I know the business meaning behind the numbers.
My background covers reconciliations, receivables, invoice tracking, month-end reports, and financial controls. That helps me ask better questions before building a dashboard or query.
I am Ratnesh Kumar Pal, an accounts and finance professional transitioning into Data Analytics. My 7+ years in accounting, receivables, reconciliation, and reporting give me a strong business foundation, while SQL, Python, Power BI, and Excel help me convert financial data into clear insights.
I am not starting from zero. I already understand ledgers, invoices, receivables, month-end close, and reporting pressure. Now I am applying data tools to solve those problems faster and more clearly.
My background covers reconciliations, receivables, invoice tracking, month-end reports, and financial controls. That helps me ask better questions before building a dashboard or query.
I use SQL, Python, Power BI, and Excel to clean data, build KPIs, automate recurring reports, and create views that support faster business decisions.
My current focus is building job-ready analytics capability on top of real finance-process experience.
Receivables, reconciliations, trend review, month-end reporting, and stakeholder summaries.
Data extraction, joins, grouping, KPI logic, customer segmentation, and validation queries.
Pandas, NumPy, data cleaning, EDA, file automation, and reusable reporting scripts.
Dashboard design, DAX measures, data modeling, KPI cards, and executive-ready reporting.
Pivot tables, Power Query, lookup logic, templates, controls, and audit-ready spreadsheets.
Exploratory dashboards, visual summaries, filters, and quick insight views.
Validation checks, missing data handling, outlier review, and standardization.
Repeatable report generation, data checks, and process templates for recurring work.
Each role strengthened the same habits data teams need: accuracy, validation, reporting discipline, and stakeholder communication.
These projects show how I am converting my accounting background into hands-on data analyst work.
Automated month-end reporting with Python and Pandas, including validation, reconciliation, and formatted Excel outputs.
Sales analytics with SQL and Power BI covering revenue trends, customer segmentation, and KPI reporting for stakeholders.
Exploratory data analysis identifying key academic performance factors through cleaning, visualization, and actionable summaries.
A commerce and finance foundation supported by modern analytics credentials.
Data analytics methods, tools, and project-based workflows.
Analytics foundations, visualization, and business insights.
SQL querying, transformation, and analytical reporting.
Technology foundation for applied data work.
Professional Accounting and Finance, Jain University, Bangalore.
Business Management, CSJM University, Kanpur.
Institute of Chartered Accountants of India.
Higher Secondary education.
Secondary education.
I am looking for roles where I can combine accounts experience with SQL, Python, Power BI, Excel, reporting automation, dashboards, and practical business analysis.
This keeps the site static and reliable while still making it easy for recruiters to reach out.