Sold by: Amazon Web Services
Building a modern data architecture takes months before a single use case reaches production. Scalable Data & AI Foundation on AWS fast-tracks implementation using the ProServe Accelerator, an AWS-engineered framework that automates deployment of data lakes, lakehouses, and AI-ready environments. Pre-packaged configurations let you choose the right starting point for your use case, with built-in security controls, infrastructure-as-code, and CI/CD pipelines to move from design to production faster. ProServe consultants handle requirements analysis, solution design, and deployment so your team can operate and scale independently.
Overview
Every organization needs a data foundation. The challenge is building one that is secure, compliant, scalable, and production-ready without spending months on infrastructure before anyone can run a query or train a model.
Scalable Data & AI Foundation on AWS accelerates the implementation of a modern data architecture using the ProServe Accelerator, an AWS-engineered solution framework with infrastructure-as-code, CI/CD pipelines, and pre-validated security controls for deploying a production-ready data platform.
The engagement uses outcome-based, pre-packaged configurations matched to your use case and complexity, with implementation times as short as 4 to 6 weeks. Options range from a foundational data lake to a governed lakehouse to an AI-ready data science environment, with custom configurations available for scenarios requiring a combination of capabilities.
What gets deployed:
Secure, multi-account data lake architecture on Amazon S3 with encryption, versioning, and lifecycle policies. Automated data discovery and cataloging with AWS Glue. Configurable data quality checks for ongoing validation. Orchestration for data processing across your data lifecycle. Integrated analytics tools including Amazon Athena and Amazon QuickSight for immediate consumption capability.
How the engagement works:
ProServe consultants with deep AWS expertise begin with requirements analysis, reviewing your current architecture, target state, and priority use cases. This is followed by solution design, architecture signoff, and deployment. The engagement concludes with validation and knowledge transfer so your team can operate, extend, and scale the platform independently.
Upon completion, your organization has a standardized, well-architected data and AI foundation ready for analytics, business intelligence, AI/ML, generative AI, and data science workloads. Your team also retains the ProServe Accelerator, which you can continue to use to scale and extend your data environment as new use cases emerge.
To learn more or request a private offer, contact our team.
Highlights
- Fast-track your modern data architecture with the ProServe Accelerator, an AWS-engineered solution framework with infrastructure-as-code, CI/CD pipelines, and pre-validated security controls. Outcome-based, pre-packaged configurations let you choose the right starting point for your use case, with implementation times as short as 4 to 6 weeks.
- Security and compliance controls are embedded directly into the infrastructure-as-code, eliminating manual configuration and reducing the risk of human error. Automated control validation and standardized security implementations streamline assessment and accreditation, helping your data platform move from design to production faster.
- ProServe consultants with deep AWS expertise handle requirements analysis, solution design, and deployment. Knowledge transfer positions your team to operate, extend, and scale independently. You retain the ProServe Accelerator to continue scaling your data environment as new use cases emerge.
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