Problem Statement
The client, operating in the telecommunications sector, struggled with slow query performance and high data latency in their 4TB dataset on BigQuery. They required a solution to improve query efficiency, streamline data pipelines, and enhance reporting for their peer-to-peer (P2P) texting platform.
Approach & Solution
To tackle the client's challenges, we restructured and optimized their data infrastructure on Google Cloud Platform, focusing on performance improvements and reporting capabilities.
- We restructured the 4TB dataset in BigQuery, focusing on optimizing query performance.
- Data ingestion pipelines were reconfigured to reduce latency from Pub/Sub and external SQL connections.
- We set up materialized views to enable more efficient data analysis.
- Implemented architectural best practices to streamline the team’s workflows and improve data management processes.
Results & Outcomes
The improvements in query performance resulted in a significant reduction in query times, while data pipeline optimizations reduced latency by 30%. These enhancements led to quicker decision-making and team efficiency, translating to cost savings and better operational workflows.
Tools & Technologies used
- Google Cloud Platform (GCP)
- BigQuery
- Google Pub/Sub
- Data Lake Design
- ETL Tools
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