Centralized sales data aggregation and real-time dashboards

Purpose

1.1. Centralize all sales data from multiple retail locations or channels under alcohol retail monopoly into a unified repository.
1.2. Enable real-time or near-real-time extraction, transformation, and loading (ETL) of sales, inventory, and customer interaction data for up-to-date analytics.
1.3. Feed data into interactive dashboards for rapid insights on sales trends, product performance, and store-level metrics.
1.4. Support compliance, reporting, and inventory optimization through a single source of truth.

Trigger Conditions

2.1. New sales transaction recorded at any POS location or eCommerce site.
2.2. Daily scheduled batch for collecting aggregated sales summaries.
2.3. Inventory level updates (e.g., low-stock alerts).
2.4. Data file (CSV/API/post) upload by store managers.
2.5. Backend database update or push event.
2.6. Changes in customer membership/loyalty status.

Platform Variants

3.1. Microsoft Power BI
• Feature: REST API—Configure for data ingestion via POST requests from POS systems.

3.2. Google Data Studio
• Feature: Data Connector—Setup Google Sheets/API connectors for real-time updates.

3.3. Tableau
• Feature: Web Data Connector/API—Pull data from central store/ERP or cloud storage.

3.4. Salesforce
• Feature: REST Bulk API—Ingest sales records and inventory stats on transaction completion.

3.5. SAP BW/4HANA
• Feature: Data Integration API—Scheduled ETL from distributed retail data systems.

3.6. Amazon Redshift
• Feature: COPY/UNLOAD Command/API—Automate data movement from S3 or POS logs.

3.7. Snowflake
• Feature: Streams & Tasks—Monitor new data exchanges and trigger real-time ingestion.

3.8. Oracle Cloud Analytics
• Feature: Data Integrator REST API—Connect directly to retail store transaction feeds.

3.9. BigQuery
• Feature: Streaming Insert API—Load sales event data as soon as transactions complete.

3.10. Azure Synapse Analytics
• Feature: Data Pipeline Orchestration—Automate nightly data aggregation jobs.

3.11. Looker
• Feature: Looker API—Update dashboards using direct API or scheduled fetch.

3.12. Domo
• Feature: DataFlows/API Connector—ETL sales data for dashboard visualization.

3.13. Klipfolio
• Feature: Dynamic Data Source—Pull batch or streaming data via REST endpoints.

3.14. Qlik Sense
• Feature: Qlik REST Connector—Live load transactions for visualization.

3.15. Splunk
• Feature: HTTP Event Collector—Send POS log data for indexed search and reporting.

3.16. MongoDB Atlas
• Feature: Realm Triggers—Invoke aggregation jobs on insert/update of sales.

3.17. Airbyte
• Feature: Custom Source to Analytics Warehouse—Control batch or event ingestion.

3.18. Fivetran
• Feature: Automated Connectors—Scheduled extraction from retail databases to analytics.

3.19. Segment
• Feature: Source API—Send structured transaction events to analytics destinations.

3.20. Zapier
• Feature: Webhooks + Multi-step Automation—Forward sales data to dashboard platforms.

3.21. Smartsheet
• Feature: Data Uploader—Automate import of sales CSVs into report templates.

3.22. Sisense
• Feature: REST API / ELT Scheduler—Sync ERP and retail data for unified dashboards.

Benefits

4.1. Instant sales analytics for executive/operational decisions.
4.2. Secure compliance reporting in line with state-owned mandates.
4.3. Increased sales, inventory accuracy, and rapid response to trends.
4.4. Reduced manual data reconciliation and human error.
4.5. Increased transparency for public sector audits and consumer trust.