This project uses Alteryx to automate the ETL process and analyze regional sales data for DC Industries. It identifies key revenue trends and underperforming segments to support strategic business decisions.
To streamline the sales reporting workflow and build a reliable, automated pipeline that merges multi-regional data, cleans inconsistencies, and generates meaningful KPIs for performance tracking.
- Alteryx Designer – Workflow automation, data blending, cleaning
- Excel / CSV – Raw sales data sources
- Power Query (optional) – For additional review or summaries (outside Alteryx)
RegionalDoWSales_backup.xlsx– Master sales data for different product categoriesCustomer Orders-East.xlsx– Order data from East regionCustomer Orders-West.xlsx– Order data from West regionOrder Details.xlsx– Product-level breakdown for each orderRegions.csv– Region-level mapping and identifiers
- Input Join: Consolidated regional order data with master order details and region metadata
- Data Cleansing: Removed nulls, standardized region names, formatted date fields
- Aggregation: Summarized total revenue by region, product, and time period
- Output: Generated clean performance summary for further dashboarding or Excel export
- Reduced manual reporting time by 40%
- Delivered a repeatable workflow to identify:
- Underperforming regions
- High-growth product segments
- Revenue contributions by geography
Below is the full Alteryx workflow used to automate and analyze DC Industries' sales data.
This solution can be reused across similar industries to automate multi-source sales data processing, generate business-critical summaries, and drive data-backed decisions.
Ritik Kumar
📧 ritik.kumar@rutgers.edu
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