Power BI · Microsoft Fabric · Synapse · BC + LS data models · BI4Dynamics · semantic models · role-based dashboards — Microsoft Solutions Partner · Data & AI across UAE, KSA, India and USA.
Every industry below has a proven data model in Dynamics 365. Pick the one closest to yours and we will show you what the Power BI semantic layer looks like for that vertical.
Every organisation that has ever bought Power BI and been disappointed shares one root cause: the data was wrong before the first report was built. Silos between finance, operations and sales. No agreed definition of "revenue" or "margin." No single source of truth. Five teams, five spreadsheets, five different numbers for the same KPI. Power BI surfaces that fragmentation with perfect fidelity. The dashboard is accurate — it is accurately reflecting a broken data layer. That is the actual problem, and it is a data-architecture problem, not a visualisation problem. See how it connects to the wider Business Applications practice and the Analytics & AI practice at Novasoft.
What Novasoft does differently starts one layer below the dashboard. Microsoft Fabric Lakehouse as the single source of truth. OneLake ingesting every source system — Business Central, Finance & Operations, LS Central, D365 Sales — into one governed data estate. Semantic models on top of that Lakehouse with the business rules, KPI definitions and relationships baked in once. Power BI on top of the semantic model, reading from Direct Lake so there is no import-mode lag, no stale data, no overnight refresh to wait for. The CFO dashboard and the FP&A model read from the same row. They cannot disagree because they share a root.
If you are already on Dynamics 365 Business Central or Finance & Operations, you are 70% of the way there. The data is already clean, already structured, already validated through your daily operations. It just needs Fabric ingestion and a semantic model to become a dashboard your leadership team will actually use on Monday morning instead of emailing IT for a spreadsheet.
No dashboards on day one. First, the data audit. The semantic model second. The dashboard third. That sequencing is what makes the dashboard trustworthy rather than merely good-looking.
Data audit, source-system mapping (BC / F&O / D365 Sales / LS Central), KPI workshop with business stakeholders. Which five numbers does the CFO need every Monday? Where do they currently come from? What are the discrepancies?
Microsoft Fabric Lakehouse build, OneLake ingestion via Synapse Link and Dataflow Gen2, semantic model definition with business rules baked in. Revenue, margin, AR aging and inventory turns all defined once — every report inherits the definition.
Power BI workspace build, Direct Lake reports, executive dashboard, role-level security so each business unit sees its own slice, mobile optimisation. Finance gets the group P&L; operations gets inventory turns; sales gets pipeline value.
Copilot Studio agent on top of the semantic model so leadership can ask "what was our best-margin product last month?" in plain English. Predictive analytics via Azure ML — demand forecasting, risk scoring, churn prediction grounded in Fabric data.
Every capability below sits on top of the same Fabric Lakehouse. Build the foundation once; add capabilities in any order.
OneLake, Dataflow Gen2, Synapse Link from BC and F&O. All source systems in one governed data estate. No more data-warehouse side projects — Fabric replaces the legacy Azure Synapse architecture for most Dynamics 365 BI workloads.
Microsoft Insights practiceThe semantic layer (formerly Analysis Services Tabular) sits between the Lakehouse and every report. Revenue, margin, open AR — defined once, inherited everywhere. Row-level security by role. Direct Lake connection for sub-second queries.
Microsoft Insights practiceDirect Lake mode connects Power BI straight to the Fabric Lakehouse delta tables — no import-mode lag, no overnight refresh, no stale data. The P&L you see at 9am is the P&L as of 9am. Available in GA for BC and F&O datasets.
Microsoft Insights practiceMargin, AR aging, pipeline value, inventory turns — five to ten KPIs per executive role, built on real BC and F&O data. Each role gets their slice of the Fabric semantic model. The CFO sees the group P&L; the COO sees throughput and turns.
Microsoft Insights practiceDemand forecasting, risk scoring, churn prediction via Azure ML grounded in Fabric data. Signals surface in Power BI or in a Copilot Studio agent before leadership needs to ask the question. Demand spike, margin erosion, churn risk — warned, not informed.
AI & Copilot practice"What was our best-margin product last month?" asked in Teams or WhatsApp, answered instantly from the Fabric semantic model. Copilot Studio agent grounded in your Lakehouse — no hallucinations, no made-up numbers, only data that exists in your Dynamics 365 tenant.
AI & Copilot practiceA generic Power BI template cannot understand the intercompany elimination logic in F&O or the store-replication model in LS Central. Novasoft ships product-specific semantic models because we built the tenant.
BC data ingested into Fabric via Synapse Link. Semantic model covers item-level margin, AP and AR aging, open purchase order analysis and warehouse turns. All five numbers a BC CFO needs on Monday morning, live by Tuesday of week five.
Business Central practiceMulti-entity group P&L with currency consolidation and intercompany eliminations handled in the semantic model. Statutory reporting by legal entity. Cash flow dashboard and budget-vs-actual in Power BI on real F&O data, not a spreadsheet export.
D365 Finance practiceStore comparison dashboards, basket analysis by category, shrinkage by location, staff productivity. Retail Co-Pilot on top for natural-language store queries. LS Retail Diamond Partner — five consecutive years — means the data model is deep, not generic.
LS Central practicePipeline value by stage and rep, win-rate trends, average deal age, forecast accuracy against actuals. Grounded in the same Dataverse as your BC tenant — so the sales pipeline and the fulfilment capacity are in the same semantic model.
D365 Sales practiceNot licence metrics. Not "improved visibility." These are specific, verifiable changes that Novasoft customers report in the first two weeks after a Fabric + Power BI go-live.
Live Microsoft Fabric with Direct Lake Power BI means the P&L closes in hours, not days. Finance gets the same number as operations because they both read from the same Lakehouse row. The three-day month-end spreadsheet cycle stops the week the semantic model goes live.
One semantic model, one set of business rules, one source of truth. The CEO dashboard and the FP&A model agree because they read from the same Lakehouse. The revenue number in the board pack is the revenue number in the operational report. Not approximately — exactly.
Role-based Power BI workspaces for every team. Self-serve analytics with guardrails so the finance analyst can slice the margin data without accidentally breaking the shared dashboard. IT gets out of the report-building business — permanently.
Predictive analytics on Azure Machine Learning and Copilot Studio agents surface the signal before you ask the question. Demand spike, margin erosion, churn risk — you get warned, not informed. The difference between a Tuesday alert and a Friday board surprise is three days of recovery time. Extend further with the Business Process Automation practice to act on the alert automatically.
Novasoft delivers data analytics projects from four delivery centres — UAE, Saudi Arabia, India and the USA. The same Microsoft Solutions Partner team is on every engagement regardless of where the customer sits. Saudi Arabia projects run through the local Novasoft entity for on-site work; UAE, India and USA cover remote and hybrid delivery across the Gulf, Indian-subcontinent and North-American business hours.
A standalone BI consultancy starts a Fabric engagement with a reverse-engineering project. They map the BC or F&O schema from scratch, negotiate with the customer's IT team about which tables hold which business logic, and build a semantic model on top of a data estate they have never seen before. That reverse-engineering phase takes 4–8 weeks and produces a model that has a non-zero probability of being wrong about something important.
Novasoft built your BC or F&O tenant. The Fabric schema, the semantic model field definitions, the intercompany logic, the LS Central store replication model — all of it starts from a solid data foundation because the same team that implemented the ERP is now building the Lakehouse on top of it. Implementation to BI go-live, same team, no handover risk, no schema-archaeology. That is the reason the Novasoft Fabric Lakehouse timeline starts at four weeks rather than twelve.
Edited excerpts from Novasoft customer references. Every reference is contactable on request during the scoping workshop.
Fabric replaced four separate BI tools we had been running in parallel. One Lakehouse, one semantic model, one dashboard for the whole group. The CFO stopped asking which system the number came from — because it only comes from one place now.
Store comparison dashboards were live in two weeks. The first time we had seen real-time sales by category across all our locations in the same view. Previously it was an export from three different systems every Friday morning. Now it is just there.
Budget vs actual in Power BI on Business Central data. Month-end close went from five days to same-day. The semantic model was the key — once "budget" and "actual" meant the same thing in every report, the reconciliation work disappeared.
The Fabric Lakehouse sits at the centre. Every technology below connects to it — either as a data source ingested into OneLake or as a consumption layer on top of the semantic model.
Four Novasoft-built or Novasoft-implemented Co-Pilot products that connect directly to the Fabric Lakehouse and semantic model — AI answers grounded in your Dynamics 365 data.
Active Microsoft Solutions Partner — Business Applications credential, covering Power BI and Fabric as part of the data-and-AI pillar. Azure OpenAI Practitioner Certified. Consultants certified across the Dynamics 365 and Fabric stack.
Microsoft practice
For retail customers on LS Central, the Novasoft Power BI semantic model is built by the team that implemented the LS Central tenant — store replication model, POS data structure and loyalty schema are all known. Verified on the LS Retail partner directory.
LS Retail practice
At go-live the Fabric Lakehouse, the Power BI semantic models and the refresh schedules hand over into NovaCare 360° — refresh-wave readiness for Microsoft's monthly Fabric updates, semantic model patching, workspace governance and quarterly executive-dashboard reviews. Same partner, no inter-vendor gap.
Explore NovaCare 360°Five updates to the Novasoft data analytics practice in 2025–2026 — platform GA milestones and Novasoft-built products that ship on top of the Fabric foundation.
Direct Lake, OneLake and Fabric Lakehouse reached general availability in 2025, replacing legacy Azure Synapse for most Dynamics 365 BI workloads. Novasoft has been building on Fabric since public preview — the practice is production-ready, not experimental.
Insights practiceSub-second dashboard refresh in GA for BC and F&O datasets — Direct Lake mode replaces import mode entirely for Fabric-backed reports. The month-end P&L that used to take an overnight refresh now updates the moment a posting lands in the ledger.
Insights practiceNatural-language report generation and Q&A grounded in the Power BI semantic model. Ask "show me margin by product category for Q1" and get a formatted visual — no SQL, no DAX. Novasoft deploys Copilot in Power BI as part of every Fabric engagement.
AI & Copilot20+ retail KPIs in plain English — store performance, basket analysis, shrinkage, replenishment signals — built on Fabric and LS Central data. A Novasoft product, not a generic template. Available in Teams and WhatsApp. Delivers immediately after the Fabric Lakehouse goes live.
Retail Co-PilotAI procurement analytics grounded in the BC Fabric Lakehouse — vendor spend analysis, PO matching, approval routing, demand-based replenishment. 15+ procurement KPIs in chat, answered from the same Fabric data that powers the executive dashboard.
Purchase Co-PilotThe most expensive BI mistake is buying Power BI before sorting the data model. Every dashboard we have ever rebuilt started the same way — great visualisations on top of bad data. The semantic model is not the glamorous part of a Fabric engagement, but it is the only part that determines whether the CFO trusts the number on Monday morning. We spend 60% of every BI engagement on the model — not the dashboard. That is why our dashboards work.
Novasoft Leadership · 20 years in Microsoft Dynamics and BI
No dashboards on day one. First, we map your Dynamics 365 data estate, identify the five KPIs your leadership needs most, and give you a written Fabric + Power BI scope inside five business days. Free, even if you never sign with us.
Tell us about your Dynamics 365 data estate and what leadership needs to see. A Novasoft data architect — not an SDR — will be in touch within one business day to book the assessment.
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Microsoft Fabric Lakehouse build, OneLake ingestion from Dynamics 365 (BC, F&O, LS Central, D365 Sales), Power BI semantic models with Direct Lake, executive dashboards, role-level security, Copilot Studio agents on top of Fabric data, and predictive analytics via Azure ML.
A standard Fabric Lakehouse + Power BI semantic model + 5-dashboard executive workspace takes 4–6 weeks from data-audit to go-live. Predictive analytics or Copilot Studio agents on top add 2–6 weeks depending on model complexity. Timelines depend on data source complexity and number of business rules.
No — Novasoft can build Fabric and Power BI on any Dynamics 365 tenant, even one implemented by a different partner. The data audit at week 0 maps your existing data estate and confirms the Synapse Link / Dataflow ingestion approach. It is faster if Novasoft already knows your BC/F&O schema.
A semantic model defines business rules, KPI calculations and relationships in one place — so every report and dashboard reads from the same definition of "revenue," "margin" or "open AR." Without it, different Power BI reports give different numbers for the same metric. Fabric's semantic layer is what makes the CFO dashboard and the FP&A model agree.
Yes. Multi-entity consolidation (multiple BC companies, multiple F&O legal entities) is a core Novasoft BI capability. OneLake ingests all entities into a single Lakehouse, the semantic model handles currency consolidation and intercompany eliminations, and the Power BI workspace surfaces group-level and entity-level views side by side.
Microsoft Solutions Partner — Business Applications (covers Power BI and Fabric as part of the data-and-AI pillar). Azure OpenAI Practitioner Certified. LS Retail Diamond Partner — 5 consecutive years (2022–2026). Deep Dynamics 365 Business Central specialisation since v2009. 20+ years as a Microsoft partner.
Last reviewed May 2026.
