This document provides an overview of an elementary data analysis course using MS Excel. The 6-day course will introduce basic concepts like data, data types, and data analysis processes. It will cover collecting, cleaning, and analyzing data in Excel. Topics will include functions, formulas, charts, pivot tables, and more. The goal is to help professionals and students better understand and utilize data through hands-on Excel training and examples.

1. Elementary Data Analysis
with MS Excel
Redwan Ferdous
Electrical Engineer| Tech Enthusiast| Robotics | Automobile| Data Science |
Tech-Entrepreneur & Investor |
redwan.contact@gmail.com | ferdousr@emk.com.bd
https://sites.google.com/view/redwanferdous
Day: 01 out of 06 | September 2nd, 2020

2. 9/2/2020 2
What do you think about ‘Data Analysis’ and ‘Visualization’?

3. 9/2/2020 3

4. Disclaimer
• You need not to reinvent wheel all the time, rather its better to
create application using that wheel !!
• Most of the contents of my slides are collected from internet. Credit
mentioned with due respect at the last slide
• My job is to facilitate the learning, motivate to adopt the beauty of
MS Excel and Data Analysis.
• The learning material is 40%- Slide & 60%- Live session on video
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5. Course Summary
• This course is stated as “Elementary Data Analysis with MS Excel”-
Organized by EMK Center, Dhaka, Bangladesh
• Course Duration: 06 Days. Each Day 2.00 hours.(including FAQ)
• The schedule is subject to be changed based on unavoidable
circumstances (if appears any).
Date Stating Time End Time Platform
Wednesday, September 02, 2020 07.30 pm 09.30 pm Zoom
Saturday, September 05, 2020 07.30 pm 09.30 pm Zoom
Wednesday, September 09, 2020 07.30 pm 09.30 pm Zoom
Saturday, September 12, 2020 07.30 pm 09.30 pm Zoom
Wednesday, September 16, 2020 07.30 pm 09.30 pm Zoom
To Be Announced 07.30 pm 09.30 pm Zoom
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6. Course Summary (cont.-2)
• Each day’s lecture slide can be found on “Slide share” at instructors
profile- after the end of the scheduled lecture.
Link: https://www.slideshare.net/RedwanFerdous/
• The instructor personally do believe the following quote:
“ Keep it Simple
Keep it Short
Keep it Real”
- It will be reflected throughout the course contents and
methodology of sharing the knowledge as well as interaction.
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7. Course Attendee Summary
• Total 99 has been invited from among 321. Only 30.84%
• Most of the attendees are Professionals of different levels. Next major
portion is either Students or Freelancers.
• Selected attendees are finalized based on considering 06 layers of
filter.
Congratulations!!
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8. Course Attendee Summary (cont.)
• Among the participants, there are:
• 20+ Participants who are aged ‘Equal or Above 35’
• 18 Participants are aged among 20-24
• 30+ participants are aged among 25-30
• 09 Students
• 03 Government Service Holders
• 02 Journalists
• 08 Teachers/ Lecturers/ Professors
• 45+ Private Service Holders
• +/- 06 Entrepreneurs
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9. The Course Leads you:
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60%
40%
0% 10% 20% 30% 40% 50% 60% 70%
LEARNING EXTENSIVE USE OF MS EXCEL AS A TOOL:
DATA ANALYZE AND VISUALIZE
Upon Completion of 06 days Training:

10. Course Outline
• This is a very basic and summarized course specially designed for the
working people or SME owners for the betterment of their day-to-day
activities with the help of ‘Data’ and ‘Analysis’.
• Course Outline:
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- What is Data, Data Analysis, Data Vs. Information
- Regular life data analyzer Vs. Data
- Sources of Data in real life and online
- Statistics, Data
- Types of Data Source (CSV, Excel)
- Basic Terminology for Data Analysis using MS Excel
- Big Data, Minitab
- Career
- File Options
- Workbook, Worksheets
- Cells, Ranges, Keyboard Shortcut
- Ribbon Engagement:
- Home
- Insert
- Page Layout and Setup
- Basic Functions and Practices [+ Examples]

11. Course Outline (cont.)
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(IF, Nested IF, VLOOKUP, HLOOKUP)
- Formulas and Functions
- List of Formulas
- 15 Important Functions for Data Analysis+ Practice
- Error Handling [Formula]
- Data Validation
- Developer Mode Enable
- Macro
- Ribbon Engagement:
- Data
- What-If Analysis
- Review
- View
- Developer
- Random Number
- Crystal ball
- Freeze Pane
- Data Analysis Tools
- Quick Analysis
- Pareto Test

12. Course Outline (cont.)
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- Statistics, Hypothesis
- Regression Analysis, Trend Line
- T-Test
- Solver
- Goal Seek
- Idea : Z-Test, ANOVA Test, P-Value
- Pivot Table and Interactive Dashboard, Charts
- Pivot Table with Open Office Platform
- Introduction to MS Access
- Creating and Using a Complete Database using MS
Access
- Basics of Probability, Entropy, Model Development
[Part of Advance]
- Tableau, Qlik, Octave
- Practical Example of Forecasting using the model
building [advanced]
- Bonus Training!

13. Course Outline (cont.)
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Submission of final project by the participants and send the evaluation
result virtually by EMK/instructor.

14. Decorum for Attendee
• This 06 days session will be a semi-formal session. The instructor is
very much fun loving, believe me!
• You can ask question either in the end of the session or during the
demonstration.
• Whenever you are not talking, please MUTE your microphone. You
can switch your video off during observing live demonstration for
better experience.
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15. Decorum for Attendee (cont.)
• All the attendee will try to practice live with the instructor – that is
showed on shared screen on the platform.
• During the live demonstration there might be technical error like
internet disconnection or hanging of host platform- please have
patience on that situation. Everything will be All Right !
• This is a two-way communicating session. Both Instructor and
attendee will learn from each other. Medium –English/Bengali.
• We will learn a lot more than MS Excel & Data Analysis, I do believe !
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16. Decorum for Attendee (cont.)
Please don’t fall asleep!!
Feel Relaxed.
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Let’s Start….

17. 9/2/2020 17
Elementary Data Analysis with MS Excel
Day-01

18. 9/2/2020 18

19. Data
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20. Data Types
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21. Data Vs. Information
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22. Data Vs. Information (cont.)
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23. Data Analysis Process
• The Data Analysis Process is nothing but gathering information by
using a proper application or tool which allows you to explore the
data and find a pattern in it.
• Based on that information and data, you can make decisions, or you
can get ultimate conclusions.
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24. Data Analysis Process (cont.)
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25. Data Analysis Process (cont.)
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Simpler Form

26. Data Analysis Process (cont.)
• So, Data Analytics Process includes:
• Data Collection
• Working on data quality
• Building the model
• Training model
• Running the model with full data.
• Visualize Relation
• Some tips to analyze the data are:
• Remove unnecessary data before the analysis.
• You should not perform the analysis on a master copy of data.
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29. Data Mining
Vs.
Data Analytics
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30. Why ‘Data Analysis’?
• If you know Six Sigma/Lean Process of Six Sigma-
it follows a framework DMAIC
[Define, Measure, Analyze, Improve and Control]
• DMAIC refers to a data-driven improvement
cycle used for improving, optimizing and stabilizing
business processes and designs.
• The ‘M’ & ‘A’ part is redirected to ‘Data Analysis’ part.
• It is one of the compulsory item for ensuring quality, timely, efficient
and waste less – Production and Industrial Procedure.
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31. ‘Data Scientist’ Vs. ‘Data Analyzer’
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32. Modern Data Scientist
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33. ‘Regular life Data Analyzer’ Vs. ‘Data Scientist’
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34. Data Analysis Types
The major types among several:
• Text Analysis
• Statistical Analysis
• Diagnostic Analysis
• Predictive Analysis
• Prescriptive Analysis
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35. Data Analysis Types (cont.)
• Text Analysis is also referred to as Data Mining. It is a method to discover a
pattern in large data sets using databases or data mining tools.
• Statistical Analysis shows "What happen?" by using past data in the form
of dashboards. It’s of 02 types:
• Descriptive
• Inferential
• Diagnostic Analysis shows "Why did it happen?" by finding the cause from
the insight found in Statistical Analysis.
• Predictive Analysis shows "what is likely to happen" by using previous
data.
• Prescriptive Analysis combines the insight from all previous Analysis to
determine which action to take in a current problem or decision.
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36. Data Visualization
• More likely ‘Information’ Visualization.
• Data visualization is the representation of data in a graphical or
pictorial format. It allows key decision-makers to see complex
analytics in a visual layout, so they can identify new patterns or grasp
challenging concepts.
• When you have your hands full juggling multiple projects at once, you
need a quick and effective reporting method that allows you to get a
clear point across.
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37. Types of Data Visualization (Most Common)
• Column Chart
• Bar Graph
• Stacked Bar Graph
• Stacked Column Chart
• Area Chart
• Dual Axis Chart
• Line Graph
• Mekko Chart
• Waterfall Chart
• Bubble Chart
• Scatter Plot Chart
• Bullet Graph
• Funnel Chart
• Heat Map
• Box Plot
• Pie Chart
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38. Types of Data Visualization (Most Common)
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39. Business Intelligence
• The term Business Intelligence (BI) refers to technologies, applications and
practices for the collection, integration, analysis, and presentation of
business information.
• The purpose of Business Intelligence is to support better business decision
making. Essentially, Business Intelligence systems are data-driven Decision
Support Systems (DSS).
• Business Intelligence is sometimes used interchangeably with briefing
books, report and query tools and executive information systems.
• The global Business Intelligence and Analytics Software Market is
expected to grow from $17.90 Billion in 2015 to $26.78 Billion by 2020, at
an estimated Compound Annual Growth Rate (CAGR) of 8.4%.
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40. Business Intelligence Tools
1. SAP Business Intelligence
2. MicroStrategy
3. Datapine
4. SAS Business Intelligence
5. Yellowfin BI
6. QlikSense
7. Zoho Analytics
8. Sisense
9. Microsoft Power BI
10. Looker
11. Clear Analytics
12. Tableau
13. Oracle BI
14. Domo
15. IBM Cognos Analytics
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41. Business Intelligence Tools
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Oracle BI

42. Business Intelligence Tools
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Tableau

43. Business Intelligence Tools
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Clear Analytics

44. Business Intelligence Tools
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Microsoft Power BI

45. Business Intelligence Vs. Data Science
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46. Big Data
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47. Big Data
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48. Data Analysis Software/ Tools
• MS Excel
[sometimes ‘Calc’ from LibreOffice]
• SPSS (IBM SPSS)
• R (Language)
• Atlas.ti
• JMP
• QlikView
• Tableau [Required mostly in Big Data/ Hadoop Cluster]
• Microsoft BI (Business Intelligence)
• RapidMiner
• Check some comparison of tools: https://www.softwaretestinghelp.com/data-analysis-tools/
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49. Introduction to MS Excel
• The version of MS Excel on instructor’s PC is 2013. You can use any of
2007/ 2010/ 2013/ 2019.
• Microsoft Excel is a spreadsheet program that is used to record and
analyze numerical data.
Think of a spreadsheet as a collection of columns and rows that form
a table.
• Alphabetical letters are usually assigned to columns and numbers are
usually assigned to rows.
• The point where a column and a row meet is called a cell.
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50. ‘Excel’ in LibreOffice [Open Office]
• ‘Calc’ is the spreadsheet program of LibreOffice, which is a Open-
Source Platform
• Currently the version 7.0.x is going on of LibreOffice
• Their Theme is ‘The Spreadsheet for everyone’
• It can also analyze data using it’s ‘Advanced DataPilot technology’
• Can do almost all the operations like MS Excel
• While Calc saves spreadsheets in its native Open Document Format
(.ods), it can also open and save files in Microsoft Excel format for
sending to people still locked into Microsoft products.
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51. ‘Excel’ in LibreOffice [Open Office]
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52. Minitab
• Minitab is a software product that helps you to analyze the data. This is
designed essentially for the Six Sigma professionals. It provides a simple,
effective way to input the statistical data, manipulate that data, identify
trends and patterns, and then extrapolate answers to the current issues.
• MiniTab Inc. is one of the dominant providers of the statistical software for
quality improvement.
• Minitab is not for all types of users. It is specially designed for the six
sigma professionals.
• They use Minitab to analyze the data, and on the basis of their analyzation,
they improve the business process. The six sigma is all about quality
management techniques.
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53. Minitab (Cont.) – Demo Interface
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54. Minitab vs. MS Excel
Features of MS Excel Features of Minitab
1. Conditional Formatting
2. PivotTables
3. Paste Special
4. Add Multiple Rows
5. Absolute References
6. Print Optimization
7. Extend formula across/down
8. Flash Fill
9. INDEX-MATCH
10. Filters
1. Measurement systems analysis
2. Contour and rotating 3D plots
3. Analysis of Variance
4. Linear and nonlinear regression
5. Binary, ordinal and nominal logistic regression
6. Measurement Systems Analysis
7. Exact failure, right-, left-, and interval-censored
data
8. Random number generator
9. Extensive preferences and user profiles
10. Chi-square, Fisher’s accurate, and other tests
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55. Jobs with MS Excel Jobs with Minitab
1. Financial Analysts
2. Administrative Assistants
3. Retail Store Managers
4. Project Managers
5. Business Analysts
6. Data Journalists
7. Accountants
8. Cost Estimator
9. Sales Manager
10. Information Clerk
1. Quality Manager
2. Project Development Engineer
3. Sales Management Advisor
4. Data Analyst
5. Design Engineer
6. Process Improvement Manager
7. Quality Assurance Specialist
8. Senior Automotive Engineer
9. Manufacturing Engineer
10. Power Supply Quality Analyst
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Minitab vs. MS Excel

56. Sources of Data in real life and online
• Mainly 02 types of Data-Sources:
• Primary &
• Secondary
• Primary Data Collection:
Primary data sources include information collected and processed directly by the
researcher, such as observations, surveys, interviews, and focus groups.
• Secondary Data Collection:
Secondary data sources include information retrieved through preexisting sources:
research articles, Internet or library searches, etc. Preexisting data may also include
records and data already within the program: publications and training materials,
financial records, student/client data, performance reviews of staff, etc.
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57. Types of Data Source
• Mainly in 02 format:
• .CSV
• .xlsx / .xls
• There are some other based on Excel and other data analyzing software. You
may need to convert the dataset in a format required for that particular
analyzer.
• Out test datasets (Sample Dataset (1~10+) and Dataset-Mega) will be
.xlsx format for easy understanding
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58. Source of Data
How can you collect your data: (SME/ Industry)
• Implementing ERP (e.g. SAP/Oracle/Freeware)
• Implementing Accounting Software (e.g. Qucikbooks)
• Enable E-Commerce
• Enable Digital Money (Credit Card/ MFS)
• Deploying Separate Entry and Exit with Human Counter
• Digital Inventory Management
• Loyalty / Membership Card
• Digital SCM etc.
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59. Some Sample Data Sources [Practice]
• We will use 10+ sample datasets throughout our course.
• Dataset (1~10+): [for class 02-05]
• Comparatively Small. Uploaded in Google Classroom on or before the class day.
• Dataset-Mega: [for class 05]
We will try to use this in the class. If we can’t due to time, it will be in Assignment.
• Our Practice Dataset is a sample superstore sales data, collected from internet.
• In XLSX format, not curated. Comparatively large.
• It consists of almost 10,000 rows and 21 columns.
• It will be uploaded in Google Classroom
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60. Some Sample Data Sources [Practice]
• Google/ Kaggle
• WHO- https://www.who.int/healthinfo/statistics/data/en/
• Contextures- https://www.contextures.com/xlSampleData01.html
• E for Excel- http://eforexcel.com/wp/downloads-18-sample-csv-files-data-
sets-for-testing-sales/
• John Hopkins Dataset for COVID-19
And thousands more……
• You also can create your own set of data for better observation!
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61. Basic Terminology for Data Analysis using MS Excel
The powerful features Excel has to offer to analyze data:
• Sort: You can sort your Excel data on one column or multiple columns. You
can sort in ascending or descending order.
• Filter: Filter your Excel data if you only want to display records that meet
certain criteria.
• Conditional Formatting: Conditional formatting in Excel enables you to
highlight cells with a certain color, depending on the cell's value.
• Charts: A simple Excel chart can say more than a sheet full of numbers. As
you'll see, creating charts is very easy.
• Pivot Tables: Pivot tables are one of Excel's most powerful features. A pivot
table allows you to extract the significance from a large, detailed data set.
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62. Basic Terminology for Data Analysis using MS Excel
• Tables: Tables allow you to analyze your data in Excel quickly and
easily.
• What-If Analysis: What-If Analysis in Excel allows you to try out
different values (scenarios) for formulas.
• Solver: Excel includes a tool called solver that uses techniques from
the operations research to find optimal solutions for all kind of
decision problems.
• Analysis ToolPak: The Analysis ToolPak is an Excel add-in program
that provides data analysis tools for financial, statistical and
engineering data analysis.
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63. Career: As ‘Data Analyzer’ in MS Excel
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64. Career: As ‘Data Analyzer’ in MS Excel
• We will check some freelancing site for the status of ‘Data Analyst in
MS Excel’, Live:
• Upwork
• Freelancer.com
• Moreover, we will google “Current market for data analyst in MS Excel”
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65. Though, your path may not be smoother…
• Until you have proper knowledge, expertise, passion and vision.
9/2/2020 65

66. Bibliography
• https://www.guru99.com/introduction-to-microsoft-excel.html
• https://cyfar.org/data-sources
• https://libguides.macalester.edu/c.php?g=527786&p=3608657
• https://www.computerhope.com/issues/ch000357.htm
• https://www.datapine.com/blog/wp-content/uploads/2018/12/data-science-vs-data-analytics-difference.png
• http://datascientistyuyuria.blogspot.com/2017/01/difference-between-data-analyst-and.html
• https://www.guru99.com/difference-information-data.html
• https://www.twinkl.fr/teaching-wiki/data
• https://i.stack.imgur.com/UTmOm.gif
• https://sigmatricks.com/wp-content/uploads/2019/05/Discrete-and-Continuous-Data.jpg
• https://lh3.googleusercontent.com/proxy/Z2d6RFEAAt6hSbuQEzL3I2jUPw7fz0IKoTyMIYOJNuqplghnqNX8yyyqknBnP-
vsF4XQjXIsHlS67urJ60RSK87GdW35RHR2zGTezXQx4UIv0szs1Q37zUma_qFC2XAkUTg_MSj7SiSjEj6ik-IazdRVke1z
• https://www.softwaretestinghelp.com/data-analysis-tools/
• https://www.visualcapitalist.com/wp-content/uploads/2019/07/big-data-graphic.jpg
• https://www.globaldots.com/hs-fs/hubfs/Imported_Blog_Media/big-data-infographic-1-
728.jpg?width=728&height=406&name=big-data-infographic-1-728.jpg
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67. Bibliography
• https://encrypted-tbn0.gstatic.com/images?q=tbn%3AANd9GcSkM6dHyCLSnqMbLj4z2a_eM5VrnxrouKQQng&usqp=CAU
• https://www.researchgate.net/profile/Abbas_Wahab/publication/330988181/figure/fig1/AS:724465180762112@1549737367087
/Knowledge-Discovery-in-Database-KDD-Process.png
• https://community.tableau.com/s/question/0D54T00000CWeX8SAL/sample-superstore-sales-excelxls
• https://static8.depositphotos.com/1023803/970/i/450/depositphotos_9707546-stock-photo-analyzing-data-on-computer.jpg
• https://encrypted-tbn0.gstatic.com/images?q=tbn%3AANd9GcQsf0zs4m-tSzsUOJdNPR2UhmqUlGiFo07I6A&usqp=CAU
• https://www.excel-easy.com/data-analysis.html
• https://revolution-computing.typepad.com/.a/6a010534b1db25970b01901c38e94d970b-pi
• https://mopinion.com/business-intelligence-bi-tools-overview/
• https://olap.com/learn-bi-olap/olap-bi-definitions/business-intelligence/
• https://www.greycampus.com/opencampus/minitab/introduction-on-minitab
• https://statanalytica.com/blog/excel-vs-minitab/
• https://www.ktvn.com/story/41067230/the-top-10-types-of-data-visualization-made-simple
• https://www.guru99.com/what-is-data-analysis.html
• https://www.datapine.com/blog/data-analysis-methods-and-techniques/
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68. Anything you want me to tell?
Thank You
See you on next class…
9/2/2020 68
Lets try to learn, in every second.