Business Intelligence
Power BI, DAX, Power Query, KPI design, interactive dashboards and executive reporting.
Data Analyst | Software Engineer | Business Intelligence Analyst
I build practical software and turn complex data into clear business insights.
I’m Ernest-Cyril Divine Onyeze. I analyse data, build dashboards and develop web applications that turn information into practical tools and clear business decisions.
Power BIInteractive reporting
SQL + ExcelAnalysis & preparation
Python + DjangoData workflows & web applications
Open to data & software opportunities
01Featured case studyGlobal sales intelligence
DATA CLEANING ✦ DATA MODELLING ✦ DASHBOARD DESIGN ✦ BUSINESS INTELLIGENCE ✦ INSIGHT COMMUNICATION ✦
01 / About
Analysis built for the person who has to make the next decision.
I combine Data Analytics, Business Intelligence and Software Engineering. I use Power BI, SQL, Excel and Python to build reliable models and intuitive dashboards, and Django, SQL and Bootstrap to develop database-backed web applications.
My approach combines analytical rigour with clear visual communication. I care about data quality, meaningful metrics and making every report easy to explore—not just impressive to look at.
View my full CV ↗02 / Toolkit
Data Analysis
Excel, SQL, Python, exploratory analysis, data cleaning and insight development.
Data Modelling
Star schemas, relationships, date dimensions, calculated measures and model optimisation.
Communication
Data storytelling, stakeholder-focused design, documentation and actionable recommendations.
Software Engineering
Python, Django, SQL and Bootstrap: database-backed web applications, backend logic and responsive interfaces.
03 / Credentials
Microsoft Certified
Power BI Data Analyst Associate
Earned September 2026 · Valid through September 2027
04 / Selected work
Featured Power BI case study
NaijaMart Global Sales, Profitability & Shipping Performance
An end-to-end BI project that transforms 51,290 order-line records into a four-page decision-support dashboard.
One dataset. Several decisions.
NaijaMart needed a clear view of sales growth, product profitability, customer and market performance, and shipping efficiency. The source data required cleaning, date correction and dimensional modelling before it could support reliable analysis.
My approach- Cleaned and transformed the source workbook in Power Query.
- Designed a star schema with sales, customer, product, location, market and date tables.
- Built reusable DAX measures for sales, profit, margin, growth, loss and shipping.
- Designed four connected report pages with slicers, navigation and contextual tooltips.
05 / Selected work
Featured SQL case study
TeleConnect Customer Churn SQL Analysis
An end-to-end MySQL investigation of customer churn, historical customer value and practical retention priorities across 7,043 telecom customers.
From customer records to retention priorities.
I designed and queried a relational MySQL database to identify the customer segments most associated with churn, quantify historical value linked to churned customers and create a rule-based priority list for proactive retention.
MySQL and SQL skills- Relational schema design, data loading, cleaning and validation.
- Multi-table joins, aggregations, CASE expressions and subqueries.
- CTEs and window functions for revenue ranking and cumulative analysis.
- Reusable views for customer, churn-segment and retention reporting.
06 / Selected work
Featured Excel case study
Retail Budget, Sales and Profit Forecasting Model
An Excel 2019 model combining 829,262 retail transaction lines with budget comparisons, gross profitability, inventory valuation and three forecast scenarios.
From transaction data to financial planning.
I used Maven Analytics Mexico Toy Sales data to analyse a fictional toy-store chain across 35 products and 50 stores. The workbook connects historical performance with transparent budget targets and adjustable sales-growth and cost assumptions.
Excel skills demonstrated- Power Query transformations, product merges and financial calculations.
- A Power Pivot Data Model with five one-to-many relationships.
- SUMIFS and INDEX/MATCH for monthly comparisons and scenario selection.
- PivotTables, six charts, slicers, conditional formatting and linked KPI cards.
Budget and forecast methodology
The Jan–Sep 2023 budget uses comparable 2022 sales with editable category growth targets. The Oct–Dec 2023 forecast uses the corresponding 2022 seasonal baselines under Best, Expected and Worst Case assumptions. These are modelled targets and estimates. Profit refers to gross profit before operating expenses.
The workbook is saved in Best Case. Select a scenario on Assumptions, then refresh the forecast PivotTable at Analysis!X55 to update its chart. Historical slicers and the fixed budget and forecast periods are explained in the documentation.
07 / Selected work
Software engineering project
NetOps Network and Infrastructure Monitoring Dashboard
A Django web application that simulates infrastructure health monitoring and turns threshold breaches into actionable incidents.
One view of infrastructure health and incident response.
Operations teams need to identify which servers, routers, fibre links, cloud nodes and databases require attention. I built NetOps as an independent portfolio prototype to demonstrate a central monitoring view and a database-backed incident workflow.
Implementation- Python and Django backend with SQLite for persistent asset and incident records.
- Threshold checks for CPU, memory and latency, plus Offline detection.
- Automatic incident creation, duplicate checks and escalation from Warning to Critical.
- Rule-based recommendations and Open, Investigating and Resolved incident states.
- Bootstrap interface, Chart.js visualisations, asset detail pages and Django Admin.
All infrastructure and metrics are fictional and simulated. This prototype does not scan or connect to real networks. Recommendations use predefined rules rather than AI-generated advice.
08 / Process
01
Understand
Define the business questions and identify the decisions the analysis must support.
02
Prepare
Profile, clean and validate the data before designing a dependable model.
03
Analyse
Create meaningful measures and investigate the patterns behind performance.
04
Communicate
Deliver a clear, interactive story with findings people can act on.
Available for opportunities
Have a data or software problem worth solving?
I’m open to opportunities in Data Analytics, Business Intelligence and Software Engineering, including roles and collaborations involving dashboards, data workflows and web applications.