Enterprise data platforms are undergoing a significant evolution to meet the changing needs of companies that are building generative AI applications. While traditional data platforms were designed for specific tasks, like data warehousing or data science, generative AI requires an evolution towards improved data quality, scalability, accessibility, and governance, along with tightly integrated gen AI model execution, to unlock all of your data’s full potential and drive innovation. Migrating to a modern AI ready data platform is paramount for organizations to be successful in the AI era.

Google Cloud’s unified data platform is designed to meet today’s AI needs. Together, BigQuery and Dataproc provide a path to data modernization with built-in capabilities for data lakehouse architectures including multimodal data, multi-engines (SQL, Spark, Python), streaming, governance and integrated ML/AI capabilities. With superior price-performance across data workloads at any scale, organizations can run all of their workloads, delivering best in class ROI and faster time to value.

Customers like Veo have transformed their ability to access, understand, and use data by migrating to Google’s Data Cloud, with 30% lower total cost of ownership and data processing costs. At Veo, BigQuery and Looker have become the heart of their machine learning operations by making it easy for teams to create, deploy, and manage models at scale. Seattle Children’s Hospital migrated 650+ databases to BigQuery to build a sustainable growth strategy to serve business demands for AI/ML, natural language processing and image analytics. General Mills completed a data lake migration to Google Cloud 30% faster than planned which helped them offer new capabilities and streamlined data management practices.  By migrating to Google Cloud, including moving from Hadoop to Dataproc, Choreograph, a WPP company, saw over a 50% decrease in cloud costs.

However, migrating to a cloud-based platform is not a trivial undertaking: It requires running two systems in parallel during the migration period and, when coming from another cloud, data egress fees are incurred on top of costly implementation services. 

To help organizations accelerate time to value with data and AI, we are excited to introduce a Data Platform Migration incentives program targeted at data warehouse and data lake migrations from on-premises and clouds, by new and existing Google Cloud customers. The program makes it simpler, easier and more cost effective than ever to migrate workloads to an AI ready ecosystem. In addition, our enhanced migration services tooling makes these journeys more seamless than ever.

Migration incentives 

The Data Platform Migration Incentive Program provides significant benefits to organizations looking to modernize their data foundations, accelerate their gen AI readiness, unlock the full potential of their data, and drive innovation and growth:

• Google Cloud credits: Offset 1st year costs of running two systems in parallel while migrating.

• Implementation credits: Enjoy a smooth transition with implementation credits that can be applied to Google or eligible partners.

• Cloud egress credits: Credits to cover egress costs associated with moving data from AWS or Azure to Google Cloud (up to $250k).

Migration services and tools

BigQuery migration service provides a comprehensive set of tools to migrate data into BigQuery, so you can run analytics at scale and build an integrated data-to-AI platform. With services such as the BigQuery migration assessment, Batch SQL translator and the Interactive SQL translator, you can migrate your data quickly, efficiently, and with minimal downtime. BigQuery migration service is now being expanded to cover migrations from Hadoop & Spark into BigQuery and Dataproc. New features in the 2024 roadmap include automatic assessment of on-prem Hadoop clusters and automatic table migration for open table formats such as Iceberg. Usage of BigQuery migration services tools has grown by over 400% YoY, with thousands of customers using these services to migrate from other providers during this period.

Build  your unified, AI-ready data platform with BigQuery and Dataproc

Google Cloud offers several advantages to organizations exploring new generative AI initiatives with BigQuery and Dataproc:

• Built-in intelligence: Integration with AI capabilities, including Gemini and many out-of-the-box ML/AI models, enables organizations to leverage AI to accelerate their business outcomes.

• All data and workloads in one platform: Support for a diverse range of data formats and workloads makes Google Cloud a single destination for an ever-growing number of use cases and all your data needs.

• Simplicity at its finest: BigQuery and Dataproc’s serverless architecture and unified UI simplify data management and analysis for users of all skill levels.

• A pocketbook-friendly powerhouse: With cost-effective data processing, streaming, and governance capabilities, BigQuery and Dataproc offer a lower TCO compared to alternative cloud-based enterprise lakehouse solutions.

With new migration service tools and the Data Platform migration incentive program, you can begin enjoying these capabilities, and get started on your generative AI journey. To learn more, contact your sales representative today, or if you’re new to Google Cloud, use the contact form here. Get ready to embark on a transformative data journey today.