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Eureka

LTIMindtree’s automated Eureka framework seamlessly modernizes legacy data ecosystems and cloud Data Warehouses (DW) with Google Cloud Platform (GCP) Big Query. Eureka framework addresses the core challenges of migrating and modernizing legacy data solutions to GCP Data Cloud solutions, making your data transformation journey timely, predictable, and cost-effective while de-risking and easing the transition path.

We helped a leading Television Brand Advertising Company reduce their operational costs by 60% by leveraging Google Cloud Platform to deliver faster time to insights with zero infrastructure management.

Our Framework

Smart Analyzer

Provides intelligent insights into the legacy data platform and formulates data cloud migration strategies to GCP Big Query (BQ) within days.

Inventory Analysis – Analyses database inventory and provides distribution by object type.
Complexity Distribution – Provides complexity distribution of objects to be migrated.
Debt Analysis – Provides technical debt details that can help descope non-relevant objects for migration.
Risk Analysis – Provides information on risk factors associated with migration from Legacy DW to BQ.

Migrate

Migrates legacy data platform to GCP BigQuery and validates it. Achieves 50-60% overall automation across the migration value chain.

Meta Migrator – Tables, Views, and Sequences.
SQL Converter – SQL Scripts, BTEQs, Stored Procedures, and UDFs.
Data Migrator – Migrates historical data and selectively incremental data.
Data Validator – Validates historical and incremental data between BigQuery and legacy data warehouse.

Cloud SQLizer (ETL Converter)

Accelerates migration of legacy Extract, Transform, and Load (ETL) jobs/packages to BigQuery SQL/procedures.

Cloud SQLizer Framework

Extract – Connects to ETL repositories and extracts ETL workflows and dataflows with dependency details in XML format.
Analyze – Classifies ETL workflow complexity and highlights migration risk.
Transform – Converts workflow XMLs to JSON and JSON to BQ SQL.
Deploy – Deploys as BigQuery SQL/stored procedure.
Validate – Executes transformation pipelines and validates incremental data loads using Eureka Data Validator.

FinOps

Eureka framework provides cost visibility for BigQuery Data Platform to enable recurring cost visibility, monitoring and control, and optimization

Eureka FinOps – TCO Management Framework

Cost Visibility – Analyzes BigQuery Information_Schema query logs and provides usage and associated costs across storage and compute
Cost Monitor – Provides daily briefing and budget alerts, current usage trends, and future estimates
Cost Control – Gives insights into avenues to control costs on GCP BigQuery
Cost Optimization – Analyzes complex and long-running queries and provides recommendations