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Case Study

Bringing Retail Data Together for Consistent Business Reporting

Bringing sales, orders, customer, and inventory data into a central data warehouse, to give retail teams a more consistent foundation for cross-channel reporting and business analysis.

Industry
Retail & E-commerce
Capability
Data Engineering, ETL/ELT & Data Warehousing
Focus
Cross-Channel Business Reporting
Cross-Channel Reporting
Sales channels compared on one basis
Consistent Metrics
One definition for each business metric
Automated Pipelines
Less manual consolidation of datasets
Fresher Reports
Analytical reports refreshed on schedule

Business Situation

Retail Data Lives in Separate Platforms

Retail businesses manage sales, orders, customer information, and inventory across e-commerce platforms, point-of-sale systems, and enterprise applications. When these sources operate independently, reporting becomes difficult to standardise and analysts spend time consolidating data manually.

The Challenge

Why Reporting Was Hard to Standardise

  • Sales and inventory data distributed across systems.
  • Conflicting definitions of business metrics.
  • Manual consolidation of reporting datasets.
  • Delays in refreshing analytical reports.
  • Difficulty comparing performance across sales channels.

Case Flow

How Retail Data Reaches Business Reporting

  • Retail data sources
  • Automated ingestion
  • Transformation and quality checks
  • Central data warehouse
  • Business intelligence and reporting

TECHAIVV Capability Applied

One Warehouse for Retail Reporting

  • Data Ingestion

    Connect relevant commerce, inventory, and transaction sources.

  • ETL/ELT Automation

    Automate data extraction and transformation workflows.

  • Data Modelling

    Standardise products, orders, customers, and transactions.

  • Data Quality Controls

    Detect duplicates and reconcile important totals.

  • Data Warehouse Integration

    Publish structured datasets for dashboards and business intelligence.

How It Fits Together

From Retail Sources to Business Intelligence

Retail Data Sources

  • E-commerce platforms
  • Point-of-sale systems
  • Enterprise applications
  • Inventory systems

Central Data Warehouse

  • Ingestion
  • Transformation
  • Quality Checks
  • Automated ETL/ELT workflows
  • Standard products, orders, customers and transactions
  • Reconciled totals

Reporting

  • BI dashboards
  • Business reports
  • Channel comparison
  • Analyst access

Outcome Snapshot

A Consistent Foundation for Cross-Channel Reporting

A unified analytical data environment can provide a more consistent foundation for cross-channel reporting and business analysis. Measure success through report preparation time, data freshness, reconciliation discrepancies, and pipeline reliability.

  • Report Preparation Time

    Time analysts spend preparing report data.

  • Data Freshness

    How current the data behind each report is.

  • Reconciliation Discrepancies

    Differences between totals across systems.

  • Pipeline Reliability

    How consistently the pipelines run and deliver data.

Related Services

Explore the services applied in this case study, or combine them into one program for your own project.

Let’s Build Together

Spending Too Long Consolidating Reports?

Tell us where your sales, order, and inventory data lives, and we will discuss how a central data warehouse could support your reporting.

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  • Ingestion
  • ETL/ELT
  • Data Modelling
  • BI & Reporting