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Migrating from Greenplum to Google BigQuery

7 Petabytes of data, etl and object migration and reconciliation for a leading telecom provider

Project Overview

A telecom provider managing 7 petabytes of data approached Travinto Technologies to migrate from Greenplum to Google BigQuery. The project involved handling complex database objects (triggers, cursors, SQL scripts, ETL jobs, and aggregations) while ensuring performance, scalability, and seamless integration using GCP components like Dataflow, Cloud Functions, Pub/Sub, and Vertex AI.

Challenges

  • Migrating 7 petabytes of data with minimal downtime.
  • Converting complex SQL, triggers, cursors, and ETL processes into BigQuery-compatible formats.
  • Managing partitioning problems due to schema differences between Greenplum and BigQuery.
  • Ensuring data governance and compliance during and after migration.
  • Optimizing for cost efficiency using BigQuery and GCP components.

GCP Components Used

  • Google Cloud Dataflow - Streaming data processing for ETL migration.
  • Google Cloud Functions - Event-driven execution of migration tasks.
  • Google Pub/Sub - Real-time messaging for data pipeline orchestration.
  • Google Vertex AI - Data insights and ML-driven data optimization.

Migration Process

Detailed analysis of Greenplum database objects (triggers, cursors, SQL scripts, ETL pipelines) using X2XAnalyzer identified schema differences and partitioning issues that would need to be addressed during migration.

X2XConverter automatically converted Greenplum-specific SQL, triggers, and ETL processes into BigQuery-compliant code. Custom aggregations, window functions, and partitioning logic were re-engineered to optimize performance in BigQuery’s architecture.

During the migration, partitioning problems arose due to differences in how Greenplum and BigQuery handle partitioned tables. Travinto used BigQuery's native partitioning along with Dataflow to adjust the data schema, ensuring efficient partitioning and faster query execution. X2XValidator was used for data reconciliation to ensure all data was migrated without any discrepancies.

Results and Benefits

Data Governance and Compliance

Through X2XValidator and BigQuery’s auditing tools, the migration maintained full data governance and compliance with industry regulations. This helped the telecom provider adhere to strict privacy and data security guidelines.

Cost Savings and Efficiency

By leveraging BigQuery’s pay-as-you-go model and using X2XFinOps to optimize queries, the client realized a 35% reduction in cloud spending. Pub/Sub and Dataflow pipelines provided real-time cost-effective data streaming and processing solutions.

Data Monetization

With Vertex AI and BigQuery’s advanced analytics capabilities, the telecom provider was able to monetize their data by extracting actionable insights. This resulted in a 20% increase in revenue from targeted customer offers and better network optimization.

7 Petabytes of Data Migrated Seamlessly

The migration of 7 petabytes of data, including customer records, call logs, and usage statistics, was successfully completed with minimal downtime. Thanks to X2XValidator, the data was reconciled with zero loss, ensuring business continuity.