DSA-Data-Analysis-Documentation

A collection of data analysis projects and exercises completed during my training with IncubatorHub through the Digital Skillup Africa (DSA) program.

It includes works on data cleaning, visualization, statistical analysis and real-world datasets using tools like Excel, SQL, and Power BI

PHASE 1: Excel Data Analysis Practice

This is a documentation on Excel exercises and projects I completed as part of my data analysis learning journey. It showcases practical applications of Excel functions, data cleaning, visualization, and reporting using real-world scenarios

Learning Focus

Guided by: Mr. Hameed Mushin

I focused on building a solid foundation in the following Excel areas:

Data Cleaning & Transformation

Functions: SUM, SUMIF, COUNTA, COUNT,FIND, SEARCH, COUNTIF, IF, IFS, MAX, MIN, LARGE, SMALL, AVERAGE, LEFT, RIGHT, DATE, OR, AND, BETWEEN, TRIM,UPPOER, LOWER, AND, PROPER, VLOOKUP, PIVOT TABLE and more.

Exercise:

Rearranging messy or unstructured data into clean, structured formats.

Data Analysis & Reporting

Exercise:

• Pivot Table creation and manipulation
• Summary statistics and insights from raw data
• Dashboard development for interactive reporting
  
  

Data Visualization

Exercise:

• use of Bar charts, column charts, pie charts, line graphs, and combination charts
• Custom chart formatting and dynamic visuals for better storytelling
  
  

Sample Exercises & Mini Projects

Sales Analysis

• Cleaned and analyzed monthly sales data using formulas, PivotTables, and charts.

Data Cleaning Tasks

• Transformed messy datasets into structured tables using formulas and Power Query.

Pivot Table Exercises

• Explored grouping, filtering, and calculations using PivotTables.

Dashboard Design

• Dashboard Design Built a mini dashboard with slicers and charts for dynamic reporting.
  
  

Tools Used

• Microsoft Excel 2016
• Power Query (built-in with Excel)
• Basic charting and dashboard tools
  
  
  
  

sample files and Screenshots of some class excercises are available here: (https://drive.google.com/drive/folders/1jT89aD3MuCxFUdYQdyRfB3UchaTBTFMe?usp=drive_link)

PHASE 2: SQL Data Analysis Practice

This phase contains my learning journey in Microsoft SQL for data analysis,

Guided by Mr. Ayodele Femi

It includes a wide range of exercises, practice queries, and mini-projects focused on mastering SQL for working with real-world datasets.

Learning Focus

My SQL training covered both foundational and advanced database concepts and techniques, including:

• Writing powerful SELECT queries to extract data
• Performing data cleaning, aggregation, and transformation
• Designing and modifying tables, views, and schemas
• Simple backup and restore operations (introdutory)
  
  

some Basic SQL commands Learnt

• SELECT, WHERE, ORDER BY JOINs (INNER, LEFT, RIGHT, FULL), GROUP BY, HAVING, COUNT, SUM, AVG
• CASE statements
• Subqueries and nested SELECTs
• CTEs (Common Table Expressions)
• Logical operators (AND, OR, NOT, IN, BETWEEN, LIKE)
• Table operations: CREATE, ALTER, ADD, DROP, TRUNCATE, DELETE, UPDATE, INSERT
• UNION, UNION ALL
• Creating and using Views
• Database Backup and Restore
  
  

Projects & Practice Exercises

Task Description

Sales Data Analysis:

• Used JOINs, GROUP BY, and CASE to summarize and segment sales

Employee Database Queries

• Filtered, sorted, and grouped employee records

SQL Table Management

• Practiced table creation, modification, and deletion

Backup & Restore

• Backed up and restored sample databases in SSMS
  
  

Tools Used

• Microsoft SQL Server (2016+)
• SQL Server Management Studio (SSMS)
  
  
  
  

sample files and Screenshots of some class excercises are available here: (https://drive.google.com/drive/folders/1jT89aD3MuCxFUdYQdyRfB3UchaTBTFMe?usp=drive_link)

PHASE 3: Power BI Data Analysis Practice

A documentation on my practical learning in Power BI for data visualization and business intelligence, under the guidance of Mr. Temidayo Teedee Ayeni. It includes exercises, dashboards, and projects designed to build skills in connecting, transforming, analyzing, and visualizing data.

Learning Focus

Throughout this journey, I focused on

• building strong foundations in using Power BI for data analysis and reporting:

• Connecting to various data sources (Excel, CSV, SQL)

• Cleaning and transforming data with Power Query

• Creating interactive reports and dashboards

• Writing DAX measures and calculated columns

• Building data models and managing relationships (intoductory)
  
  

Topics Covered

• Power BI Interface and Navigation
• Connecting to Excel and SQL Server
• Power Query Editor: cleaning and shaping data
• Data Modeling: relationships, cardinality, and normalization (intodutory)
• DAX (Data Analysis Expressions):
  • CALCULATE, FILTER, SUMX, AVERAGEX, RELATED, etc.
• Calculated Columns vs Measures
• Creating interactive visualizations:
• Bar/line charts, slicers, cards, matrix tables, maps, KPIs
• Designing user-friendly dashboards
  
  

Project Description

• HR Analytics Report Cleaned employee data and visualized hiring trends and attrition rates
• Design Performance Dashboard analyzing hiring trends and attrition rates
  
  

Tools Used

• Power BI Desktop (latest version)
• Power Query (built-in)
• Excel & SQL as data sources

> sample files and Screenshots of some class excercises are available here: (https://drive.google.com/drive/folders/1jT89aD3MuCxFUdYQdyRfB3UchaTBTFMe?usp=drive_link)