Teradata to BigQuery migration
Migrate your on-premises Teradata warehouse to Google Cloud and take advantage of cost-effective data services and solutions.
BigQuery differentiation for Teradata Migration
Migrating from Teradata to Big Query means migrating from server based to serverless architecture. Migrating from Teradata to Big Query is an attractive option because It doesn’t require provisioning for storage and computing resources in advance. It allows streaming ingestion of huge volumes of data. Owing to column wise data store in BigQuery, high levels of compression of data is obtained. BigQuery has integrations with various BI tools like Tableau, Looker and MicroStrategy. The traditional ETL tools and processes are eliminated.
Our experts and partnerships get you there
Kick your Teradata-Google Cloud migration into high gear with TheLogicPlus’s proven project experience, world-class migration program, and rock-solid partnership with Google Cloud.
Take advantage of Google BigQuery
Migrating from Teradata to Big Query means migrating from server based to serverless architecture. Migrating from Teradata to Big Query is an attractive option because It doesn’t require provisioning for storage and computing resources in advance. It allows streaming ingestion of huge volumes of data. Owing to column wise data store in BigQuery, high levels of compression of data is obtained. BigQuery has integrations with various BI tools like Tableau, Looker and MicroStrategy. The traditional ETL tools and processes are eliminated.
TheLogicPlus Differentiation for Teradata to bigquery migration
TheLogicPlus has developed a number of tools and accelerators to deliver the value from the migration to BigQuery. Through these assets, efforts savings of up to ~20-40% can be achieved as part of the end-end data movement. Some of these assets are listed here:
Pulse On-prem data landscape discovery, performance bottleneck identification & optimization facilitating strategic decision making before migration
Schema Optimizer - Schema migration supported to facilitate validation by DBA prior to data movement. ETL code analyzer to provision replication of ETL mappings in target system
Query Convertor - 50-60% automated ANSI compatible conversion of SQL views & queries
DWH Mover - Historical data movement facilitated with basic sanity reconciliation. Additional flexibility to simultaneously move data to multiple targets in the same platform
Data Lake Mover - Hadoop discovery and data migration for seamless movement to GCP
Smart Data Validator - Elaborate row-level & column level verification with potential to plug-in in multiple migration use cases
When all of these are taken into consideration, the opportunity for savings and benefits for organizations are astounding. Through the newfound ability to provide more comprehensive intelligence to the organization in a faster and more agile manner, large enterprise organizations could easily expect overall savings and benefits in the millions to tens of millions of dollars by migrating from on-premises EDW solutions to Google BigQuery.