Real-Time Analytics for a Leading SaaS Pioneer:
A Case Study
To enhance data integration and visualization for 10 billion monthly transactional data records and extract valuable insights
Implemented an Amazon Redshift data warehouse and Tableau dashboard for efficient data analysis
- Supported 100M+ transactions on a daily basis
- Saved infra costs by 34%
- 2.3X higher engagement
- 18% higher customer satisfaction
- Report accuracy improved to 96%
With billions of transactions flowing through our client’s global ecosystem, the capacity for real-time analytics isn’t merely an advantage – it’s an imperative. Real-time analytics empowers swift, informed decision-making and success in an agile, data-driven world.
Our client, a global leader serving 45,000+ brands in 60 countries, adeptly manages an astonishing 10 billion monthly transactions. Yet, a pivotal challenge emerged: the transformation of this vast transactional data into actionable insights. That’s where we stepped in, crafting a bespoke solution.
Together, we laid the foundation for a robust data warehouse, automated intricate data pipelines, and meticulously improved the data loading process. The outcome was nothing short of transformative, fundamentally reshaping their operations.
The Impact?
Infra Cost
Saved
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The primary challenge revolved around effectively managing and deriving valuable insights from a colossal volume of 10 billion monthly transactions within our client’s global ecosystem.
This required the implementation of real-time analytics for informed decision-making and optimizing the existing data infrastructure to reduce costs. Ensuring data accuracy and report reliability was another key aspect of the challenge.
At Algoscale, we crafted a clear and well-structured solution.
- Data Warehouse Creation: Implemented a scalable Amazon Redshift data warehouse to handle and process the enormous transactional data volume efficiently.
- Infrastructure Optimization: Optimized the existing data infrastructure to reduce costs while accommodating the substantial data load.
- Automated Data Pipelines: Developed and automated data pipelines to streamline data transfer and ensure up-to-date information.
- Business Intelligence: Leveraged Tableau for business intelligence, creating intuitive dashboards for quick access and enhanced data accuracy.
- Security Measures: Implemented security features, such as row-level security (RLS), to ensure authorized user access and protect sensitive information.
Tech Stack
