NCR Aloha Integration & Analytics
Budget: $20,000 – $50,000 USD
I need a developer who can connect the NCR Aloha POS directly to a brand-new back-end, capturing both sales transactions and inventory movements in real time, then turning that raw feed into clear, decision-ready insights.
Here is what I’m after:
• Seamless API or data-bridge that pulls every ticket, item sold, and stock adjustment from Aloha without interrupting daily operations.
• A lightweight data store or warehouse you set up from scratch—no legacy system to worry about—ready to scale with additional locations later.
• Interactive dashboards and scheduled reports that spotlight sales performance, customer behaviour patterns, and true inventory-turnover rates. I should be able to filter by daypart, menu item, employee, and promo code at minimum.
• Clean documentation and a simple admin panel so my team can monitor sync status, adjust mapping rules, and add new outlets without calling a developer each time.
SQL, ETL scripting, and a BI layer such as Power BI, Tableau, or Looker are all fine; just explain why you prefer one over another. What matters most is data accuracy, low-latency refresh, and visuals that non-technical managers can follow.
When you reply, please outline your approach to the Aloha data extract, the tech stack you recommend for the warehouse and reports, and a rough timeline for proof of concept, pilot, and final hand-off.
Here is what I’m after:
• Seamless API or data-bridge that pulls every ticket, item sold, and stock adjustment from Aloha without interrupting daily operations.
• A lightweight data store or warehouse you set up from scratch—no legacy system to worry about—ready to scale with additional locations later.
• Interactive dashboards and scheduled reports that spotlight sales performance, customer behaviour patterns, and true inventory-turnover rates. I should be able to filter by daypart, menu item, employee, and promo code at minimum.
• Clean documentation and a simple admin panel so my team can monitor sync status, adjust mapping rules, and add new outlets without calling a developer each time.
SQL, ETL scripting, and a BI layer such as Power BI, Tableau, or Looker are all fine; just explain why you prefer one over another. What matters most is data accuracy, low-latency refresh, and visuals that non-technical managers can follow.
When you reply, please outline your approach to the Aloha data extract, the tech stack you recommend for the warehouse and reports, and a rough timeline for proof of concept, pilot, and final hand-off.
Related categories:
PHP
SQL
MySQL
Database Programming
Data Warehousing
Business Intelligence
ETL
API Development