Google Cloud Evolved Data Warehouse Modernization
Moving to the cloud and being cloud-native are critically important for organizations today. For many, this starts with data warehouse modernization. As data volumes grow exponentially and data science and data management grapple with the challenges of scalabilty, elasticity, data latency and compatibility, the need modernize one’s data warehouse becomes apparent. Successful data warehouse modernization allows organizations to leverage cloud technologies, support multi-cloud and cloud-hybrid strategies, as well as supporting semi-structured and unstructured data. Many data warehouses started in on-premises environments where they served countless institutions very well. But now, organizations are migrating data warehouses to the cloud as they adopt cloud analytics and AI on their journey to digital transformation. Google Cloud is one of the leaders at the forefront, along with Informatica.
We recently had the pleasure of listening to Debanjan Saha, GM Data Analytics at Google Cloud, during a fireside chat with Jitesh Ghai, Chief Product Officer at Informatica, during Informatica World 2021. Google Cloud and Informatica have been strategic partners for several years and have helped many joint customers such as Sunrun, Feeding America, and SulAmerica to leverage the analytics power of Google Cloud. Informatica has also invested in providing best-of-breed capabilities for Google Cloud Platform (GCP) customers whether through deep integration with Google BigQuery or seamless subscription options via GCP Marketplace.
Data Warehouse Modernization Challenges
According to Saha, when it comes to data warehouse modernization, there are some common challenges for customers. First, it is the move to hybrid and multi-cloud environments. According to industry research, more than 80 percent of public cloud managed and professional services deals will require the provider to handle both hybrid cloud and multi-cloud capabilities by 2025. Data warehouse modernization is not just simply decommissioning your on-premises warehouse and going to the cloud. It’s not enough to do a simple “lift-and-shift.” Once you’ve migrated to a cloud data warehouse like BigQuery, you need cloud data integration and cloud data management for full digital transformation.
Another challenge is data governance. The cloud helps provide scalability and flexibility, but the expansion and growth of data also increases the need for compliance, policy support, and data cataloging to effectively manage the data appropriately.
Cloud models will start to include a governed data architecture, with accelerated adoption of analytics and AI throughout an organization. While previous adoption cycles were driven by software as a service or data center exits, this next phase will be driven by digital transformation.
Enhancements to Data Warehouse Modernization
To help support their digital transformation, Informatica recently announced a major expansion of Informatica Intelligent Cloud Services (IICS) on GCP that will help Google Cloud customers address many more use cases and data management patterns. Delivered on Informatica’s Intelligent Data Management Cloud platform, IICS provides industry-leading cloud-native, AI-powered data management. With IICS available via Google Cloud Marketplace, using IICS is now as seamless as using cloud-native GCP services.
Some of the new enhancements include the ability to:
1. Quickly Build and Deploy Data Integration Pipelines with Informatica Cloud Data Integration-Elastic (CDI-E) on Google Cloud: Customers can now process very large data engineering workloads elastically via Informatica’s Intelligent Data Management Cloud on GCP (available on the GCP marketplace), using Informatica's codeless, visual, data ingestion and transformation user experience.
2. Simplify Large-Scale Data Ingestion from On-Premises to Google Cloud with Informatica Cloud Mass Ingestion (CMI) Service: Informatica CMI gives customers a simple and intuitive wizard-based approach to efficiently ingest and replicate large amounts of data into Google Cloud from on-premises sources such as Oracle, SQL/MySQL, Teradata, Netezza, and DB2 and others. CMI supports Google Pub/Sub Model as both a source or destination while supporting schema drift and ingesting streaming and IoT data for real-time analytics.
3. Modernize Your Data, API, and Application Integration on Google Cloud with Informatica API Manager: As data flow and integrations continue to evolve, Informatica’s API Manager on GCP makes it easy to manage all phases of your API process. Throughout the development, management, or even deprecation of APIs, API Manager is designed to orchestrate complex hybrid and multi-cloud systems by automatically keeping track of changing capabilities and integrations with any external system.
Informatica is uniquely positioned to help Google Cloud customers with hybrid and multi-cloud scenarios as well as cloud-first and cloud-native scenarios on GCP. Informatica’s elastic data integration and mass ingestion services on GCP help customers address all data integration patterns and work seamlessly with Google native services such as Google BigQuery.
Learn more about Informatica and Google Cloud by checking out our session, “Get More From Your Analytics by Modernizing Your Data Warehouse” available on-demand at the Google Data Cloud Summit.
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