :Conditional Formatting7:11
Report Making : Borders5:45
Report Making : Printing Techniques4:49
Learn to print an Excel sheet efficiently by choosing the right orientation, fitting columns on A4, using print preview and the control p shortcut, with gridlines, headings, and repeating headers.
Report Making : Protecting Files3:58
Learn how to protect Excel workbooks and sheets with passwords, restrict edits, and create clear file names using timestamps to ensure secure, searchable data analysis reports.
Shortcut Keys Tricks for Excel Data Analysis2:54
Keyboard Shortcut (Windows) Meaning
Ctrl + C : Copy
Ctrl + V : Paste
Ctrl + X : Cut
Ctrl + Alt + V : Open Paste Special Dialog Box
Ctrl + Z : Undo last activity
Ctrl + Y : Redo Last Activity
Ctrl + ↑ : Go to the top of a column
Ctrl + ↓ : Go to the bottom of a column
Ctrl + → : Go the right(end) of a row
Ctrl + ← : Go to the left (beginning) of a row
Shift + Arrow Keys (← ↑ → ↓) : Select cells in the direction of movement
Shift + Ctrl + Arrow Keys (← ↑ → ↓) : Select all cells in the direction of the arrow keys
E.g.: Shift + Ctrl + ↓ : Select all cells from current cell to the bottom of the column

Ctrl + S : Save
Ctrl + P : Print
Ctrl + Shift + L : Filter
Discover shortcuts by using Alt keys
○ E.g.: Alt + P + V - Show Print Preview
○ E.g.: Alt + H + S + F - Filter

Introduction to Acquisition Analytics2:00
Telemarketing Case Study:
The datasets contains information of abount 45000 customers and their historical reponse to products offered by bank.The objective is the find those segments who are likely to purchase bank products in future.
This is the most common analytics across the industries . The usual purpose is the increase the sales of the products and reduce the cost of marketing . Instead of calling everyone and trying to sales , the tele-marketing channels will call only few customers and make as much sale.
Data Understanding of Telemarketing Datasets2:20
Data Understanding of Telemarketing Datasets - 23:36
Explore the banks' telemarketing dataset to identify customer profiles most likely to buy, using demographic data and contact details. Predict future campaign responses to guide acquisition and marketing insights.
Segmentation Techniques and Excel Formulae8:27
Response Rate Calculation and Replace Techniques5:15
Univariate Analysis -15:34
Univariate Analysis -25:00
Multivariate Analysis - 13:51
Multivariate Analysis - 25:13
Logical Operators4:01

Introduction to Excel Charts1:56
Bar Plot - 16:26
Bar Plot - 25:15
Bar Plot - 32:55
Different types of Plots3:50
How and Where to use Plots3:02
Explore when to use column, line, bar, pie, and scatter plots in Excel to reveal trends, compare categories, and enhance readability for actionable insights.
Real Life Project Example2:29
Analyze fraud claims in life insurance using bar plots and box plots to reveal age-based patterns and distinguish fraudulent from legal claims.

Introduction to Pivots1:07
Pivot Tables-13:15
Learn to use pivot tables to compute and format average response rates as a percentage by categories such as marital status and education, enabling quick, formula-free data analysis.
Pivot Tables-25:26
Pivot Tables-32:06
Create pivot tables to summarize data, drag the response rate to values, and apply conditional formatting to highlight trends and exceptions; ensure the sample count exceeds 30 for population-level analysis.
Filter in Pivot6:41

Introduction to Vlookup2:23
Vlookup from within the Sheets - 14:22
Use vlookup to merge data from two sheets by matching a common column, returning salaries for occupations with exact match and absolute references.
Vlookup from within the Sheets - 21:21
Name the salary column on sheet one as salary one, then use Vlookup to look up values from that named range, simplifying the formula.
Vlookup from Different Excel3:37
Learn to perform vlookup from a different workbook, concatenate marital and education data into a single key, and correctly reference lookup columns and directories to determine qualified yes or no.

Introduction to Investment Case Studies2:27
This investment case study uses company, investment, and mapping data to identify top English-speaking countries and leading company categories for a 5-15 billion USD startup investment.
Understanding Case Studies and Downloads1:00
Assignment Solutions:Data Preparation-16:49
Data Preparation - 27:07
Data Preparation - 31:41
Data Preparation - 46:40
Data Preparation - 55:09
Country Wise Analysis6:03
Investment Type Analysis7:56
Company Category Type Analysis6:02
PPT Presentation to Business Users for Data Insights4:25

Why SQL for Data Science?1:06
Discover why sql is a key in data science, as analysts tame massive data from platforms like Facebook, Twitter, and Gmail, unlock insights, and boost earning potential beyond 100k.
Database Concept1:15
SQL Concept2:35
Explore the SQL concept and how a database engine retrieves data from a server in response to a command, with examples illustrating data manipulation language and common definition language.
Write your 1st SQL1:15
Introduction to SQL with Python and R2:08
Learn to connect Python and R to an RDBMS, run SQL queries, and extract data for analysis and visualization using relevant libraries.
Understanding Machine Learning2:04
Explore how machine learning uses historical data to predict loan defaults and classify emails as spam, while distinguishing regression and classification (supervised) from clustering (unsupervised).
Introduction to Linear Regression2:53

Requirements

Students must be passionate about data

Description

**** Testimonials ****

This is a great course for those who want to start data science --Sangwe Bertrand Ngwa

Basics are well explained laying the foundation for excel analytics . Looking forward to it--Himanshu Negi

**** Lifetime access to course materials . 100% money back guarantee. Best course for data literacy for absolute beginners ****

1. Learn basic and advanced functionalities in Excel.

2. Learn how to do data manipulation and analysis to solve real world business problems using case studies.

3. Start using pivot tables and Vlookup like a pro.

4. Start using built-in formulae in excel for the data analysis.

5. Learn how to find interesting trends in the real world datasets.

6. Increase data literacy.

7. Learn to make various charts for effective data visualizations.

8. Learn how to infer hidden insights from data using plots.

Real World Case Studies include :

Acquisition Analytics on the Telemarketing datasets : Find out which customers are most likely to buy future bank products using tele channel.

Investment Case Studies: To identify the top3 countries and investment type to help the Asset Management Company to understand the global trends

Data Analysis on Ireland Loan Datasets : Find out which customers are good or bad and who are likely to repay the loan.

Who this course is for:

Beginners who are looking to enhance their data science skills
Those who want to switch the career in data science

Excel for Data Analysis. Learn the Art of Excel Analytics.

What you'll learn

Explore related topics

Course content

Introduction5 lectures • 31min

Advance Excel2 lectures • 15min

Report Making with Loan Data Sets7 lectures • 40min

Case Study -Acquisition Analytics10 lectures • 45min

Data Visualisations7 lectures • 26min

Data Analytics with Pivot Tables5 lectures • 19min

Data Analytics with Vlookup4 lectures • 12min

Common Errors in Excel and Ways to Mitigate2 lectures • 11min

Investment Case Study for an Asset Management Firm11 lectures • 55min

Understanding Basics of SQL , R , Python7 lectures • 13min

Requirements

Description

Who this course is for: