Anonymized professional work
Building a data model for project-costing reporting
Current work building and maintaining a Power BI model for project-costing, margin, and operational KPI reporting, with data preparation and dynamic row-level security.
About Seakleng Ren
A finance foundation, growing into data and business intelligence.
I’m an Assistant Accountant whose work has grown from core accounting operations into financial analysis and business intelligence. With an accounting foundation and a Bachelor of Business Analytics with Distinction from Deakin University, I prepare financial and operational reports, manage budgeting and variance analysis, and build Power BI dashboards and data models for project costing, margins, and operational performance. I’m continuing to develop my skills in DAX, SQL, Python, and Power Query, bringing a finance perspective to the questions behind the data. Explore my projects and articles, or read my full story.
Business Intelligence / Data Analyst
Finance × Data × Programming
I connect financial understanding with business intelligence—bringing an accounting background to reporting, analysis, and clearer decision-making.
A connected perspective
- Finance
- Data
- Programming
The connection
How I connect finance and data
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Finance
Financial reporting, budgeting, and variance analysis ground my work in business context.
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Data
Business analytics and Power BI help turn financial and operational information into clearer insight.
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Programming
I’m continuing to build my programming skills as part of my broader technical development.
Tools
Working with data
I use Power BI and Excel in reporting and analysis; SQL and Python are areas I’m continuing to develop.
- Power BI
- SQL
- Python
- Excel
Case studies
Selected projects
Simulated-data portfolio project
E-commerce checkout A/B test analysis
A Python analysis of a simulated checkout experiment, with results clearly limited to the sample data and not presented as real business outcomes.
Synthetic-data portfolio project
Customer segmentation with RFM analysis
A Python notebook applying recency, frequency, and monetary scoring to synthetic retail transactions. The segments are exploratory labels, not real customer behavior or measured retention outcomes.
Synthetic-data portfolio project
Power BI retail sales and profit dashboard
A Power BI model and report built with synthetic, AI-assisted retail data. Its figures and trends are illustrative sample outputs, not real business performance or impact.
Synthetic-data SQL exercise
Exploring retail transactions with SQL
SQL aggregations across synthetic retail rows, with a documented data-integrity caveat: repeated order IDs do not consistently map to one customer or order date, so order-level metrics are not reliable.
Notes and ideas
Articles
Why data grain matters before you aggregate
Before aggregating transactions, check what one row represents, verify key consistency, and make sure metric labels match their calculations.
What makes a Power BI dashboard useful beyond its visuals?
A practical guide to designing a Power BI dashboard around its audience, purpose, measures, and visual choices.
How my finance background shapes the questions I ask of data
How my accounting and finance experience informs the questions I ask about measures, reporting, data quality, and business context.
Learning SQL and Python from a finance starting point
How I’m developing SQL and Python skills while building on a foundation in accounting, financial reporting, and business analytics.
From business requirements to a secure Power BI model
A practical workflow for evolving requirements, source discovery, data exploration, platform choices, Power BI transformations, maintenance, and dynamic security.
Get in touch
Let's connect
I'm always happy to talk about finance, data, and business intelligence. The best way to reach me is on LinkedIn, and my code is on GitHub.