Priya Raghavan

Data Analyst at Marudham Bank | SQL, Power BI & retail credit analytics

I’m a Chennai-based data analyst working on retail credit and branch performance at Marudham Bank. My work involves SQL, Power BI, and quite a few conversations about what a number actually means before it goes into a report. I like a tidy reconciliation, clear documentation, and leaving enough time for someone else to check my work. Outside the bank, I’ve learnt Bharatanatyam since childhood, run at Besant Nagar, and save a little leave for the December concert season.

Build and maintain SQL datasets and Power BI dashboards for retail credit and branch performance reviews. Work with credit and operations teams to reconcile monthly figures, investigate exceptions, and document reporting definitions. Introduced a pre-release checklist for recurring reports so validation does not depend on whoever happens to remember it.

Prepared portfolio and collections reports using SQL and Excel. Replaced several manual spreadsheet steps with reusable queries and worked with operations colleagues to resolve mismatches between source files and monthly summaries.

Supported reporting projects for financial-services clients, including data cleaning, reconciliation, and dashboard testing. Maintained issue logs and learnt to ask for a metric definition before building the chart.

SQL, Power BI, Microsoft Excel, Python, Data reconciliation, Retail credit analytics, Dashboard development, Data quality assurance, Statistical analysis, Requirements gathering

Tamil, English

A small reporting improvement this month: we put the metric definitions next to the dashboard instead of leaving them in a separate document that everyone had to hunt for. Nothing dramatic, but our review conversations are already better. We spend less time asking which accounts are included and more time discussing the actual movement. I’m learning that making analysis useful often means making the surrounding information easier to find.

Eight years into working with data, I still keep a reconciliation sheet before I publish a dashboard. Row counts, totals, date boundaries, a few known cases. It isn’t the most interesting part of the work, but it catches the things a good-looking chart can hide. This week, a date filter was the culprit. Very ordinary mistake, very useful reminder: check the boring things first.

My dance teacher has always made us practise a difficult passage slowly before bringing it up to speed. I thought about that during a report handover this week. Walking through one example carefully did more than a long list of instructions. We traced the source, checked the transformation, and explained the exception. A little slower on the first day, much less confusion afterwards. Some lessons travel surprisingly well between the rehearsal room and the office.