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Data Migration to Google BigQuery

To stay competitive, organizations must migrate data from legacy data warehouses like Oracle, Netezza, and Teradata to the cloud, specifically to Google BigQuery. BigQuery is a fully managed, AI-enabled data analytics platform, empowering organizations to extract maximum value from their data. 

 

Onix specializes in migrating legacy data to BigQuery. Leveraging our proprietary set of data migration tools, we address common challenges associated with on-premise data warehouses, including high operational and maintenance costs, inflexible architectures, performance issues, and data latency concerns. By transitioning data to BigQuery, organizations will be primed to harness the power of AI and advanced analytics capabilities.

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Benefits of data migration to BigQuery

BigQuery supports data processing for both small and petabyte-scale datasets. Perform data analytics without modifying your existing data warehouse.
Support for Petabyte-scale
datasets
Leverage real-time access to structured data storage and analytics, which are scalable and cost-effective for growing data volumes.
Reduced
analytics costs
Achieve a secure and scalable cloud data warehouse based on demand using its sophisticated cloud-powered SaaS architecture.
High
scalability
Improve the performance of your data analytics with BigQuery’s ability to execute in-memory queries.
In-memory
capabilities
BigQuery APIs can directly integrate with BI engine – including integration with features like data masking and authorized views.
Business intelligence
(BI) integration
With GoogleSQL, BigQuery features an ANSI-compliant SQL feature that supports data query language.
Compliance with
ANSI SQL

How Onix can help you

Migration from traditional data warehouses to Big Query:

We are experts in migrating traditional data warehouses like Netezza, Teradata, Oracle, MS SQL Server to BigQuery:

  • Understanding and assessing current database volumetrics, complexity metrics, dependencies to prepare a conversion plan with Eagle
  • Automating and converting code artifacts to BigQuery using Raven
  • Validating and assuring 100% code conversion with Pelican 
  • Expertise in historical data migration from traditional data warehouse to BigQuery with Pelican

Migration from other cloud platforms to BigQuery : 

Onix is the go-to  partner to streamline end-to-end  migration from  cloud platforms like Synapse (Azure), Snowflake, Redshift (AWS) to BigQuery with our Datametica Birds suite.

How we do it

 

To enable Google Cloud migration, Onix has the following set of data migration tools:

Eagle

Eagle is Onix’s migration planning tool that can perform a detailed assessment of the existing data warehouse. Eagle can help you develop a comprehensive data migration strategy with details about existing workloads, cloud optimization, and accurate estimation of the migration time and costs.

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Raven

Raven is Onix’s data transformation tool that can automate code conversion – including SQL and ETL – to cloud-native technologies. Raven can identify any source workload and transform it into the target format.

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Pelican

Pelican is Onix’s data validation tool that can automate data validation and reconciliation between the source and target data stores. Pelican provides data validation at a granular level including database tables, rows, and columns, without moving any data between the source and target systems.

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Birds in action

transformational value across the migration continuum

Pre-Migration

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ASSESSMENT

(Assess and Plan)

  • Current state deep dive analysis
  • Workload pattern analysis & underlying dependencies
  • Migration Plan Sprint detail
  • Recommendation & design

Migration Strategy

Migration

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TRANSFORM

(Code conversion Service)

  • SQL dialects to target SQL
  • ETL Mapping (ETL to ELT)
  • Reports, Queries and Ad-hoc workloads

Fully Converted Code

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RECONCILIATION

(Validation)

  • Cell level data validation
  • Data matching between cloud DB and on-premise
  • Migration & Optimization
  • Reduced application testing

100% Reconciled Data

Pre-Migration

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CLOUD OPTIMIZE

  • Analyze cloud utilization Identify tuning opportunities
  • Data model
  • Queries
  • Costs

Cost and Performance

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