SAP data on AWS, governed and ready to use
Bristlecone moves SAP and operational data onto AWS, builds governed data lakes on S3, Glue, and Athena, and runs the platform with cloud operations and FinOps.
The hard part is keeping it secure, affordable, and useful to the people who plan, buy, and ship. That's where we focus.
Moving SAP data to AWS is the easy half
Keeping it secure, affordable, and useful for planning is where programs slip: storage costs climb, pipelines multiply, and nobody owns the bill.
We design AWS data platforms with operations in mind from day one: encryption, account separation, and disaster recovery, a FinOps model that assigns spend, and a warehouse layer, whether that's Redshift, Snowflake, or Databricks, chosen for the workload.
Already running on AWS? Get more from it
Many of our AWS engagements start with an environment that's already live but costing more than it should, or data that isn't reaching the business. We rightsize, tighten security and recovery, bring FinOps discipline to spend, and put the data lake to work on real supply chain decisions.
Standing you can check
- Leader in the IDC MarketScape: Worldwide Supply Chain, SAP & All Other Ecosystem Services, 2025-2026.
- Enterprise cloud operations for life sciences and other regulated businesses.
- Supply chain focus since 1998, with 1,000+ customer engagements.
- Part of the Mahindra Group.
What we do on AWS
Assess and plan
An AWS landscape and cost baseline before you commit, including landscape design and strategy, migration planning across rehost, re-platform, refactor, retain, retire, and repurchase options, and an enterprise data assessment.
Migrate SAP and data to AWS
Move SAP S/4HANA data and pipelines into an S3 data lake, and load tables in parallel with AWS Glue.
Build the data lake and warehouse
A governed S3 data lake with online and near-line storage tiers, Glue jobs, Lambda ingestion, and Athena query, with Redshift for reporting, or Snowflake or Databricks where they fit better.
Secure and govern
Security and recovery designed in, not bolted on: encryption at rest and in transit, VPC design, centralized logging, separate accounts for development, QA, and production, cross-account sharing, and disaster recovery with defined recovery objectives.
Analytics and BI
Fast answers on granular data, with QuickSight and Power BI on Redshift, and Qlik and Spotfire on an AWS-hosted lake.
Operate and optimize
Keep the platform up and the bill down, with L1, L2, and L3 cloud managed services, AWS FinOps covering rightsizing, Reserved Instances and Savings Plans, S3 lifecycle, and budgets, and 24x7 DataOps for SLA-bound data services.
SAP to a governed AWS data lake, run under FinOps
This is our most repeated AWS pattern: take SAP data off an overloaded on-premises system, land it in a secure S3 lake, and put a warehouse and BI on top, with operations and cost ownership defined before go-live. SAP S/4HANA data and pipelines move off the on-premises system into an encrypted S3 lake with online and near-line tiers. Glue jobs and Lambda handle processing and parallel refreshes. Athena, Redshift, or Snowflake serve the data, chosen per workload. And disaster recovery, account separation, logging, FinOps, and managed services keep it all running.
Accelerators built from delivery
- AWS FinOps toolkit: rightsizing, commitment planning, S3 lifecycle, and budget alerts, working alongside third-party cost tools.
- Edge Data Readiness Accelerator: metadata-driven, cloud-agnostic ingestion and transformation.
- Assessment frameworks: enterprise data assessment and data quality frameworks.
What an AWS data platform lets you do next
- Plan: product launch and demand analytics on granular sales data.
- Source: spend analytics on SAP data.
- Make: predictive maintenance and remaining-useful-life models.
- Deliver: retailer POS data ingestion and fleet telematics analytics.
- Service: warranty and complaint trending on historical SAP data.
Secure by design. Predictable to run.
Encryption at rest and in transit, VPC design, centralized logging, separate accounts per environment, and cross-account sharing are standard in our AWS builds.
Our AWS FinOps practice covers rightsizing, Reserved Instances and Savings Plans, S3 lifecycle policies, and budgets, so spend has an owner from the start.
From governed data to AI
We extend a governed lake to AI in four steps:
- Ground: SAP and operational data in a governed S3 lake with a catalog.
- Govern: business definitions and access rules applied before any model sees the data.
- Activate: models on SageMaker and generative features on Amazon Bedrock, released only after evaluation.
- Decide: answers in BI and the tools planners and buyers already use.
What leaders ask about SAP data on AWS, governed and ready to use
Practical answers to the questions that often shape the first conversation.
Do you build on Redshift, or on Snowflake and Databricks?+
All three. We choose the warehouse per workload on top of an S3 data lake.
Can you move SAP data to AWS?+
Yes. We've moved S/4HANA data and pipelines into an encrypted S3 data lake.
Can you run the AWS platform after go-live?+
Yes. We provide L1 to L3 managed services with SLAs, disaster recovery, and FinOps.
How do you control AWS costs?+
Through rightsizing, Reserved Instances and Savings Plans, S3 lifecycle policies, and budgets, with clear ownership of spend from day one.
How do we start?+
With a four-week assessment of your data estate and AWS cost baseline.