DEV Community: SHARON CHEROCK

How Analysts Translate Messy Data, DAX and Dashboard into Action using Power BI

SHARON CHEROCK — Mon, 09 Feb 2026 22:57:20 +0000

Power BI makes raw data meaningful. This is achieved through visualization like charts and graphs. Data cleaning is done using the Power query which cleans and combines data from various sources

Data Cleaning in Power BI

Some of the basic tasks include:
.Removing duplicates
.Handling missing values
.Data type conversation
.Replace values

DAX - Data Analysis Expressions

DAX is a set of functions for calculations.
After cleaning your data, you can now perform your calculations.
You can use your formulas to calculate tables, calculations will add a table or calculate columns, calculations will add a column.

Common DAX functions

.Simple calculations like COUNT, SUM, AVERAGE, MIN, MAX
.IF, this returns a different value whether true or false
.DATEDDIFF, gives difference between two dates in days, months, years
.SUMX,AVERAGEX,COUNTX

Row context and Filter context in DAX

Row context
Operates on row to row basis. Examples of calculations include SUMX, AVERAGEX

Filter context
Filter Context refers to the set of filters applied to the data model before calculations.
Example is a function like CALCULATE

Dashboards

This is a page that tells a story through visuals. It provides the highlights just with a look of it. You get a general view of the output without delving so much into it which can be used in decision making.

Power BI is key when it comes to decision making. It assists businesses make sense of data at hand and give them a leverage. It answers what and why questions and gets you thinking of the next thing to do.

Schemas and Data Modelling in Power BI

SHARON CHEROCK — Sun, 01 Feb 2026 11:03:44 +0000

Power BI has proven to be a resourceful tool when it comes to shaping data. Large data is made simple and easy to understand.

What is Data Modelling?

Data modelling in Power BI is organizing data and creating relationships between different tables so that data works together correctly.

Importance of data modelling

. It makes data easy to understand and be used.
. Provides accurate results analysis
. Reduces data duplication
. Improves performance
. Scalability - it can handle large volume of data with ease

Levels of Data Abstraction

Physical level - How data is stored
Logical level - What data is stored
View level - What the user sees.

Example of data abstraction in Power Bi:

.Physical - sales table stored in database
.Logical - sales connected to customer tables
.View - sales dashboard showing charts

Power BI data model organization

Schema is how tables are arranged and connected.

Fact table - Contains measurable data or numbers. It enables summarization.
Dimension table - Contains descriptive data. It enables filtering and grouping.

Star Schema

In simple terms, the structure of Star schema is designed to have one central Fact table and multiple Dimension tables. This is the common type.

Advantages of Star Schema

Accurate data analysis
Easy to understand and use.
Improves performance
Reduction in data duplicates

Snowflake Schema

Its structure is designed such that the Fact table is connected to Dimension table and those Dimension tables to other Dimension tables.

Advantages of Snowflake Schema

Reduces storage space
Supports complex queries because of hierarchical data.
Useful for large data sets.

Flat Schema

Here, data is stored in one single table without dimensions.

Advantages of Flat Schema

Very convenient for small datasets thus easy to set up
Easy to understand.

A well designed data model is important for data analysis. It helps in maintaining data integrity. Ensure that you import data, describe relationships and calculations needed on the data before modelling it.
Happy learning and discovery!

Simple steps in excel for Data Analysis

SHARON CHEROCK — Sat, 31 Jan 2026 16:49:10 +0000

I thought excel was a few classes learning then you are at it, but Alaaas! To my amazement, I keep meeting something new that excel can solve for me.
Let us learn a few but critical functions excel can do for a simple data set.
Always remember to save your work after every update to avoid loosing your work.

What makes up an excel?
The basic parts of an excel are:

Rows - the vertical cells
Columns - the horizontal cells
Cell - intersection of row and a column
Sheet bar - displays number of sheets.

Data Types
This ensures that you input your data correctly.

Let us explore these data types:

.Number
.Currency
.Date
.Text
.Time
.Percentage
.Fraction

Excel can used to analyze basic data in following ways;

Sorting and Filtering
You can sort your data in different ways; smallest-biggest, largest-smallest or even customize your filter.
Data Cleaning
. Removing duplicates
Having repeated data can give wrong computations. So you ensure you remove any duplicates in your data.
Select your column>Go to Data on the Tool Bar and Select Remove Duplicates, Click Okay
Flash Fill.
It includes several actions like;
.splitting and combining texts
For splitting data:
Select the name column>On the Tool Bar go to Data>Select Text to Columns> Pick Delimitedclick Next and choose space/comma> Finish
Formatting data for example to upper case, lower case

to upper case you use this formulae =upper(f2:f10)
to lower case you use this formulae =lower(f2:f10)

Basic data calculations
. Sum - =sum(b2:b5) adds data in that column
. average - =average(b2:b5) finds the average
. min - =min(b2:b5) finds the minimum number
. max - =max(b2:b5) finds the maximum number

Logical functions
. IF/IFS - IF includes one multiple and IFS includes several multiples
. COUNTIF
. SUMIF

Pivot Tables

Used to analyze and summarize large volumes of data.

Select your data , on the Tools Bar, Select Insert, Select Pivot Table.
you will have this window after the steps

After selecting data you can select different calculations you need on the data in the Values area

Visualization
Transforms data into visuals using charts and graphs.
It breaks down complex data into simple easy to understand data.

By the time you are reading this i believe you must have learnt the basics of excel if not all. With continuous interaction with excel you will be able to learn much more. Happy learning and discovery!

Getting to know Git and Github

SHARON CHEROCK — Wed, 28 Jan 2026 07:51:51 +0000

Definitions

Git - A version control tool used to track changes in computer files.
Github - A web-based platform where you can store Git repositories allowing you to store, manage, track and share codes.

Installing Git and Gitbash

Go to https://git-scm.com, install the latest version and make sure to choose the correct operating system. Continue to signing up.

To access Gitbash, search on your computer and you will get a terminal.

Configuring On GitBash This is to ensure that Git recongnizes you. Ensure the email you will use is the same email as the one you are signed on in Git.

git config --global user.name "name"
git config --global user.email "emailyours@email"

You can check if your configurations have picked using this command
git config --list

Generate SSH key and add an Agent

.Use this command to generate a key
ssh-keygen -t ed25519 -C "sharoncherock1@gmail.com"

.Adding an agent
eval "$(ssh-agent -s)"

4.Adding your Key to Github

.Copy your key
.On Github, click on your profile, go to Settings
Scroll to SSH and GPG Keys, tap on New SSH Key
.Name your key and paste the key in the box. Then tap the Add SSH Key.

Git Push and Pull. .First, create a repository. On your Github account, tap on the + sign and click on New Repository. Give it a name and make its visibility to your preference. Click the Add A README file. Click on Add Repository

Commands used;
git push -u origin main

The purpose is to link the local repository to remote repository

git pull origin main

In conclusion, just start, we will get better with practice. I hope this articles gives you some little insights and you can comment for more engagements and learning together.