AWS-Powered Retail Analytics Modernization for Leading Furniture Retailer

About Customer

The customer is a leading furniture brand in India, known for ergonomic design, modern aesthetics, and premium craftsmanship. With a growing ecommerce presence alongside its established retail network, the organization manages large volumes of sales, customer, marketing, and inventory data across multiple digital platforms.

To support their expanding online business and improve decision-making, the company needed a unified analytics platform capable of consolidating data scattered across Shopify, CRM, and marketing tools.

Industry​

Industry​

Retail, Furniture Retail, Ecommerce

Solution

Solution

Retail Analytics, Data Modernization, AWS Data Analytics

Location

Location

India

Key Objectives

The organization’s primary goal was to achieve faster, more reliable visibility into ecommerce and retail performance. Leadership sought to eliminate reporting delays, unify fragmented datasets, and build trusted KPIs that would drive timely, informed decision-making. The key objectives were to:

  • Consolidate ecommerce, CRM, and marketing data into a unified AWS data lake
  • Automate daily and weekly reporting cycles
  • Improve data accuracy, consistency, and governance
  • Deliver real-time dashboards for leadership and regional teams
  • Establish a scalable foundation for AI/ML-driven personalization and forecasting
The Challenge

Before modernization, the company struggled with data fragmentation across Shopify, CRM tools, and multiple marketing platforms. The absence of a centralized system created inconsistent reports, slower decision cycles, and limited visibility into true business performance.

Leadership lacked a single source of truth, reporting processes took 2–3 days, and teams spent significant time manually aggregating data. The company needed a modern data architecture that would:

  • Unify data from multiple disconnected sources
  • Automate daily and weekly transformation pipelines
  • Improve KPI accuracy and reliability
  • Enable near real-time reporting and secure, role-based visibility
The Solution

Rysun partnered with the customer to design and deploy a modern, serverless AWS analytics platform that automated data ingestion, strengthened governance, and delivered real-time insights through QuickSight dashboards.

To achieve this, Rysun engineered a multi-layered architecture using AWS Glue, Amazon S3, Redshift, and QuickSight — creating a secure and scalable environment for unified reporting and advanced analytics.

  • Data Lake Foundation: A centralized Amazon S3 data lake was deployed with Raw, Curated, and Analytics zones, creating the company’s new single source of truth.
  • Automated ETL & Transformation: AWS Glue jobs automated ingestion, cleansing, and standardization across ecommerce, CRM, and marketing datasets — replacing manual consolidation efforts.
  • Analytics & Visualization: Amazon Redshift enabled cross-domain analytics for revenue, customers, product performance, and regional visibility. Amazon QuickSight was implemented for interactive dashboards tailored to leadership, marketing, and operations teams.
  • Security & Governance: IAM, CloudTrail, and CloudWatch enforced secure access, compliance, audit trails, and proactive monitoring of ingestion pipelines.
  • Role-Based Access: Dashboards and datasets were segmented by region and role, ensuring secure, context-specific insights for leadership, managers, and franchise teams.
The Benefits

The new AWS analytics platform transformed how business teams accessed, interpreted, and acted on ecommerce and retail insights. Reporting cycles that previously took several days were replaced with automated, near real-time dashboards that improved operational agility and decision velocity.

Leadership now has accurate, unified visibility across online and offline channels, while improved data quality and governance ensure long-term trust and scalability.

Quantitative Impact

  • Reporting latency improved from 2–3 days to real-time, daily updates, enabling faster leadership decision-making.
  • Data accuracy increased from ~80% to 98%, creating a trusted foundation for business insights.
  • Manual reporting effort was reduced by 70%, allowing teams to focus on higher-value, revenue-driving activities.
  • Dashboard refresh times dropped from over 1 hour to under 5 minutes, dramatically improving analytics responsiveness.

Qualitative Impact

  • Leadership visibility strengthened across online and offline channels
  • Improved forecasting and marketing campaign measurement
  • Better cross-team collaboration across sales, marketing, and operations
  • Established a modern foundation for future AI/ML-driven initiatives
Rysun is an AWS Advanced Tier Partner

Rysun is a CMMI Level 5-certified engineering and consulting partner specializing in AI, data modernization, and cloud transformation. As an AWS Advanced Tier Partner, Rysun helps enterprises modernize legacy systems and build scalable analytics platforms that deliver measurable outcomes. Our deep retail and ecommerce expertise enables fast, business-aligned implementations using the latest AWS services.

Technology Stack

The solution was built using AWS serverless and managed services:

  • Data Lake Storage: Amazon S3
  • Data Integration & ETL: AWS Glue
  • Data Warehousing: Amazon Redshift
  • Analytics & Dashboards: Amazon QuickSight
  • Security & Compliance: IAM, AWS KMS, CloudTrail
  • Monitoring & Logging: Amazon CloudWatch