Snowflake POC: Scalable data access for enhanced reporting
Project Overview
This project aimed to evaluate Snowflake as a potential data warehousing solution to replace an outdated in-house system. The goal was to improve data accessibility, flexibility, and scalability for clients, allowing for more efficient data usage and enhanced operational efficiency.
Problem Statement
The in-house data warehousing solution was not scalable enough to meet clients growing needs, limiting their ability to access and leverage data effectively. A modern, flexible solution was required to support various data needs and streamline data sharing processes.
Key Findings
- Scalability and Flexibility: The existing data warehousing solutions lacked the flexibility and scalability required by clients, hindering efficient data access and utilization.
- Modernization Need: A modern solution was necessary to support diverse data requirements and provide seamless data sharing.
- Platform Evaluation: The project focused on evaluating Snowflake capabilities as a more flexible and scalable alternative to the current system.
Implemented Solution
To address the limitations of the existing system, the following steps were implemented:
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Research and Development:
Extensive research was conducted to evaluate Snowflake's capabilities, ensuring it met the project’s scalability, flexibility, and data access needs.
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Data Integration:
A solution was developed to efficiently transfer data from the existing Greenplum database to Snowflake, ensuring a smooth transition.
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Data Warehouse Creation:
Two distinct data warehouses were developed within Snowflake, each tailored to meet specific client reporting and data analysis requirements.
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Enhanced Data Sharing:
Snowflakes data-sharing features were leveraged to allow clients to seamlessly access and share data, replacing the previous in-house solution with a more flexible and collaborative platform.
Results
The POC successfully demonstrated Snowflake’s capabilities, significantly enhancing client data accessibility and operational flexibility. This transition laid the foundation for future development of new data products and services. As a result, the project contributed to a 25% increase in revenue and paved the way for potential future products valued at $50,000 per customer.