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Found 3 results

  1. A set of strategies and guiding principles to effectively scale your data platform while maximizing its business impact. Continue reading on Towards Data Science » View the full article
  2. Data management changes when migrating to the cloud, but there are strategies for technical leaders who want to direct more efficient DataOps. View the full article
  3. Google Cloud and Databricks share a common vision of open source, open data platforms, and an open cloud. With this shared philosophy, Google Cloud is delighted to announce our partnership with Databricks to bring their data analytics and machine learning solutions to Google Cloud. The partnership enables customers to accelerate Databricks implementations by simplifying their data access, by jointly giving them powerful ways to analyze their data, and by leveraging our combined AI and ML capabilities to impact business outcomes. Databricks is tightly integrated with Google Cloud’s infrastructure and analytics capabilities with the security, elasticity and reliability that customers need. By deploying on Google Cloud, Databricks users can build data lakes fast and integrate data science and ML workloads on their path towards production. Databricks’ capabilities in data engineering and analytics are complemented by Google Cloud’s global, secure network as well as the capabilities of BigQuery, Looker, AI Platform and our expertise in delivering applications in a containerized environment. All together, customers get an enterprise-ready cloud service with a Databricks experience that is reliable, scalable, secure and governed. How Google Cloud makes a difference for Databricks users Business benefits: Customers can reduce the overhead of deploying models built on Databricks using the managed services in Google Cloud AI Platform. The combined capabilities of Databricks and AI Platform offers customers a broad range of modeling techniques, like AutoML, to deploy machine learning quickly into their applications. Productivity gains: Customers can pair Databricks with Google Cloud services to make the most of their data management and analytics investments. Databricks users can bring new data pipelines, analytic applications, and machine learning models to market by blending their choice of service offerings across our two businesses. At a time when it’s critical to do more with less, customers can migrate Databricks to Google Cloud to take advantage of the benefits of the world's fastest growing cloud. Infrastructure savings: Customers are able to dynamically scale implementations to meet their needs. Our joint customers can have their Databricks, Google Cloud, and additional analytics applications work side by side on one shared infrastructure that’s optimized for analytics performance. This provides economies of scale from a pricing standpoint and helps lower the overall management of their enterprise analytics architecture. Google Cloud and Databricks are focused on integration and deployment in these areas: Deploying Databricks on Google Cloud: This solution provides a streamlined, reliable, and cost-effective way to deploy and work with Databricks - and for the first time, customers will have the ability to leverage a Google Kubernetes Engine-based Databricks runtime. With Google Cloud, customers are now able to choose the set up that is best for them, whether that is fully open source Apache Spark on Dataproc or Databricks’ performance-optimized version of Spark. Similar to using Dataproc with Google Cloud Storage (GCS), Databricks' Lakehouse architecture gives customers the ability to deploy a data lake using inexpensive GCS object storage. Integrating Databricks with Google Cloud services and applications: Databricks on Google Cloud offers a unique level of integration in the market. Together, we have worked to ensure seamless Databricks interoperability with Google Cloud Storage, BigQuery, Looker, and Pub/Sub. Customers will also benefit from integration with Google Cloud AI Platform through capabilities like serving models built on Databricks as endpoints using the Prediction service, and accessing Google’s state-of-the-art, pre-built AI models and AutoML for vision, language, tables, and conversation. Further integrations will ensure that Databricks on Google Cloud meets our joint customers' requirements for simple and efficient management, administration, and security. This includes unified billing, integration with Google Identify to enable SSO, and credential passthrough. A commitment to openness Google Cloud’s partnership with Databricks provides organizations with an open approach that enables greater flexibility into their data management and analytics strategy, and builds upon Google’s ongoing commitment to an open cloud. This open approach assures interoperability and portability for enterprises, including those that want to use multiple public clouds for their analytics applications. Data analytics partnerships Members of our joint ecosystem of partners have committed to ensure seamless integrations and expertise with Databricks on Google Cloud, including Accenture, Cognizant, Collibra, Confluent, Deloitte, Fishtown Analytics, Fivetran, Immuta, Informatica, Infoworks, Insight, MongoDB, Privacera, Qlik, SoftServe, Slalom, Tableau, TCS and Trifacta among others. Explore Databricks on Google Cloud We're looking forward to helping customers discover Databricks on Google Cloud and put all of these capabilities to work. Get started by exploring Databricks on Google Cloud or access it through the Google Cloud console. Related Article The democratization of data and insights: making real-time analytics ubiquitous We examine data access, data insights, and machine learning in the context of real-time data analysis, and how Google Cloud is working to... Read Article
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