Forem: Victor

How Analysts translate Messy Data, DAX and Dashboards into Action using Power BI

Victor — Tue, 24 Feb 2026 00:48:53 +0000

You have done your data modelling and your dataset is well structured and preferably in a star schema. The relationships are correct.

Then what?
This data is still raw data and it does not answer any questions the business is asking. What is the total revenue? What is the cost of production? You cant outright answer this questions.
This is where DAX comes in.

DAX- Data Analysis Expressions

This is a powerful formula language used in Power BI.
It is essential for creating calculations that unlock insights into your data. It is what says "
revenue this year is higher than last year" or " cost of production this year is up 4% as compared to last year".
DAX is important so as to optimize decision making in a business.

Calculated Columns and Measures in DAX

Calculated Column: This performs a row by row calculation in a table.
Measure: This returns a singular value for the context you choose(filter, aggregation)

DAX Functions

Text Functions

They manipulate texts.

Concatenate/ConcatenateX

Concatenate joins two texts from different columns into one.

ConcatenateX is for each row. It returns the concatenation of these texts and is separated by a delimiter.

Left
Extracts characters from the left.
Right
Extracts characters from the right.
Mid
Extracts characters in the middle.
Upper, Lower, Proper
Upper upper cases the whole text.
Lower lowercases the whole text.
Proper capitalizes only the first character.
Len, Trim, Clean, Search
Len returns number of characters in a text.
Trim removes spaces from text.
Clean removes hidden non printable texts.
Search returns starting position of one text within another text.

Date and Time Functions

Today and Now
Today returns current date in datetime format.
Now returns current date and time in datetime format.
Date, Day, Month, Year, Quarter
Date returns the specific date.
Day extracts the day of the month.
Month extracts the moth of the year.
Year extracts the year of a date.
Quarter extracts the quarter of the year in a number.

DateValue and TimeValue
DateValue converts a date in text to a date in datetime format.
TimeValue converts a time in text to a time in datetime format.
DateDiff
This calculates the difference in specified intervals between two dates.
The interval can be in minutes, hours, weeks, months, years, quarter.

This gives the difference in years.

Aggregate Functions

Average, AverageX
Average calculates the mean of all numbers in a column.
AverageX is an iterator. It goes trough each row, takes the sum of these calculations and averages them.
Sum and SumX
Sum adds all the numbers in a column.
SumX returns the sum of an expression evaluated for each row. For example, Sum of revenue when you have got yield and price. SumX will calculate revenue of each row then add the total.
Max and Min
Max returns the largest value in a column.
Min returns the smallest value in a column.
Count, Countrows, CountBlank, CountX, DistinctCount
Count returns the number of rows in a column that has no blanks.
Countrow returns the number of rows in a table.
CountBlank returns the total blanks in a column.
CountX returns the count of values which result from evaluating an expression for each row of a table.
DistinctCount returns the number of distinct values in a column.

Time Intelligence Functions

They are used to compare and aggregate data over periods of time. For example, revenue this month versus last month.
A data table should be present for the DAX functions to operate.

DateAdd

It is used to move a date by a specified interval
If we are going forward, we use +ve.
If we are going backwards, we use -ve.

Here, we have shifted the date by two quarters back.

TotalYTD, TotalMTD, TotalQTD, TotalWTD

They calculate cumulative totals.
They are Year-to-Date, Month-to-Date, Quarter-to-Date, Week-to-Date.

The same happens to the other functions.

DateBetween

This returns the dates between two given dates.

Dashboard

After doing your calculations, you need to present this result to the decision maker. You do this by use of a dashboard.
Designing a good dashboard is crucial as it impacts how well the data you present will be interpreted.
It should be visually appealing and user friendly.

Dashboard Design

Meaningful title. It should be concise and reflect the data you want to present.
KPIs. These are Key Performance Indicators and they are the important numbers of a business, e.g., total revenue, profit margin.
Charts. They show the performance visuals. They are placed in the middle section. Trend charts should start, followed by comparison charts then the breakdown visuals.
Colors. Color palette should be limited to give a cleaner look. The colors should have high contrast. The background color should be simple and should not compete with the actual visualization.
Layout. Avoid overcrowding the dashboard. Have a maximum of 6-8 visuals. You should not have any duplicate charts, e.g. area chart of monthly revenue and line chart.
Interactivity. Have slicers, filters and drill down capabilities to enhance user interaction.

A good dashboard should turn raw data into actionable insights to support optimal decision making.

DATA MODELLING IN POWER BI

Victor — Tue, 24 Feb 2026 00:46:14 +0000

Data modelling is critical in Power Bi and it determines how effective your analytics work will be.

What is it?

Well, data modelling is the process of structuring data into tables and connecting those tables so they can work together.
This helps the data in your data model easy to explore. Think of it this way, instead of throwing all your clothes on one drawer, you have different drawers for your shirts, trousers, jeans and even vests.
Good data modelling aids in curing this headache.

In Excel, the data is stored in one table. In Power BI, this data is stored in several tables which are connected. The tables are of two types:

Fact table.
Dimension table.

Fact Table

A fact table contains the quantitative data such as sales, revenue. They contain measurable business events.
Each row in this table is an event/transaction.
For example, a data set showing retail business with several stores will have a fact table with entities such as Total sales, Quantity, Unit price and OrderID.
Fact tables are basically used for calculations. They have keys that link it to the dimension table

Dimension Table

They contain descriptive data that describes the data in the fact table and helps you in slicing and filtering your fact table.
For example, Customer dimension(contact ID, Gender), Product dimension(product ID, name), Date dimension(date, day, month, year, quarter)

A fact table contains your data and changes frequently while a dimension table describes this data and is updated less frequently

A fact table and dimension(s) table are organized in the data model using a schema

SCHEMA

This is a structure/shape of how your data is organized in a database or models.
It answers questions such as:

How many tables do you have in your model?
Which tables are connected?
What kind of relationships exist between them?

Star Schema

A central fact table is directly connected to several dimension tables. If you open it in a model view, it looks like a star.
Examples; FactSales ( Orderdate, Salesdate, Revenue, Cost)
They have a simple structure, easy to understand, scale and gives better performance in Power BI due to fewer joins making it the preferred choice.

Snowflake Schema

Just like the Star schema, the fact table is connected to the dimension tables. However, the dimension tables are further normalized into multiple related tables.
The core of a snowflake schema is just a star schema.
For example, a Customer dimension table is further divided into another dimension such as the City( CityID, Name, County).

Star schema is preferred for being simple and having faster analysis performance while snowflake schema is preferred in complex data environment as they reduce redundancy.

Relationships in Power BI

Relationships in Power BI are crucial as they indicate which tables are connected. This is done using a common column (Key) between the tables.
This is helpful when doing DAX calculations.
Let's say we need to know the order a particular customer made. We will need a common column between the customer table and the order table such as CustomerID.

This column will be used to create a relationship between Customer table and Order table by Keys.

Keys

Relationships are built on Keys.
In the Order table, each order will have it's own ID that can never be repeated. This is called a Primary key
There are also Foreign keys. In the same Order table, we have the customer ID which tells us which customer made an order. However as this key is coming from a foreign table which is the customer table, it is called a Foreign key.

Cardinality

Let's say a customer has made several orders. This customer's customer ID will appear once in the Customer table but several times in the Order table.
If the customer makes one order, the customer ID will appear once in the Customer table and once in the Order table

These are different relationships between the tables (Cardinality)

Types of Cardinality

One to Many (1:M or 1-*)

A single record in one table is connected to many records in another table.
For example, one customer having many orders.

The reverse is true for Many to One relationship.

One to One (1:1 or 1-1)

A single record in one table is connected to a single record in another table.
For example, a National ID can only belong to one person.

Many to Many (M:M or M-M)

Multiple rows are matching in both tables.
For example, students can enroll in multiple courses and each course will have multiple students.
Many to Many relationships are troublesome as a lot is happening at the same time.

All these steps are done in Power BI to have good modelling as it forms the foundation of our analysis in Power BI. It makes our DAX calculations precise and correct by removing ambiguity in relationships making our data easier to understand.

I hope you now have a strong understanding about data modelling in Power BI and its importance.

Thank you for reading.

INTRODUCTION TO MS EXCEL

Victor — Tue, 27 Jan 2026 00:07:26 +0000

Microsoft Excel is a spreadsheet software that was developed by Microsoft. It is the foundation on which analytical thinking is built. It is used for organizing, analyzing and visualizing data
Excel is just a big calculator but with some advantages like;
It can store data.
-It can perform multiple calculations at the same time.
-It can do operations on other forms of data such as text.
Excel is a powerful tool and you should let it work for you.

Vocabulary

You can think of this into two; the part of Excel that you work with such as cells, columns, and the tasks that you want to do such as cleaning, sorting and formatting.
Excel is made up of two sections; the upper part called the ribbon and the lower part called the sheet

This is the ribbon

This is the sheet or the worksheet.
Many worksheets make up a workbook
A worksheet is made up of cells, rows and a column.
A cell is denoted by it letter-number address.The letter is the column and the number is the row. A row moves from left to right while a column moves up to down.

This is cell E2
A range is a collection of cells. it is denoted using a range operator

This range is denoted by A2:C6

Formulas and Functions

Formulas are created by the user e.g., (10+10), (A6*B6)
Functions on the other hand are built in formulas. they are codes designed for calculations e.g. Sum(A2:B2), =Average(C2:C30). Don't worry. You'll get the hang of it as we go on.

Data Analysis Tools

This is where the magic with your hands begins. You have tools such as sort ad filter, formatting, data validation to analyze and interpret data.

Charts and Graphs

These are used to visually represent your data.

Lets now begin learning about some of what we have talked about above.

Formulas and Functions

Formulas

You make formulas using arithmetic operations, i.e. addition(+), subtraction(-),multiplication(*), division(/) exponent(^).
The values are typed directly and by using cells.

This shows multiplication calculation =(L2*M2)
For the others, you follow the same operation

Before we go to anything else, lets talk about parentheses. These are very important in Excel.
They dictate the order of a calculation. Having them or not having them is crucial.

No parentheses

=10+10*10. The result is 110 as the calculation is 10+100

With parentheses, the same result is 200 as Excel calculates it as 20*10

Data Analysis

There are three types of data namely text data, number data and date and time data
Different operations can be performed on these using different data analysis tools.
Lets start with sort and filter

Sort

3 types based on the data type:
-Text sorting(A-Z/Z-A)
-Number sorting(Largest-Smallest/Smallest-Largest)
-Date sorting(Oldest to Newest/Newest to Oldest)
Go to Home, Sort, choose expand the selection the click OK

The sorting operation is under the editing group.

Filter

This allows you to display only the rows and columns that meet a certain criteria and temporarily hide the rest.
it also has three types based on the type of data, i.e. text filter, number filter and date filter.
Go to Home ribbon. It is the "twin brother" to the Sort function.
Quick tip; you can click on your data and type Ctrl + Shift + L

Conditional Formatting

This is a function that is used to change the appearance of cells in a range based on your specified conditions, e.g. color scale formatting.

It is found in the Home ribbon.
You can also condition format cell rules. This options include greater than, less than, equal to, text that contains, between, duplicate/unique values

Here, we have given Excel specific conditions using the greater than option.

Excel Functions

They are divided into;
-Aggregate functions, eg. sum, average, min
-Logical functions, e.g. If, And, Or
-Text functions e.g. Uppercase, Lowercase, Trim, Right, Left
-Lookup functions e.g. vertical, horizontal, xlookup
-Date/Time functions

Text Functions

They are used to manipulate text data.
-Upper - Uppercases what you want

Lower - Lowercases what is in a cell.
Proper - Capitalizes only the fist letter -Trim - Used to remove extra unwanted space Length - Shows the number of characters in a cell including the spaces
Left - Extracts the first letters, e.g.

The number 2 shows the number of characters you want to extract

Right - Extracts the last letters. Prompts same as Left function
Mid - Extracts characters in the middle Prompts same as Left function
Concatenate - Used to combine two words e.g.

If you want them to separate:

Aggregate Functions

Sum-

Very simple, right.
The other functions, i.e. Average, Maximum, Minimum, Count follow the same procedure.

SumIf, AverageIf,

They are used for conditional aggregation e.g. average age of people above 40 years

SumIf- Sum of people above 40 years old

AverageIf is also done the same way

Logical Functions

They are used to perform logical test and return one value for TRUE and another for FALSE.
E.g. column E has the salary of employees. The scenario is that employees above 80,000 are high while the others are low. How do you go about it?
=IF(E2>80000,"High","Low")

From here, you can now autofill.

And

Used when we want to meet two conditions such as salary and age.It is performed the same way as the IF function.

Or

We use it when we want to meet only one condition.

LookUp Functions

Just as the names suggests, they are used to "look up" for values in another column or row.
Three types namely Vertical(VLookup), Horizontal(HLookup) and XLookup.

Vertical Lookup

It searches for a value in the first column over a range and returns a value from another range.
E.g. we have Employee with ID 10009 and we want to know his department

=VLOOKUP(10009,A2:E15,4,FALSE)

10009 is his ID, A2:E15 is the range we want to work with, 4 is the column index where you want your answer from AND you write FALSE if you want the exact value.
If you want the approximate, write TRUE

HLookup

It searches for a value in the first row of a sheet and returns a value from another sheet.
The data is structured horizontally, that is, the rows have headers.
Its operation is the same as that for VLookup

XLookup

Also known as Index Matching.
Our reference is neither in the first column or first row. So what do we do?
Let's say the ID is in column F and we want t find his department in column D.

We use 0 as it gives us an exact value.

Pivot Charts and Pivot Tables

These are used to summarize our data.
They are very easy to work with.
How do you create them? Click anywhere on your sheet and go to Insert Ribbon and click Pivot Tables.

Always click on New Worksheet.

In the new worksheet, you now work your magic. Add the headers you want to the columns, rows and values table. That is it. you will have created your pivot table

You can now use this pivot table to create charts such as Column, Bar, Line and Pie charts

And that is it! A rundown on Excel. You may not get the hang of Excel right away. Don't worry. Every beginner was once there. The skills you learn here will carry over into your Data journey so get to learn it thoroughly.

Version Control

Victor — Sun, 18 Jan 2026 08:16:01 +0000

In the world of software, Version Control is an important infrastructure. Imagine having to write code without being able to track the changes. This is recipe for chaos.
Version Control exists to mitigate this allowing for efficient collaboration and help you undo mistakes.

So then, what is version control?

Version Control is a system for tracking changes to files e.g. code. Every time you make a change, Version Control records this and saves the outcome.

GIT

This is a Distributed Version Control System that helps track changes in code and allow collaborations between multiple people simultaneously.

GITHUB (Git + Collaboration)

GitHub is a cloud platform that hosts Git repositories and allows developers to collaborate through pull requests.
While Git is the tool, GitHub is the platform around it.
GitHub is crucial as it is your CV. Recruiters will always check it.

Push and Pull

These are operators for synchronizing code between your local computer( local repository) and the shared project space on GitHub( remote repository)

Git Push

This uploads your local changes to the remote repository making them available to collaborators.
How do you do this?
-Create new repository on GitHub and name it.
-Go to the file you need to push and initialize Git on it. Use the command git init
-Check the files you need to push using git status
-Add the files using git add
-Commit locally using git commit -m "Project added"
-Now push this code to Git repository. Commit the URL on GitHub and paste it on Git together with the command git remote add origin URL
-Then type git push origin master
-Your files will now appear on GitHub.

Git Pull

This fetches the latest changes to ensure your local copy is up to date.
How do you do this?
-Find the repository you need
-Fork the project. This is crucial as it creates a copy of the project and stores it on your GitHub. The changes you do here wont affect the original file
-Pull this project to your local machine by copying the URL ang going to Git Bash.
-After type git clone URL
-You can now make your desired changes before pushing them back to GitHub.

So, what is the summary of this article? Simple

Version Control makes sure the changes we make are safe
Git makes it distributed
GitHub allows for collaboration on these changes