Costing, Resourcing & Budget

Migration Investment
Plan with AI Leverage

Full cost model for the SSAS Multidimensional → Fabric migration across three scenarios: no AI assistance, 25% AI leverage, and 50% AI leverage. Use the interactive calculator below to model the impact.

Day rate: consultant-grade Region: APAC / Europe blended Currency: USD Timeline: 9 months AI tool: GitHub Copilot + Claude

AI Leverage Calculator

Drag the slider or click a scenario to see how AI assistance changes your total investment

No AI · 0% 50% · Max AI
Baseline (no AI)
$198,500
Total project cost
AI saving at 0%
$0
0 days recovered
Net investment
$198,500
+ AI tooling ~$3,600/yr
Rate Card

Resource Roles & Day Rates

Rates are blended APAC/Europe consultant-grade day rates in USD. Internal (FTE) rates are shown at a 40% discount to consultant market rate to reflect the lower direct cost where internal resource is available.

Lead BI / Data Engineer
$850
per day (consultant)
Internal FTE equiv: ~$510/day
SSAS / DAX Specialist
$950
per day (consultant)
Specialist rate — SSAS expertise commands premium
Azure / Fabric Architect
$1,050
per day (consultant)
Internal FTE equiv: ~$630/day
Business Analyst
$650
per day (consultant)
Internal FTE equiv: ~$390/day
QA / Test Engineer
$650
per day (consultant)
Reconciliation & UAT phase focus
Project Manager
$750
per day (part-time)
Governance, reporting, stakeholder mgmt
💡
Rate assumption All costs below use consultant-grade rates as the baseline. If internal FTE resources are used for any role, the equivalent phase cost reduces by approximately 40%. The AI leverage calculation applies on top of whichever rate basis you choose.
Cost Breakdown

Phase-by-Phase Resource Plan

Days estimated per role per phase. The "AI-adjusted days" column updates live based on your AI leverage setting above.

⚡ Immediate · Azure Arc Bridge
Role Task Base days Day rate AI-adj. days Cost
Azure / Fabric Architect Azure Arc registration, ESU activation, compliance documentationLow AI 2 $1,050 2.0 $2,100
Phase subtotal 2.0 days $2,100
Phase 1A–D · Assessment & Tabular Rebuild (Months 1–4)
Role Task Base days Day rate AI-adj. days Cost
SSAS / DAX Specialist MDX inventory, cube audit, artefact documentationMed AI 15$950 15.0 $14,250
Business Analyst Business owner interviews, KPI definitions, sign-off sessionsLow AI 10$650 10.0 $6,500
SSAS / DAX Specialist MDX → DAX translation, calculated measures rebuildHigh AI 20$950 20.0 $19,000
Lead BI Engineer Star schema design, dimension/fact table build, data modellingHigh AI 18$850 18.0 $15,300
Lead BI Engineer RLS role design, security implementation & testingMed AI 5$850 5.0 $4,250
QA / Test Engineer Parallel reconciliation, number validation, UAT coordinationMed AI 12$650 12.0 $7,800
Project Manager Governance, stakeholder reporting, risk managementLow AI 8$750 8.0 $6,000
Phase 1 subtotal 88.0 days $73,100
Phase 2 · Cloud Migration to Microsoft Fabric (Months 5–8)
RoleTask Base daysDay rate AI-adj. daysCost
Azure / Fabric Architect ADLS Gen2, Fabric workspace, Synapse provisioning & setupMed AI 10$1,050 10.0 $10,500
Lead BI Engineer ADF pipeline build — SSIS package replacementHigh AI 15$850 15.0 $12,750
Azure / Fabric Architect Fabric Semantic Model deployment, DirectLake configurationMed AI 8$1,050 8.0 $8,400
Lead BI Engineer Dataverse Synapse Link setup, data source re-pointingMed AI 6$850 6.0 $5,100
Lead BI Engineer Power BI report build on Fabric Semantic ModelHigh AI 12$850 12.0 $10,200
Lead BI Engineer SSRS → Fabric Paginated Reports migrationMed AI 8$850 8.0 $6,800
QA / Test Engineer Fabric vs on-prem parallel validation, cloud UATMed AI 10$650 10.0 $6,500
Project Manager Cutover planning, change management, decommission sign-offLow AI 6$750 6.0 $4,500
Phase 2 subtotal 75.0 days $64,750
Phase 3 · Cutover, Handover & Documentation (Month 9)
RoleTask Base daysDay rate AI-adj. daysCost
Lead BI Engineer Final documentation, Git archiving, knowledge transferHigh AI 8$850 8.0 $6,800
SSAS / DAX Specialist Final model review, handover sessions with internal teamLow AI 4$950 4.0 $3,800
Business Analyst User training, Power BI adoption sessions, report sign-offLow AI 6$650 6.0 $3,900
Project Manager Project closure, lessons learned, decommission recordsMed AI 3$750 3.0 $2,250
Phase 3 subtotal 21.0 days $16,750
Infrastructure & Tooling (fixed costs — not AI-reducible)
ItemDetailUnit costQty / periodTotal
Microsoft Fabric capacity F4 SKU — analytics + Power BI Premium $730/mo9 months $6,570
Azure Data Lake Storage Gen2 ~5TB estimated, LRS redundancy $110/mo9 months $990
Azure Data Factory Pipeline runs, data integration unit hours $180/mo9 months $1,620
SQL Server 2022 Dev licence Phase 1 tabular model dev/UAT server $0Developer Ed. $0
GitHub Copilot Business AI coding assistant — 3 engineers × 9 months $19/mo/user3 × 9 mo $513
Claude / AI assistant Documentation, DAX generation, test case writing $20/mo3 × 9 mo $540
Tabular Editor licence Professional SSAS/Fabric modelling tool $600/yr2 licences $1,200
Contingency (10%) Scope risk buffer on labour costs —— $13,670
Infrastructure & tooling subtotal $25,103
AI Leverage Detail

Where AI Saves the Most Time

Not all tasks benefit equally from AI assistance. This table shows which activities in this migration are highest-yield for AI tools — and why.

AI-leverageable tasks — impact by activity
Task AI tool Max time saving Impact level How AI helps
MDX → DAX translation Claude / Copilot 50–60%
Very High
AI can convert MDX syntax to DAX equivalents, explain filter context differences, and suggest DAX patterns. Requires human review of business logic assumptions.
DAX measure writing GitHub Copilot 40–55%
Very High
Copilot autocompletes time intelligence patterns (SAMEPERIODLASTYEAR, DATESBETWEEN, CALCULATE). Reduces boilerplate time substantially.
ADF pipeline build Copilot + Azure AI 40–50%
High
AI generates ARM templates, pipeline JSON, and linked service configurations. Azure's native AI features suggest connector settings from source schemas.
Documentation writing Claude 50–70%
Very High
Given a DAX measure or SSIS package, AI can draft the plain-English business definition, assumptions, and operational notes. Reduces one of the most time-consuming manual tasks.
Star schema design Claude 30–40%
Medium
AI can suggest dimension/fact table structures from source schema descriptions. Business domain knowledge still required — AI produces a first draft, not a final design.
Test case generation Claude / Copilot 40–50%
High
AI generates reconciliation test scripts, SQL validation queries, and UAT test cases from measure definitions. Significant saving on QA effort.
SSRS → Paginated Reports Migration tooling 20–30%
Medium
RDL format is the same — migration is already low-effort. AI can assist with data source re-pointing scripts but the gain is smaller here.
Business owner interviews N/A 0–5%
Minimal
Human relationship and domain knowledge — AI cannot replace this. AI can help prepare interview guides and summarise notes afterwards.
RLS security testing N/A 0–10%
Minimal
Security testing requires human validation with real credentials and real data. Cannot be delegated to AI — governance risk is too high.
⚠
Important caveat on AI leverage AI reduces time on individual tasks — it does not eliminate the need for expert review. Every AI-generated DAX measure, pipeline config, or documentation output must be validated by a qualified engineer before production use. The saving is in first-draft speed and boilerplate elimination, not in replacing expertise. Budget for review time: assume 20–30% of AI-generated output requires meaningful correction.
Scenario Comparison

Three Investment Scenarios

Total project cost across the three AI leverage scenarios, including labour, infrastructure, tooling, and contingency.

Scenario A · No AI
$198,500
 
Est. timeline: 9 months
Labour (186 days)$156,827
Infrastructure & tooling$11,433
Contingency (10%)$15,683
AI tools cost$0
Recommended
Scenario B · 25% AI
$155,200
Save ~$43,300 vs no AI
Est. timeline: 7–8 months
Labour (~140 days)$117,350
Infrastructure & tooling$11,433
Contingency (10%)$11,735
AI tools cost$1,053
Scenario C · 50% AI
$117,900
Save ~$80,600 vs no AI
Est. timeline: 6–7 months
Labour (~93 days)$78,233
Infrastructure & tooling$11,433
Contingency (10%)$7,823
AI tools cost$1,053
✓
Recommendation: Scenario B — 25% AI leverage The 25% scenario is the most defensible position. It is achievable with widely available tools (GitHub Copilot + Claude), realistic given the need for expert review of all AI outputs, and delivers a ~22% cost reduction versus baseline. The 50% scenario is achievable but requires a team experienced in AI-assisted development workflows and carries higher review overhead — better suited to organisations already embedded in AI tooling.
Budget Summary

Budget Allocation

Cost distribution by phase and category — updates with your AI leverage setting above.

$155k
0% AI
Phase 1 — Assess & Rebuild 49%
Phase 2 — Cloud Migration 30%
Phase 3 — Cutover & Handover 10%
Infrastructure, Tooling & Contingency 11%
ℹ
Ongoing cost post-migration (annual) Microsoft Fabric capacity (F4): ~$8,760/yr · ADLS Gen2 storage: ~$1,320/yr · Azure Data Factory: ~$600/yr · Power BI Pro licences (if needed beyond Fabric): $120/user/yr · AI tools (Copilot + Claude): ~$1,200/yr for 3 users. Estimated total ongoing cloud cost: ~$12,000–15,000/yr vs on-prem server maintenance and licencing costs. Payback on migration investment typically achieved within 2–3 years.
Delivery Schedule

Resource Schedule by Month

High-level Gantt showing when each role and phase is active across the 9-month project.

M1
M2
M3
M4
M5
M6
M7
M8
M9
Azure Arc bridge
Arc
Assessment & audit
Assess
Tabular model build
MDX → DAX Rebuild
Parallel validation
Validate
Cloud infra setup
Infra
Fabric deploy + Power BI
Fabric + Power BI
Cloud parallel run
Parallel
Cutover & handover
Go-live
📋
Resourcing note This plan assumes a core team of 3 people (Lead BI Engineer, SSAS/DAX Specialist, Azure Architect) with part-time BA, QA, and PM support. If resourcing to a single senior engineer, extend the timeline to 12–14 months. If this is an internal FTE project with consultant specialist support only for MDX→DAX translation and Azure architecture, total cost reduces by approximately 40% on labour — bring the Scenario B cost to approximately $93,000–$100,000.