Six services bolted together,
or one Lakehouse that hides the joins.
Azure consultant for industrial operations. Microsoft Fabric, Azure Data Factory, Synapse, Azure SQL, Azure OpenAI and the identity layer that ties them to your Microsoft 365 tenant. SKU sizing modelled before the prototype — not after the bill surprise.
Trusted by manufacturing, FMCG, packaging and logistics operations across India, the GCC, Singapore, the UK and North America.
50+
Clients delivered
150+
Projects
14+
Years in industrial data
5
Markets
Who this is for
Azure consulting built around your role
Azure data-platform consulting for mid-market manufacturers, FMCG and supply chain — the landing zone, ingestion and governance each leader needs, mapped to the decision they own.
IT Head
The problem
Subscriptions were spun up per project, so there is no landing zone, RBAC is inconsistent across resource groups, and every new workload adds another thing to patch and monitor.
What we build
A governed Azure landing zone — subscription and network topology, Microsoft Entra ID roles, and Microsoft Purview governance set once so new workloads inherit the guardrails.
One landing zone your team can actually administer
Head of Data
The problem
Ingestion is stitched together by hand — a mix of on-prem SSIS, scripts and manual extracts — and nobody can say cleanly where a number came from.
What we build
Azure Data Factory ingestion into OneLake, with Microsoft Fabric and Synapse for analytics and lineage tracked in Microsoft Purview.
First working data workload in 6 weeks
Operations Director
The problem
The data platform IT runs is invisible to operations — reports arrive late, and when a pipeline breaks nobody owns it.
What we build
A Fabric Lakehouse on OneLake feeding operational dashboards, with a named owner and monitored Azure Data Factory pipelines behind it.
Operational reporting that holds up on the floor
CFO
The problem
Ungoverned subscriptions and creeping consumption mean the Azure bill climbs every quarter with no clear line back to workload.
What we build
Azure sized to workload — SKU and capacity modelled before the build, cost tagged by domain so you can read the bill.
Azure cost tied to workload, not guesswork
The Problem
Patterns we see in every engagement
Most industrial businesses do not need every Azure service. They need a Lakehouse, a pipeline, a SQL store, a model-hosting service and an identity layer. We build that. We tell you when you need more.
Azure pricing is non-linear.
A workload that costs USD 800/month at small scale costs USD 12,000/month at 10× scale if you picked the wrong SKU. We model capacity and SKU before the prototype, not after the bill surprise.
Service sprawl is real.
Every Azure service has its own monitoring, its own RBAC model, its own quirk. Fabric solves most of that for data workloads. Outside Fabric, operational overhead is high — and most mid-market teams cannot staff for it.
Regional availability matters.
Azure UAE North, Saudi Central, India Central, Singapore — each has a different service availability matrix. Some services are not in every region. We check on day one, not week six.
Microsoft's roadmap is the roadmap.
Synapse, Power BI Premium per User, parts of Power Apps — features and pricing change. We track announcements and we will not lock you into anything Microsoft has signalled they are sunsetting.
What we build
Azure surfaces we build on
Six engagement shapes. Each one tied to a workload an Operations Director or IT Head can name.
Microsoft Fabric foundation
Replaces
The five-service Azure stack (ADF + Synapse + Power BI + SQL + Storage) that nobody can administer cleanly at mid-market scale.
- Fabric Lakehouse with OneLake as the single data store
- Data Pipelines (the rebranded ADF) for ingestion
- Power BI Direct Lake over Delta Parquet for the semantic model
- F-SKU capacity sized to actual workload
One platform replaces five. Administration overhead drops. Time to first dashboard moves from months to weeks.
Azure Data Factory for legacy migration
Replaces
On-prem SSIS packages running on a Windows server nobody wants to touch.
- ADF (or Fabric Data Pipelines) for orchestration with 100+ source connectors
- CDC where the source supports it — incremental loads, not full reloads
- Audit and lineage built in
- Migration from SSIS, on-prem schedulers, custom scripts
Brittle on-prem ETL retired. Modern orchestration with monitoring and lineage.
Azure SQL for OLTP and Power Apps backends
Replaces
The SQL Server running on a VM in your DC that has not been patched in 18 months.
- Azure SQL Database for new OLTP and Power Apps backends
- Azure SQL Managed Instance for lift-and-shift from on-prem SQL Server
- Active geo-replication for DR — same SLA as enterprise on-prem at a fraction of operational cost
- Integration with Microsoft Entra ID for SSO from your existing tenant
Patching, backups, DR become managed. Your team stops being the DBA team.
RAG on Azure OpenAI with Azure AI Search
Replaces
The PDF SOP library nobody opens because finding the right page takes 12 minutes.
- Document ingestion via Azure Document Intelligence
- Embedding via Azure OpenAI text-embedding-3-large
- Hybrid search (vector + keyword + BM25) in Azure AI Search
- Generation via GPT-4o or GPT-4 Turbo with citation to source page
Plant managers ask SOP questions in plain English. Answer arrives with citation. Compliance teams accept it.
Azure IoT for fleet management at scale
Replaces
The home-grown MQTT broker on a VM that handles 12 sensors fine and fails at 500.
- Azure IoT Hub for device registration and twin sync
- X.509 device authentication, OTA firmware updates
- Fleet-scale device management — 500+ sensors across multiple sites
- Integration with Fabric Real-Time Analytics for the stream
Edge device fleet becomes manageable. New sites onboard in days, not weeks.
Identity, governance and Purview
Replaces
The 'we will do governance later' approach that becomes a compliance audit failure two years in.
- Entra ID for workspace access — SSO and conditional access from existing tenant
- Sensitivity labels applied at source — propagate through Fabric to Power BI
- Purview catalogue for data discovery and lineage
- DLP policies on Power Platform and Fabric workspaces
Compliance teams sign off. New use cases launch faster because the governance scaffolding exists.
Business outcomes
What changes after the build
Figures are from delivered MDI engagements, tagged to their source; capability outcomes apply to every governed Azure build. Azure consumption savings depend on your estate — we model them, we do not headline a number we cannot stand behind.
up to 90%
Faster reporting refresh
Korpack — CDC pipeline + Direct Lake
−85%
Pipeline runtime cut
Korpack — Azure Data Factory + Fabric
6 weeks
To first working Azure workload
MDI standard cadence
8 weeks
To production
first governed workload
A governed Azure landing zone — Microsoft Entra ID, Microsoft Purview, cost tagged by workload
Azure Data Factory ingestion into OneLake, lineage tracked end to end
Microsoft Fabric and Synapse analytics on one Lakehouse, not six stitched services
SKU and capacity sized before the build, so the Azure bill maps to workload
Client results
Proof, not promises
Verified outcomes from delivered Microsoft-stack work — Azure Data Factory, Microsoft Fabric and Power BI. Each links to the full case study.
How we work
From estate audit to first vertical slice in 6 weeks
Discover → Architect → Prototype → Deploy. We model cost before we commit to architecture.
01
Discover — audit existing Azure estate
Two weeks. We pull subscription-level cost and usage. Find the services that are unused but charged. Score what you have vs what you actually need.
02
Architect — target architecture with cost model
One to two weeks. Target architecture document, SKU sizing, capacity cost model, identity and governance plan. Reviewed with your IT leadership before any build begins.
03
Prototype to Deploy — vertical slice first
Four to twelve weeks depending on scope. One end-to-end vertical slice in production. Scale across domains. Documented runbooks and trained internal team at handover.
Technology stack
Lakehouse
Pipelines
SQL & Database
AI
IoT & Edge
Identity & Governance
Why MyData Insights
Why choose MDI for Azure consulting
Microsoft-stack specialists
We build only on Azure, Microsoft Fabric, Power BI and Power Platform — so your IT team can support what we deliver, with no niche-vendor lock-in.
SKU sized before the build
We model Azure capacity and SKU with the workload in front of us — not a procurement guess — so the consumption bill does not surprise you at 10× scale.
Governance from day one
Microsoft Entra ID, Microsoft Purview and sensitivity labels are set in the landing zone at the start, not retrofitted after a compliance audit fails.
One Lakehouse, not six services
Where Microsoft Fabric and OneLake replace the ADF-plus-Synapse-plus-SQL stack, we build on the surface a mid-market team can actually administer.
Senior practitioners only
The person you meet in discovery designs your Azure landing zone. No junior hand-off funded on your budget.
First working output in six weeks
A governed Azure workload live on a fixed scope in six weeks — not a 50-slide roadmap to review.
Common questions
What buyers ask us
We are a Microsoft 365 shop. Do we need Azure separately?
For data and AI workloads — usually yes. M365 includes Power BI Pro and Power Automate per-user, which is enough for some teams. For Fabric, Azure OpenAI and Azure SQL you need Azure subscriptions.
What about AWS or GCP?
We are a Microsoft-stack specialist. If your enterprise standard is AWS or GCP and that is not changing, we are probably not the right shop. If you are mid-market and weighing the choice, we are happy to share a frank comparison.
What is the difference between Azure Databricks and Microsoft Fabric?
Short answer: Fabric wins on time-to-value and integrated experience for mid-market industrial. Databricks wins on heavy data-science workloads and multi-cloud strategies. We have shipped both. See our stack-choice blog series.
Synapse — should we keep using it or move to Fabric?
Synapse is in maintenance mode at Microsoft. New investment goes into Fabric. If you have a working Synapse workload, we will tell you whether to migrate now or wait. If you are starting fresh, build on Fabric.
How much does an Azure-on-Fabric build cost?
Our fee is fixed-scope and confirmed after a 30-minute diagnostic — never open-ended time and materials. What moves it is the number of business domains, the source systems in scope and whether real-time ingestion is required. What we commit to upfront is the timeline: first working output in 6 weeks, not a 50-slide roadmap. Azure consumption is separate and billed by Microsoft, not us — budget USD 4,000–14,000/month for a typical mid-market build at production scale, and we model the SKU and capacity before the prototype rather than after the first bill.
Engagement
Free Azure Data Platform Review
Thirty minutes with Amit on your actual Azure estate — what you are running, what it is costing, and what a governed landing zone would change. No slides, no obligation.
What you get
- A read of your current Azure estate and consumption cost
- A target landing-zone and architecture sketch on Azure Data Factory, Fabric and OneLake
- A governance gap check across Microsoft Entra ID and Microsoft Purview
- SKU and capacity sizing against your actual workload
- A 6-week first-workload roadmap you keep
Ready to move
Book a 30-minute Azure Architecture diagnostic
30 minutes with Amit. No slides. No pitch deck. No obligation to proceed. We walk through your current Azure estate, your subscription cost, and the SKU mix you actually need.