Home / Portfolio / Retail Data Platform Modernization

Retail Industry

1.2 Years

16 members

Hyderabad

Retail Data Platform Modernization

Modernized a legacy retail analytics ecosystem into a scalable, cloud-native data platform using Azure Data Factory, Snowflake, Power BI, Azure Key Vault, RBAC, and enterprise-grade monitoring.

Azure + Snowflake Enterprise Data Engineering Solution

Modernizing legacy retail data systems into a scalable, secure, analytics-ready cloud ecosystem using Azure Data Factory, Snowflake, Power BI, Azure Monitor, and enterprise-grade SRE practices.

Project Overview

Revuteck designed and implemented a modern retail data platform by migrating legacy ETL and reporting workloads into a scalable Azure and Snowflake ecosystem. The solution automated ingestion pipelines, improved data quality validation, enabled governed analytics, strengthened monitoring, and established production-ready SRE operations.

The platform was built to support high-volume retail operations, including sales, inventory, product, customer, and operational analytics, while improving performance, scalability, security, and reporting reliability.

Project Highlights

Automated Azure Data Factory ingestion pipelines
Snowflake-based enterprise data warehouse
Multi-layer validation and reconciliation framework
Power BI reporting enablement
Azure Monitor-based operational observability
Production support and incident management setup
Secure Key Vault and RBAC implementation
Modular cloud-native architecture

Deliverables

Industry

Project Info

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Technologies test

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Research

Project Research

An inside look at how we identified the core problems, structured our approach, and delivered a scalable solution.

Business Challenges

The existing retail platform struggled with scalability, slow reporting cycles, fragmented ETL workflows, manual interventions, and limited monitoring visibility.

-Legacy platform modernization
-Retail analytics scalability
-Pipeline automation
-Production monitoring
-Secure enterprise reporting

Project Scope

The project included migration planning, Azure Data Factory development, Snowflake modeling, validation frameworks, Power BI enablement, production support, and SRE implementation.

-Cloud-native architecture
-Automated ingestion pipelines
-Curated analytics layers
-Monitoring dashboards
-Incident response workflows

Development Approach

The engineering phase focused on reusable pipeline design, metadata-driven processing, modular transformation logic, and enterprise monitoring standards.

-Azure integration patterns
-Snowflake optimization
-Data reconciliation strategy
-Operational reliability
-SLA-driven support model

Solution Provided

A layered architecture was designed to separate ingestion, storage, transformation, reporting, and monitoring for better scalability and maintainability.
-Reliable data ingestion
-Secure cloud storage
-Optimized reporting datasets
-Automated quality checks
-Production-ready observability

Process

Process Flow

We build scalable mobile and web applications tailored to industry-specific workflows, user expectations, compliance requirements, and long-term business growth.

Discovery & Assessment

Architecture Design

Pipeline Development

Azure Storage Implementation

Snowflake Data Modeling

Data Validation Framework

Reporting & Analytics

Production Support & SRE

Discovery & Assessment

Analyzed the existing legacy retail data ecosystem, reviewed ETL workflows, identified source systems, documented reporting dependencies, and gathered business modernization requirements for cloud migration planning.

Key Activities:
-Source system analysis
-Legacy workflow assessment
-Business requirement gathering
-Reporting dependency analysis
-SLA and operational review
-Migration scope definition
-Risk and impact analysis

Architecture Design

Designed a scalable and secure Azure + Snowflake cloud-native architecture with separate ingestion, storage, validation, transformation, reporting, monitoring, and support layers for better maintainability and operational reliability.
Key Activities:
Azure architecture planning
Snowflake warehouse design
Data layer separation
Security and RBAC planning
Monitoring architecture setup
Validation framework planning
Scalable pipeline strategy

Pipeline Development

Developed automated Azure Data Factory pipelines for ingestion, orchestration, scheduling, dependency handling, retry management, audit logging, and metadata-driven data processing workflows.
Key Activities:
ADF pipeline creation
Dynamic parameter implementation
Automated scheduling setup
Dependency orchestration
Retry and failure handling
Audit logging integration
Metadata-driven execution

Azure Storage Implementation

Configured Azure Blob Storage landing, archive, reject, audit, and temporary processing zones to support secure raw data storage, traceability, structured ingestion, and operational data management.
Key Activities:
Landing zone configuration
Archive structure setup
Reject and failed file handling
Audit storage implementation
File partition management
Data retention planning
Secure cloud storage setup

Snowflake Data Modeling

Created Snowflake RAW, STAGE, CURATED, MART, and AUDIT schemas with optimized tables, SQL transformations, stored procedures, curated reporting models, and enterprise-grade warehouse structures.
Key Activities:
-Snowflake schema creation
-Table and warehouse design
-SQL transformation development
-Stored procedure implementation
-Curated analytics modeling
-Reporting mart preparation
-Query optimization setup

Data Validation Framework

Implemented a comprehensive enterprise validation framework including schema validation, reconciliation checks, duplicate detection, null validation, business rule verification, and source-to-target consistency checks.
Key Activities:
-File-level validation
-Schema validation checks
-Duplicate detection logic
-Business rule validation
-Record reconciliation checks
-Error handling workflows
-Audit and logging validation

Reporting & Analytics

Integrated Power BI dashboards with curated Snowflake datasets to deliver executive reporting, retail analytics, operational KPIs, sales visibility, and faster enterprise reporting capabilities.
Key Activities:
-Power BI integration
-KPI dashboard creation
-Retail analytics reporting
-Semantic model preparation
-Curated data consumption
-Reporting optimization
-Executive dashboard enablement

Production Support & SRE

Implemented production support workflows, Azure Monitor alerts, incident management processes, SLA tracking, RCA documentation, pipeline observability, and SRE-driven operational reliability practices.
Key Activities:
-Azure Monitor configuration
-Incident response workflows
-SLA monitoring setup
-Pipeline observability
-Root cause analysis
-Production issue management
-Operational support documentation

Features

Key Features

We build scalable mobile and web applications tailored to industry-specific workflows, user expectations, compliance requirements, and long-term business growth.

(01)

Intelligent Dashboard

-Real-time retail analytics visibility
-Pipeline execution monitoring
-Reporting performance insights
-Operational KPI tracking
-Business-ready dashboards
-Executive reporting metrics

🏗

(02)

Automated Pipeline Orchestration

-Automated ingestion workflows
-Dynamic pipeline scheduling
-Retry and failure handling
-Metadata-driven execution
-Dependency management
-Audit logging integration

🔐

(03)

Enterprise Data Validation

-Schema validation checks
-Duplicate detection logic
-Null and data-type validation
-Source-to-target reconciliation
-Business rule validation
-Error and reject handling

👥

(04)

Secure Snowflake Architecture

-Multi-layer Snowflake schemas
-Optimized warehouse structure
-Curated reporting models
-Role-based access control
-Secure enterprise governance
-Query performance optimization

💰

(05)

Production Support & SRE

-Azure Monitor integration
-Incident response workflows
-SLA tracking and monitoring
-Pipeline observability
-Root cause analysis
-Operational reliability management

📋

Home

Results

Project Results

We build scalable mobile and web applications tailored to industry-specific workflows, user expectations, compliance requirements, and long-term business growth.

0 %

Improved operational monitoring efficiency

0 %

Reduction in manual pipeline handling

0 X

Faster, scalable data processing capability

0 %

Improved reporting readiness and observability

Retail Industry

Admin

Client Review

“Revuteck successfully modernized our legacy retail data ecosystem into a scalable and highly monitored Azure + Snowflake architecture. The platform improved reporting reliability, operational visibility, and long-term scalability.”

Contact

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E-mail address

sales@revuteck.com

Phone number

+91-7032094811

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Retail Data Platform Modernization