Learn How Sporting Insights & Slalom Build Market-Intelligence-as-a-Service with AWS | S02EP32 | Lets talk about data show
Discover how Sporting Insights and Slalom create a scalable data pipeline; and build interactive dashboards with Amazon QuickSight that help retailers and brands track market share, spot trends, and plan for growth with data-driven confidence.
Lydia Ray
Amazon Employee
Published Aug 28, 2024
Sporting Insights, a leading research agency in the sports industry, partnered with Slalom, a modern consultancy, to build a scalable data pipeline and interactive dashboards that provide market-intelligence-as-a-service. They integrated various AWS services, including S3, Glacier, EKS, Snowflake, and QuickSight, to turn raw data from retailers and brands into actionable insights. The solution collects transactional data from multiple retailers, validates and standardizes it, and aggregates it into a Snowflake data model. This model then feeds Amazon QuickSight dashboards, allowing retailers and brands to track market share, spot trends, and plan for growth with data-driven confidence.
Key Highlights:
- Scalable data pipeline built with AWS services like S3, Glacier, and EKS for data ingestion, validation, and standardization.
- Transactional data from multiple retailers collected and aggregated into a Snowflake data model.
- Interactive dashboards in Amazon QuickSight with row level security to protect sensitive data.
- Retailers and brands can track market share, spot trends, and plan for growth with data-driven insights.
- Future plans include advanced features like basket analytics, weather impact analysis, and natural language querying with Amazon Q.
- Lessons learned: Ensure proper setup of row level security rules and align data models with dashboard requirements.
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Hosts of the show 🎤
Lydia Ray - Sr Analytics Solutions Architect @ AWS
Guests 🎤
- Robert Cobain - Head of Market Intelligence @ Sporting Insights
- Adam Saville - Senior Data & Analytics Consultant @ Slalom
Any opinions in this post are those of the individual author and may not reflect the opinions of AWS.