Explore data lake and data pipelining services in action
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Data ingestion and preparation with Snowflake on Azure
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Building serverless ETL pipelines on AWS
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Self-service ingestion: The key to creating a unified, scalable, cloud data lake


Cloud-native, on-premises, and hybrid architectures

Automated and scalable frameworks

Support for batch and real-time use cases

Operationalized a highly available Azure-based data platform to migrate a legacy system
Learn MoreReal-time business activity monitoring using an all-in-one data pipeline platform
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Data ingestion and preparation with Snowflake on Azure
Building serverless ETL pipelines on AWS
Self-service ingestion: The key to creating a unified, scalable, cloud data lake
Address your desired use case across critical analytic dimensions
Collaborate with experts on strategic objectives
Identify and select core technologies
Ensure IP governance and protection
Align business outcomes with goals
Explore architecture options with experts
Ensure alignment of business and technology
Architect an ideal solution for a pressing problem
Validate or refactor existing architecture
Develop a prototype with expert guidance
Establish a roadmap to production
