Skip to main content
Image coming soon

Enterprise Data Architecture for the BTP Platform

$199.00
Adding to cart… The item has been added

A focused course, tailored for you

Enterprise Data Architecture for the BTP Platform

A reference architecture for ERP platform advisors guiding customers through BTP-anchored enterprise data architecture: Datasphere, Analytics Cloud, AI Foundation, customer-side integration with S/4HANA and the broader data estate.

ERP platform advisors face customer Chief Data Officers asking how BTP holds across Datasphere, Analytics Cloud, AI Foundation, and the customer's broader data estate. The course delivers the integrated reference architecture.

$199 one-time
Tailored to your situation. Access within 24 hours. 30-day money-back.

Includes a hand-built implementation playbook delivered alongside course access, generated for your specific situation.

Why this course

ERP platform advisors and data architects on the BTP team face 2026 customer conversations where Datasphere adoption, Analytics Cloud positioning, AI Foundation landing, and customer-side integration with the customer's broader data estate (Snowflake, Databricks, Microsoft Fabric, Google BigQuery, AWS Redshift) all need to land in the same conversation. The customer Chief Data Officer arrives with three questions. Will Datasphere hold across the customer's existing data-mesh investment. Will Analytics Cloud integrate with the customer's existing BI commitments. Will AI Foundation provide the customer-facing answer to the customer's AI governance committee. The default BTP positioning conversation pitches the integrated suite. The customer CDO already heard that.

The course works through the integrated reference architecture. The Datasphere adoption framework. The Analytics Cloud positioning. The AI Foundation landing pattern. The customer-side broader data estate integration. The customer-side identity-federation pattern. The customer-side observability stack integration. The customer-side FinOps integration. The customer-side governance integration. The customer engagement structure. Twelve modules with deliverables. Plus a hand-built playbook for your account mix.

What you walk away with

  • A documented Datasphere adoption framework.
  • An Analytics Cloud positioning framework.
  • An AI Foundation landing pattern.
  • A customer-side broader data estate integration framework.
  • A customer-side identity-federation pattern.
  • A customer-side observability stack integration.
  • A customer-side FinOps integration.
  • A customer-side governance integration.
  • A 10-week build plan.

The 12 modules

Module 1. The 2026 BTP enterprise customer landscape
Walkthrough of the 2026 BTP enterprise customer landscape. The Datasphere product position. The Analytics Cloud product position. The AI Foundation product position. The competitive landscape against Snowflake, Databricks, Microsoft Fabric, Google BigLake, AWS Redshift Spectrum, Oracle Analytics Cloud, IBM Data and AI. The strategic decisions a customer Chief Data Officer faces.
Module 2. Datasphere adoption framework
Build the Datasphere adoption framework. The customer-side data-domain modelling pattern. The customer-side data-product definition framework. The customer-side data-mesh integration. The customer-side data-ownership framework. The customer-side data-contracts pattern. The integration with the customer's existing data-catalog. Plus the worked example for the customer's first three data-domain Datasphere landings.
Module 3. Analytics Cloud positioning framework
Build the Analytics Cloud positioning framework. The customer-side existing BI integration. The Tableau adjacency. The Power BI adjacency. The Looker adjacency. The customer-side planning integration. The customer-side reporting integration. The customer-side semantic-layer integration. Plus the worked example for the customer's typical BI footprint and the Analytics Cloud landing pattern.
Module 4. AI Foundation landing pattern
Build the AI Foundation landing pattern. The customer-side first regulated AI workload selection. The customer-side data-residency posture. The customer-side AI governance integration. The customer-side audit-trail integration. The customer-side EU AI Act and NIST AI RMF integration. The integration with the customer's existing model risk management framework. Plus the worked example for the customer's first three AI Foundation use cases.
Module 5. Customer-side broader data estate integration
Build the customer-side broader data estate integration. The Snowflake integration pattern. The Databricks integration pattern. The Microsoft Fabric integration pattern. The Google BigQuery integration pattern. The AWS Redshift integration pattern. The customer-side data-lake integration. Plus the worked example for the customer's typical heterogeneous data-platform footprint.
Module 6. S/4HANA integration pattern
Build the S/4HANA integration pattern. The customer-side embedded analytics integration. The customer-side data-extraction pattern. The customer-side data-replication pattern. The customer-side master-data-integration pattern. The customer-side transactional-data-integration pattern. The integration with the customer's existing S/4HANA cadence. Plus the worked example for the customer's typical S/4HANA-anchored data flow.
Module 7. Customer-side identity-federation pattern
Build the customer-side identity-federation pattern. The customer-side IAS integration. The customer-side IPS integration. The customer's existing identity-provider integration (Microsoft Entra ID, Okta, Ping Identity). The SCIM provisioning pattern. The role-based-access pattern. The session-policy pattern. The customer-side audit-trail integration. Plus the worked example for the customer's typical user population.
Module 8. Customer-side observability stack integration
Build the customer-side observability stack integration. The Cloud ALM integration. The Solution Manager integration. The customer-side Datadog integration. The Splunk integration. The Microsoft Sentinel integration. The metric-and-log routing framework. The alerting framework. The integration with the customer's existing SRE operating model. Plus the worked example for the customer's typical observability stack pattern.
Module 9. Customer-side FinOps integration
Build the customer-side FinOps integration. The BTP consumption model. The customer-side cost-attribution framework. The customer-side cost-management framework. The customer-side cost-optimisation framework. The integration with the customer's existing FinOps cadence. The integration with the customer's existing financial-management cycle. Plus the worked example for a customer's first-year cost model and the customer-side cost-optimisation pattern over 18 months.
Module 10. Customer-side governance integration
Build the customer-side governance integration. The customer-side data-classification integration. The customer-side data-quality framework integration. The customer-side data-lineage framework integration. The customer-side privacy-programme integration. The customer-side audit-trail integration. The customer-side AI-governance integration. The customer-side EU CSRD reporting integration where applicable. Plus the worked example for a regulated customer.
Module 11. Customer engagement structure
Build the customer engagement structure. The discovery phase. The reference-architecture phase. The pilot-workload phase. The full-rollout phase. The sustainment phase. The renewal conversation. The customer-side programme-governance committee integration. The integration with the customer's existing BTP account-team cadence. Plus the worked example for a 12-month customer engagement and the pricing framework.
Module 12. Your 10-week build plan
Week by week. Weeks 1-2: landscape and Datasphere adoption framework. Weeks 3-4: Analytics Cloud positioning and AI Foundation landing pattern. Weeks 5-6: customer-side broader data estate integration and S/4HANA integration. Weeks 7-8: identity-federation, observability stack, FinOps. Weeks 9-10: governance integration, customer engagement structure. Deliverable: an integrated BTP-anchored reference architecture ready for the next CDO conversation.

How this addresses your situation

Specific modules that map to what you said you are dealing with.

CDO asks about Datasphere → Module 2.
CDO asks about Analytics Cloud → Module 3.
CDO asks about AI Foundation → Module 4.
Customer has multi-vendor data platform → Module 5.
S/4HANA integration → Module 6.
Identity federation → Module 7.
Observability → Module 8.
FinOps → Module 9.
Governance → Module 10.

What you get with this course

  • The 12-module course delivered as text plus downloadable templates.
  • Templates and worked examples for every module.
  • A hand-built playbook generated for your account mix.
  • Three reference architectures from peer BTP engagements.
  • Scripted talking points for the customer CDO engagement.

What you will have in hand by Day 1, Week 1, Month 1

Day 1: Datasphere adoption framework scaffold drafted.

Week 4: Analytics Cloud positioning and AI Foundation landing pattern designed.

Week 8: Customer-side broader data estate, S/4HANA integration, IAM, observability, FinOps operational.

Week 10: Reference architecture ready for next CDO conversation.

Before and after

Before

Default BTP positioning pitches the integrated suite. Customer CDO already heard that. Conversation stalls.

After

Integrated reference architecture. Datasphere, Analytics Cloud, AI Foundation land in the same conversation. CDO signs the multi-year programme.

What happens if you do not address this

Customer CDOs increasingly evaluate BTP against the integrated alternatives. BTP advisors who do not arrive with the integrated reference architecture lose to integrated competitor pitches.

Who it is for

For ERP platform advisors and data architects at the BTP team, senior solution architects supporting BTP-anchored customer accounts, principal architects at BTP partners, and senior consultants delivering BTP programmes.

Who this is NOT for. Pure non-BTP practitioners. Practitioners with no enterprise data-architecture experience. Pure non-data-platform roles.

How it arrives

Text-based course via LMS, plus downloadable templates and worked examples and the hand-built playbook.

Time investment. Roughly 18 hours of reading and 60 to 120 hours of build effort across the 10-week plan.

Why $199 is the right number

External BTP enterprise-architecture programmes charge from 100,000 to 500,000 USD for reference-architecture builds. 199 USD buys the focused playbook and the implementation document for your account mix.

FAQ

Does this cover Joule integration?
Module 4 covers Joule in the AI Foundation landing pattern.
What about Build Code and Build Process Automation?
Module 2 covers Build Code adjacency.
Does this cover Integration Suite specifically?
Module 6 covers Integration Suite in the customer-side broader data estate integration.
What is in the implementation playbook for me specifically?
Reference architecture tuned to your account mix, governance integration matched to the customer's existing GRC posture, customer engagement structure pre-loaded with your sales cycle.

30-day money-back guarantee. If after a week of working through the materials this is not what you needed, reply to the receipt email and a full refund is processed. No questions, no forms.

Within 24 hours your account in the learning environment is provisioned and the tailored implementation playbook is delivered alongside it.

!