Analytics For Retail with Generative BI

Problem Overview

The existing system was built on SAP BW, which relied on legacy technology, leading to inefficiencies in handling large volumes of data. Building new reports and dashboards was dependent on IT involving manual efforts and hence time consuming.

01. SystemBender’s Solution

SystemBender built the AWS Data Analytics Platform which replaced the SAP Business Warehouse with Amazon Redshift for scalable, cost-efficient data lakehouse capabilities. Raw data is now stored in Amazon S3, processed with Glue ETL pipelines, and transformed into optimized schemas in Redshift. AWS QuickSight provides interactive, visually appealing reports for enriched data analysis.

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02. Winning Strategy

Customer Trust: Spent 6 months educating the customer on AWS and aligning the data platform with their business roadmap. Collaborated across teams, including CIO and CFO, to pitch and present the solution to the CEO.

Demo: Built a sample-data demo in QuickSight to showcase Amazon Q's functionality and the future potential of the solution.

Technical Involvement: Pre-sales and delivery teams deeply engaged to create a compelling demo and address business challenges.

AWS Collaboration: Partnered closely with AWS to build the CEO pitch, support the demo, and structure commercials and funding, ensuring project success.

Commercials: Worked with AWS to craft attractive commercial terms.

03. The Result

We are leveraging AWS cloud-native data technologies to move Customer data into a centralized data platform to create an analytics layer for Customer’s end users to create dashboards and reports using only natural language. Anyone can now create and edit dashboard using natural English Language.