SoftwareOne case study

Popular Book Company Proves the Value of Modern Retail Analytics with a Generative BI Platform on AWS

Popular Book Company needed to modernise its data infrastructure to turn massive volumes of retail data into actionable insights, moving from a slow, legacy system to a dynamic, AI-enabled cloud platform.

As a leading retailer, Popular Book Company recognised that its existing reporting infrastructure, running on SAP Business Warehouse (BW), was creating challenges. The system struggled with an ~ 11TB data volume, leading to slow performance, while the process for generating new reports was manual and time-consuming. This made it difficult for management, merchandising, and operations teams to access timely insights for strategic decision-making .

Popular wanted to understand the benefits of a modern, scalable solution that could introduce next-generation analytics and Generative BI capabilities. The objective was to demonstrate how a centralised data repository could automate workflows and provide stakeholders with interactive, visually rich dashboards.

Partnering with SoftwareOne, Popular Book Company successfully implemented a new data analytics platform on AWS. The solution uses a powerful data lakehouse architecture to process data from sources like LSBC retail data and SAP ERP and use Amazon Q in QuickSight to answer business critical questions using natural language. This successful implementation proves the efficiency of the new system and lays the foundation for a future driven by data.

Faster, Deeper Insights
Complex queries across years of sales and ERP data, delivering insights into revenue, margin, and year-over-year trends
70% Reduction in Reporting Time
The automated data ingestion and transformation demonstrated the reduced time to generate key business reports from days to minutes.
Enhanced Decision-Making
Interactive dashboards and Gen-AI queries with Amazon Q proved that management can get immediate, actionable intelligence to optimise sales and operations.

Client: Popular Book Company
Industry: Retail
Platform: AWS Cloud
Services: Application Services: Data Analytics
Country: Singapore

SoftwareOne delivered more than what they promised. The speed and flexibility of the new AWS platform are remarkable. Our teams are more empowered than ever, and with Generative BI, we are asking questions of our data that we never thought possible. This is the foundation for our next phase of growth.

Popular Book
Retail General Manager

Legacy reporting system hinders a data-driven retail strategy

For years, Popular Book Company has been a household name in retail, but its underlying reporting infrastructure was struggling to keep pace. The company's reporting, which ran on a legacy SAP Business Warehouse (BW) system, was inefficient at handling the massive volumes of data generated by its retail and e-commerce operations. With data size growing to approximately 11TB, performance was slow, and the user experience for those trying to access dashboards was poor.

A significant challenge was the manual and time-consuming process of retrieving data for new analysis. This bottleneck prevented key teams—from C-level executives to merchandise and operations managers—from performing agile analysis on critical KPIs like revenue contribution, budget variance, and top-selling products. The company wanted to build a Data & AI POV to understand the benefits of adopting an AWS-based platform for its analytics needs.

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A modern data lakehouse on AWS with Gen-BI

SoftwareOne partnered with Popular to design and implement a Data Analytics Platform built on AWS. The project was structured the engagement to demonstrate the powerful capabilities of a modern cloud data architecture.

The core of the solution involved replacing the on-premise SAP BW system with a scalable data lakehouse on AWS. The architecture leverages.

Amazon S3: To store 13 months of historical and incremental raw data from sources including SAP ERP and LSBC retail systems.
AWS Glue: To perform ETL (Extract, Transform, Load) processes, automating the cleaning and structuring of data as it moves from the raw data lake (Bronze layer).
Amazon Redshift: As the central, high-performance cloud data warehouse, serving as the single source of truth for all structured data for transformed (Silver) and aggregated (Gold) layers.
Amazon QuickSight: For creating intuitive and interactive dashboards to visualise key KPIs.
Amazon Q in QuickSight: To showcase Generative BI capabilities, allowing users to ask questions in natural language and receive instant visualisations and answers.

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The final and most impactful step was connecting this curated data to Amazon QuickSight for reporting and visualisation. This allowed for the creation of intuitive, interactive dashboards covering KPIs such as revenue analysis, year-over-year trends, and top sales products. Critically, the solution showcased the Generative BI capabilities of Amazon Q in QuickSight. This feature empowers business users to ask complex questions of their data in natural language and receive immediate answers and dynamic visualisations, moving beyond static reports to a truly interactive analytical experience.

This solution provided a robust, end-to-end data pipeline, from ingestion to visualisation, establishing a foundation for all future analytics use cases.

Driving growth with faster, smarter insights

With the new system, reports on revenue, cost, and margin analysis that once took days are now available on demand. Business users can now independently explore data through interactive QuickSight dashboards, analysing year-over-year trends, drilling down into revenue contribution by store or department, and identifying top-performing products without IT intervention.

We had a wealth of data but couldn't unlock its value quickly enough. Our teams needed self-service access to insights, not long waits for manually pulled reports. We wanted to make decisions based on what's happening today, not last month.

Popular Holdings

IT Director

This newfound agility enables more informed, data-driven decision-making across the organisation, from strategic C-level planning to tactical operational adjustments. The scalable AWS infrastructure ensures that as Popular's data continues to grow, its analytics capabilities can grow with it, providing a solid platform to support its future ambitions.