Forem: Steve Andrew

How Analysts Translate Messy Data, DAX, and Dashboards into Action Using Power BI.

Steve Andrew — Mon, 09 Feb 2026 13:42:03 +0000

Data is the new oil and is highly relied on as evidence, the difference is the quality of data used being reliable to provide business intelligence answers to stake holders and decision makers.In our current world and time governments,organizations and even families rely of data for evidence based decision making.

The power of Power BI lies on its ability to pull data from multiple sources, clean it,analyze it,create joins and charts that are used for dash board creation while providing the required business inteligence insights that are actionable and easy to understand.

1.Power Query Editor
It allows data connection, transformation and loading data into the shape and model aimed at answering expected outcomes.

Data Cleaning
The most important aspect of data handling as it determines whether an analyst will arrive at the right answers or not.
They include:

Replacing missing values to ensure the data set is not distorted - missing order value
Standardization of text values - "pct" for " percentage"
Confirming the data types - "harvest date","discharge date"

Example:
Standardize within a data set all blanks like "N/A","Error" through Transform> Replace Values with Null

Data Modelling
Uses a Star Schema where data structures are used to show how tables are organised and related in the selected data model.It helps in linking fact and dimension tables used for calculations and filtering of trhe data set while answering business intelligence questions.

Fact table contains numerical data used for calculations like Quantity and Total Sales while dimesional table contains descriptive information used for data analysis.
Examples: DimDate, DimStore, DimProduct

They are useful during relationship creation and joins with the commonest relationship being "one-to-many".

Logical functions in DAX
Used to make decisions based on conditions.Allow Power BI answer questions like "Qulified" or "Not Qualified" hence classifying data in respective categories and apply business rules.They control how results are calculated and displayed.

Commonly used in calculated columns,measures and KPIs

Example: IF function
Most basic and widely used DAX logical function.
IF(condition,value_if_true,value_if_false)

Dashboards
A well designed dashboard should be able to derive key insights useful to the end user in terms of right decision making.

Display top KPIs
Use the right charts to compare performance against targets
Tell a story through slicers

Good dashboard is well understood easily and focused on key business outputs.Some of the key purpose include support strategic planning and resource allocation,track perfomance and trends while providing insights of some of the gaps for action.

Commong KPIs include:

Total Revenue
Total Profit
Average lenght of stay
Cost of Production

Filters and slicers should be used to allow users explore key dimensions.

Conclusion
Power BI is more trhan fancy dashboards rather its critical to the value it adds to the organization and provide answers that are geared towards business growth.Help identify key drivers and areas for improvement.

As Data Analyst your value is measured by the problems you help solve through continued building,for those of us who are transitioning into tech consistency,getting stuck and showing up eventually makes the desired difference.

Schemas and Data Modelling in Power BI

Steve Andrew — Mon, 02 Feb 2026 13:57:21 +0000

Microsoft Power BI is an interactive data visualization software product developed by Microsoft with a primary focus on businness intelligence.
Power BI consists of four main areas:

Ribbon (Top Toolbar)
Fields pane (Right SideBar)
Visualizations Pane (Right SideBar)
Report View,Data View and Model View (Bottom)

In this article, i will share more information about schemas and data modelling.

** What is a Schema?**
It refers to _the structure and organization of data within a data model.Schemas define how data is connected and related within the model, influencing the efficiency and performance of data queries and reports.

Types of Schemas.

Star Schema 2.Snowflake Schema

Star Schema,how it works.
A star schema is made up of a central fact table with multiple dimensions table branching off of this fact table, much like the appearance of a star.

Benefits for Power BI
1.Query performance - star schema reduces joins from 10+ to 2-3 tables and is 5-10x faster query execution.
2.DAX simplicity - measures reference fact table,filters uses dimensions and clearer codes.
3.Star schema columnar storage compresses better than normalized.

Fact table: -mae up of values that can be summarised and aggregated as well as one or more keys that link to the dimension tables.Purpose of the key - make connections between tables.When handling large volumes of data,it is recommended for the keys to be numeric values rather than text strings, as this can improve the model perfomarmance.
Fct tables should be very narrow and include a few columns as possible.Any columns that describes the features of a dataset such as Product Name or Product Category,should be separated out of the fact table a process called normalization of data.Goal - is to avoid repetitiveness.

Dimensions Table : desribes the features of the data set logically grouped together.They should contain unique values for the features they are describing and the columns are responsible for filtering or grouping of the data in Power BI.

2.Snowflake Schema
Normalized dimensions ideal for complex hierarchies.The dimension tables are further divided especially if a feature has any further categories or sub counties.
Example: Given a data set with Product tables that contain Product ID,Product Name and Product Category.In a snowflake schema the Products table will only contain Product ID and Product Name while the Product Category would firther be divided out into its own table containing Procuct Categoty ID and Product Category.

Data Modelling
Is the process of creating visual representation of the connections between data structures, with information about the individual attributes contained within those data structures.

Good data modelling practices are very important for building Power BI reports that are optimized for performance and can scale as needed.

Microsoft Excel for beginners in Data Analytics

Steve Andrew — Sun, 25 Jan 2026 16:16:58 +0000

Microsoft excel is a spreadsheet program used to store,organize,calcualte,analyze and visualize data with the aim of drawing insights for informed decision making.

It is widely used in business,accounting,education,research and data analysis.This article will illustrate the basics required for beginners to understand use and data manipulation for simple analysis.

Data in excel is presented on a work sheet that has columns(vertical group of cells labeled A,B,C,..at the top right) and rows(horizontal group of cells labeled 1,2,3,..at the left).Columns intersects with rows to form cells where real data elements are keyed in.

How to save work done in excel

Open an excel work book
Click on file at the top left of the ribbon
Click Save As
Choose a file/folder (e.g Desktop, Documents)
Type in a file name of your choice (e.g Dataset 1)
Important to ensure the file type is excel workbook(*.xlsx) and click Save.

Excel functions and their uses

1.Mathematical functions majorly used for calculations.
Function Use
SUM Adds numbers in a range
AVERAGE Finds the means of numbers
MIN Returns the smalest value
MAX Returns the largest value
ROUND Rounds numbers to the nearest decimal place
COUNT Counts numeric values

AVERAGE
AVERAGE(K2:K15)

MINIMUM
MIN(K2:K15)

MAXIMUM
MAX(K2:K15)

Data Cleaning
The most common methods used during data cleaning includes text nd number formatting, alignments(horizontal, vertical,wrap, merge and center) borders and fill colors and conditional formatting.This is also aimed at removing duplicates and blanks.

Handling missing values:
Find and highlight missing values
Select data range/column -> go to home on the ribbon -> select conditional formatting -> new rule -> select format only cells that contains blanks -> select a color and click okay.

Removing duplicates:
Highlight the dataset -> click home -> Conditional formatting -> highlight cell rules -> duplicate values -> select a color -> Ok.

Fixing data types:
Format numeric values as numbers,currencies as currency, texts as Text, dates as dates.They are crucial for right calculations.

VLOOKUP
VLOOKUP(10003,A2:E15,4,FALSE)

Pivot Tables:
Useful for in depth data analysis of a given dataset.Allows use of slicers, graphic and dashboard creation.
Steps
Select your data
. Go to insert -> Pivot Table
. Choose where to place, as a best practice choose new worksheet
. Select the important indicators or drag to rows, columns and values.

Summary

Excel is still a highly reliable tool that has vast use for data analysis in multiple fileds and still stands out among other softwares.Its highly compartible and can be used along with other tools like PowerBI,SQL and Python.

Beginner friendly article on Git bash and Git hub.

Steve Andrew — Sun, 18 Jan 2026 09:53:21 +0000

Git is a version control system that intelligently track changes if file.
Git hub is a cloud based platform where one can store, share and work together with others to write a code.
Codes are stored in form of a repository.

How to install git bash in your computer
1.Download git from the official website and follow prompts for window users or microsoft store.
2.Run the installer and follow prompts

Ensure components selected include "Git bash" and "Git GUI" are checked.
Choose default editor - for our use we selected visual studio code.
Select option of using Git from the command line and then follow prompts till installed.

1.To confirm if git is installed
git --version

2.To input name and user mail
git config --global user.name "STEVE"
git config --global user.mail "steveandrew97@gmil.com"

3.To confirm configuration
git config --global --list

4.How to generate SSH key that ensures Github connectivity is secure and will not prompt for password each time.

ssh--keygen -t ed25519 -C "steveandrew97@gmail.com"

Press enter to accept default file location

5.How to iniate the SSH Agent
eval "$(ssh-agent -s)"

6.Add SSH key
ssh-add ~/.ssh/id_ed25519

7.In putting the public key
cat ~/.ssh/id_ed25519.pub

How to push GitHub code
First, open your project in the terminal

1.Initialize Git

git init
2.Check file status

git status
3.Add File

git add.
4.Commit changes

git commit -m "My first commit"

5.Connect to GitHub Respository

git remote add origin https://github.com/username/repository-name.git

6.Push the code

git push -u origin main

The code will appear on GitHub

How to pull code from GitHub
pulling means getting the latest version of the project from gitHub

1.git pull origin main
this is usefull when working others or when switching devices

How to track changes using Git
2.To see changed files

git status
3.To see what exactly changed.

git diff
4.To view commit history

git log

Summary: Git enables the coding community network while making it possible for oe track,store and make changes in thier coding work.