Data Observability for Snowflake Register

DataOps

Rebuilding Reliable Modern Data Pipelines Using AI and DataOps

Organizations today are building strategic applications using a wealth of internal and external data. Unfortunately, data-driven applications that combine customer data from multiple business channels can fail for many reasons. Identifying the cause and finding a […]

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Organizations today are building strategic applications using a wealth of internal and external data. Unfortunately, data-driven applications that combine customer data from multiple business channels can fail for many reasons. Identifying the cause and finding a fix is both challenging and time-consuming. With this practical ebook, DevOps personnel and enterprise architects will learn the processes and tools required to build and manage modern data pipelines.

Ted Malaska, Director of Enterprise Architecture at Capital One, examines the rise of modern data applications and guides you through a complete data operations framework. You’ll learn the importance of testing and monitoring when planning, building, automating, and managing robust data pipelines in the cloud, on premises, or in a hybrid configuration.

Plan, migrate, and operate modern data stack workloads and data pipelines using cloud-based and hybrid deployment models

  • Learn how performance management software can reduce the risk of running modern data applications
  • Take a deep dive into the components that comprise a typical data processing job
  • Use AI to provide insights, recommendations, and automation when operationalizing modern data systems and data applications
  • Plan, migrate, and operate modern data stack workloads and data pipelines using cloud-based and hybrid deployment models