Exam objectives — ASTRA Tech Sales Advisor
D1. Solution architecture, integration and operating boundaries — 14.3%
D1.1 Given a scenario, frame a scoped technical-commercial pilot from the required outcome and unknown interface capabilities.
Example concepts: pilot scope, required outcome, undocumented capability, exclusion.
D1.2 Given a scenario, trace the producer, consumer, integrator and business approver through a proposed flow.
Example concepts: producer, consumer, integrator, business approver.
D1.3 Given a scenario, choose an integration pattern that meets timing, replay and duplicate constraints.
Example concepts: webhook, batch, idempotency key, replay window.
D1.4 Given a scenario, interpret reliability test measures without hiding retries or failed records.
Example concepts: first-attempt success, retries, dead-letter queue, percentile.
D1.5 Given a scenario, resolve identifier, status, timestamp and version semantics in a two-party data contract.
Example concepts: identifier ownership, status mapping, version, time zone.
D1.6 Given a scenario, trace technical and approval boundaries across a candidate workflow.
Example concepts: workflow boundary, permitted action, approval point.
D2. Cloud and solution economics — 12.5%
D2.1 Given a scenario, identify the cost meter, period, usage owner and forecast exposure behind a quote.
Example concepts: meter, billing period, usage owner, forecast exposure.
D2.2 Given a scenario, interpret entitlements, rights and commitment terms under changing demand.
Example concepts: entitlement, commitment term, shortfall, overage.
D2.3 Given a scenario, reconcile a usage record to a defined billing line and find a mismatch.
Example concepts: usage record, invoice line, included allowance, mismatch.
D2.4 Given a scenario, calculate stepped or tiered charges and the cost of unused commitment.
Example concepts: tiered rate, stepped charge, unused commitment.
D2.5 Given a scenario, compare scenarios without treating demand assumptions as confirmed savings.
Example concepts: demand assumption, scenario, modelled saving.
D2.6 Given a scenario, calculate commercial economics without merging subscription and partner-service revenue.
Example concepts: subscription revenue, partner services, margin.
D2.7 Given a scenario, calculate released operational capacity while separating model from realised return.
Example concepts: released hours, modelled capacity, realised saving.
D2.8 Given a scenario, calculate the full effort model and bound the resulting commercial claim.
Example concepts: effort model, scope boundary, bounded claim.
D3. Security, assurance and operational trust — 12.5%
D3.1 Given a scenario, identify supported least-privilege and diagnostic controls, and what remains unproven.
Example concepts: least privilege, diagnostic access, unproven control.
D3.2 Given a scenario, translate a scoped security questionnaire into claim-specific evidence requests.
Example concepts: claim, evidence request, scope of question.
D3.3 Given a scenario, assign control operation, disclosure and customer-exception decisions to their authorised owners.
Example concepts: control operation, disclosure, customer exception.
D3.4 Given a scenario, interpret an assurance report within its period, tested services and exceptions.
Example concepts: period examined, tested services, exceptions.
D3.5 Given a scenario, sequence remediation, retest, customer acceptance and approved messaging.
Example concepts: remediation, retest, acceptance, approved messaging.
D3.6 Given a scenario, calculate incident reporting time using the specified clock trigger and authorisation.
Example concepts: clock trigger, confirmation, authorisation, deadline.
D3.7 Given a scenario, respond to an assurance objection without extending supplier evidence to a customer tenant.
Example concepts: supplier evidence, customer tenant, boundary of claim.
D3.8 Given a scenario, reconcile supplier assurance with tenant controls and executed customer terms.
Example concepts: supplier assurance, tenant control, executed terms.
D4. AI value, quality and safe-use decisions — 14.3%
D4.1 Given a scenario, frame an AI-supported workflow by decision consequence, source and permitted action.
Example concepts: decision consequence, source, permitted action.
D4.2 Given a scenario, evaluate a measured model result for the intended population and operating threshold.
Example concepts: intended population, operating threshold, agreement rate.
D4.3 Given a scenario, define allowed data, processing purpose, retention and deletion evidence.
Example concepts: allowed data, purpose, retention, deletion evidence.
D4.4 Given a scenario, interpret intervention metrics and choose the owner-led response to drift.
Example concepts: intervention rate, baseline, drift trigger, owner.
D4.5 Given a scenario, distinguish model intent, tool execution and reviewer authority in an AI control event.
Example concepts: model intent, tool execution, reviewer authority.
D5. Technical-commercial translation and defensible recommendations — 12.5%
D5.1 Given a scenario, deliver a bounded architecture recommendation with explicit exit criteria.
Example concepts: bounded recommendation, exit criteria, scope.
D5.2 Given a scenario, compare options under complete first-year costs and nonfinancial gates.
Example concepts: first-year cost, nonfinancial gate, comparison.
D5.3 Given a scenario, give a conditional purchasing decision with named triggers and accountable owners.
Example concepts: conditional decision, trigger, accountable owner.
D5.4 Given a scenario, assemble a conditional offer from cost, capability and customer acceptance evidence.
Example concepts: cost evidence, capability evidence, customer acceptance.
D5.5 Given a scenario, deliver a governed customer/partner handover with review and exit conditions.
Example concepts: handover, review point, exit condition.
D5.6 Given a scenario, sequence reversible pilot gates and the earliest evidence-backed next action.
Example concepts: reversible gate, earliest evidence, next action.
D5.7 Given a scenario, deliver an integrated recommendation distinguishing observed, modeled and unknown outcomes.
Example concepts: observed, modelled, unknown outcome.
D6. Discovery, stakeholders and decision sequencing — 12.5%
D6.1 Given a scenario, calculate and order dependent testing, security and acceptance activities.
Example concepts: dependency, testing, security review, acceptance.
D6.2 Given a scenario, prepare a conditional deployment handover with monitoring and reversal gates.
Example concepts: deployment handover, monitoring, reversal gate.
D6.3 Given a scenario, calculate eligible weighted pipeline without counting booked or unqualified opportunities.
Example concepts: eligible opportunity, stage weight, booked revenue.
D6.4 Given a scenario, frame a customer decision with technical, financial and governance constraints.
Example concepts: technical constraint, financial constraint, governance constraint.
D6.5 Given a scenario, target discovery questions to the owner and the gate each answer changes.
Example concepts: discovery question, owner, gate affected.
D6.6 Given a scenario, calculate the dependency path for reversible expansion and acceptance.
Example concepts: dependency path, reversible expansion, acceptance.
D6.7 Given a scenario, frame a multi-party, multi-domain decision into a bounded customer recommendation.
Example concepts: multi-party decision, bounded recommendation.
D7. Partner, channel and contracting boundaries — 10.7%
D7.1 Given a scenario, define a partner motion while preserving the customer and supplier boundaries.
Example concepts: partner motion, customer boundary, supplier boundary.
D7.2 Given a scenario, apply deal-registration and conflict evidence before allocating attribution.
Example concepts: deal registration, conflict evidence, attribution.
D7.3 Given a scenario, distinguish sourced, influenced and disputed co-sell evidence.
Example concepts: sourced, influenced, disputed.
D7.4 Given a scenario, apply capability and performance evidence to reversible enhanced-term gates.
Example concepts: capability evidence, performance evidence, reversible term.
D7.5 Given a scenario, protect customer continuity, renewal ownership and exit responsibilities.
Example concepts: customer continuity, renewal ownership, exit duty.
D7.6 Given a scenario, prepare a governed channel handover with economics, owners, gaps and expiry.
Example concepts: channel handover, economics, gap, expiry.
D7.7 Given a scenario, resolve vendor, partner and customer authority in a proposed transaction.
Example concepts: vendor authority, partner authority, customer choice.
D8. Evidence governance, approvals and responsible claims — 10.7%
D8.1 Given a scenario, link budget, admission and approval controls to cost and service continuity.
Example concepts: budget alert, spend limit, approval, continuity.
D8.2 Given a scenario, evaluate retention and subprocessor evidence across the actual data lifecycle.
Example concepts: retention period, subprocessor, data lifecycle.
D8.3 Given a scenario, distinguish AI assurance evidence from claims it does not establish.
Example concepts: AI assurance evidence, unestablished claim.
D8.4 Given a scenario, assemble a conditional response across evidence, missing controls and owner actions.
Example concepts: evidence status, missing control, owner action.
D8.5 Given a scenario, assign business, data, model and execution approval decisions to the correct owners.
Example concepts: business approval, data approval, model approval, execution approval.
D8.6 Given a scenario, sequence the review, version binding and release checks for a consequential action.
Example concepts: review, version binding, release check.
D8.7 Given a scenario, decide which provider or model changes require retest before deployment.
Example concepts: provider change, model change, retest requirement.
D8.8 Given a scenario, classify observed, modeled and unestablished outcomes within one commercial claim.
Example concepts: observed result, modelled result, unestablished claim.