DEV Community: Hemstone Gogo

Getting Started with Excel for Data Analytics: From Basics to Data Cleaning.

Hemstone Gogo — Mon, 31 Aug 2026 06:50:10 +0000

Introduction

Because it combines a well-known spreadsheet interface with functions for data cleansing, validation, organizing, filtering and calculation , Microsoft Excel is one of the easiest tools to learn data analytics. Many of the habits of a competent data analyst can be learned straight in Excel by a biginner before switching to more sophisticated tools like Power BI, SQL or Python. The main concept is straightforward: the accuracy of an analysis depends on the quality of the data used.

Objectives

Navigate the Excel interface confidently i.e the use key components (ribbon, cells, sheets, tabs,rows and columns,).
Understand formatting and data types i.e difference between text, numbers, dates, and currency, and appropriate formatting for correct data representation.
Enter and organize raw data effectively.
Identify and correct common data quality issues
Apply basic formulas and functions.

Understanding Excel and its Environment

The excel environment is formed if form of excel workbook, worksheets, rows and columns and lastly a cell. An Excel workbook is an excel file containig multiple worksheets in this case the Kenya Hospital Health record represents a workbook. A Worksheet consists of columns and rows, in the below attachement staging and Cleaned and consequently their interection will form a cell. In excel each individual cell has a unique address, example A1 in the below attachement.This reference is very important because we use formulas to retrieve and perform calculations.

Maintaining a straightforward rectangular dataset structure one variable per column, one observation per row, and a single header row at the top is crucial for data analytics, for example: patient, first name, last name, ID etc as highlighted below.

Excel Ribbon

This is the toolbar at sitted at the top of Microsoft Excel.It has the commands and tools that a data analysts needs to create,format, edit and analyse data.

The main parts incluse;

File-This is used to open, save, print and finally close excel files.
Home-Has common tools like copy, paste,formatting i.e font and number formattind and alignment.
Insert-Applied when adding tables, pictures,tables,pivottables and objects.
Page Layout-This sets page margins,size,printing options and orientation.
Formulas-Has tools to create and manage functions and formulas.
Data-Sorting, removing duplicates, filtering and data cleaning.
Review-Provides opportunities for spelling checks, worksheet protection and comments.
View-Controls worksheet appearance i.e zooming and additional view options.

Entering, Formatting, and Organizing Data

Excel can save text, numbers, dates, and logical values. Excel processes different types of data differently, thus it is important to choose the correct type. A real Excel date can be sorted chronologically and utilized in calculations, however a date entered in plain text may not perform as expected. Quantity should also be numerical if it is to be utilized in arithmetic.Formatting should convey meaning. Dates should be formatted consistently as dates, prices as numbers, and percentages as percentages.

Entering Data

This is adding information in excel. This data may include text, formulas,numbers and dates.

Data Formatting

Changing the look and appearance of data to easy interpretation and understanding, examples include;

Making column head bold

Add borders

Adjust row or column width
Changing font size

Organizing Data

Arranging data for easy management, retrieving and analysis. The most common command used is Sort and Filter
Data → Sort → Largest to Smallest
Data → Filter → Gender → Female

Identifying and Removing Duplicates

Duplicate records might increase totals. Excel's Data > Remove Duplicates option allows the analyst to select the columns that constitute uniqueness.Before deleting duplicates, determine why they exist. Two similar-looking rows might represent legal independent transactions, therefore duplicate elimination should adhere to a business standard.

Filtering and Sorting Data in Excel.

This are crucial excel skills that helps a data analyst to orgainize and find information in large datasets.

Sorting Data

This is the process of arranging data in a specific order.

Consider the above data set, we can sort:

Patient First Name: A-Z OR Z-A
Age:Largest to Smallest or Smallest to Largest.

Filtering Data

This allows display of specific records which meets a specific conditons while temporarily hidding other records.

In the above dataset we can filter

Patients older than 50
Female patients only.

Data Cleaning

Finding and fixing erroneous, inconsistent, incomplete, duplicated, or improperly structured data is known as data cleaning. It is rare for actual organizational data that is ready for analysis hence data cleainig is very important.

Extra spaces, incorrect capitalization, blank values, text-based integers, inconsistent status values, and duplicate records are always present in any dataset. In this case extra spaces causes data matching problems when creating pivot tables or data visualization. We deploy Excel TRIMfunctions which removes extra spaces.Additonally CLEANis applied to eliminate non-printing data characters.
Case consistency is paramount when cleaning data with names of persons, cities etc. We use PROPER,UPPERand LOWERfor text standardization.

When data is imported from external databases or systems in form of numbers might be stored in text form. These values may look numeric but when formulas are used for calculations, they they behave differently. We deploy excel Text to colums of VALUEto convert numeric text to a number. The below is a summary of the basic data cleaning workflow and as we advance and learn more about excel, we will come across better and complex cleanig procedures.

Import raw data and save it in your project folder.
Inspect the data types and columns
Convert the data range into table
Sort and filter to identify unsual records.
Standardize data by removing unnecessary spaces.
Check the missing values.
Check numeric fields and convert to numeric data types.
Remove duplicates.
Conduct data validation.

Conclusion.

Excel abilities from Week 1 offer a useful basis for data analytics. A beginner data analyst may deal with structured data with confidence if they understand worksheets, cells, tables, formatting, formulas, sorting, and filtering.The key takeaway is straightforward: excellent analysis begins with good data. Excel allows for the practical application of this before advancing to more sophisticated analytics systems.

Understanding the Git Workflow: Working Directory, Staging, Commit and Push

Hemstone Gogo — Sat, 22 Aug 2026 12:21:05 +0000

Introduction

The world is experiencing technological advancement in a very fast pace, hence this article is meant to provide a very simple understanding of Git Workflow for beginners who are stepping in to to the space of software development or BigData. Understanding of Git workflow is important because Git is widely utilized version of control system in most of the software development and data analytics. This is because; t assits developers to monitor and track changes to files they working on,it facilitates collaboration and experimentation of ideas and provides safe platform to main projects in different versins.
In the initial stages Git might seem complex and confusing because of introduction of commands and concepts that we do not encounter in any normal file management workflow.Commands such as working directory, staging area, commit and push.These concepts are very important as they highlight the levels and stages in which changes move and occur when using Git.

Four Main Stages of Git Workflow

The Working Directory

This is simple terms a folder on your PC where all projects lives. Every time a code editor is opened and you start typing, files will be modified in the working directory.At this moment Git is alert and aware however not executing and tracking the changes.
The main action when wanting to view files on the working directory is git status. When this command is typed on the terminal, git will display all list of files which have been changed. At this particular stage however the files are "untracked".

The Staging Area

This is the middle ground in Git i.e a temporal holding zone. This is where one gathers files and saves then in the next version.The Staging Area is very key because you might having 5 changes in 2 diffirent files, however only 2 changes and okay and complete.No one likes incomplete work hence can never save it. The Staging Area provides an opportunity to save selectively.We use the command addthe completed files and leaving the unfinished to the working directory.
The command here is git add <filename>
If all changes have to be added in the current folder, we use the command git add . git takes holds of those particular files and stages them in the Staging Area.

The Local Repository

After all the changes in your files have been staged, they can be saved in the Local Repository. The processing of saving the files is executed by a Commit command which is the most crucial Git command.When you run a "commit" command, it takes the files sitting at the Staging Area, moving and storing them permanently in the Local Repository
Git usually gives every commit a code because each commit is unique. Additionally every commit needs a message. This message highlights the changes made and the reason they were made.
The command used is git commit -m "The Commit Message"
Important points to note;

The commit massage is always in present tense.
Commit are usually permanent ie the version has been saved forever. This can only be reversed by forcing a reset.

The Remote Repository

Up to the local repository, files exist only on your computer.A Remote Repository hosts copy of your files or project on the internet.Examples of platform to host files on the internet are:

Github
Bitbucket
Gitlab
We use the pushcommand to uploading committed changes to the Remote Repository from the Local Repository.
The command to push commits is git push origin <branch-name>
In this case the default branch is main hence the command will be git push origin main. Your work has been backed up safely.

Summary

The most simple way to understand the above mentioned stages to just get rif of the mystery around Git is highlighted below:
Write it-Prepare it-Save it locally-Upload to cloud.
We should strive to understand the stages rather than memorizing the commands,this is because understanding where changes are taking place at each stage is the key.Once we master this movement and how changes occur from the working directory all the way to remote repository, understanding additinal commands like merging, branches and pull become easy to understand.