Insight Analytics
Service

Cloud Analytics

Move reporting off the server under someone's desk — with governance and cost controls in place before the first invoice arrives.

Cloud analytics migrations go wrong in predictable ways: a lift-and-shift that preserves every bad habit, or an open-ended platform build with no cost guardrails that produces a shocking bill in month three.

We run migrations in slices. One reporting domain moves at a time, running in parallel with the existing system until outputs match, so there's never a big-bang cutover weekend. Governance, tagging, and cost monitoring are configured in the first sprint, not retrofitted.

The outcome is elastic capacity, month-end that doesn't degrade for everyone else, and a platform your team can extend — with a spend dashboard finance can read.

Problems this solves

What we usually walk into

  • The reporting server can't handle month-end and everything slows down.
  • Hardware refresh is due and the capital request is hard to justify.
  • Disaster recovery is a backup tape and a hope.
  • A previous cloud project produced a bill nobody could explain.

Technologies

What we build with

Azure (Fabric, Synapse, ADF)AWS (Redshift, Glue, S3)DatabricksSnowflakeTerraformPower BI

Industries that benefit

  • Financial services
  • Healthcare
  • Retail
  • Manufacturing
  • Education

Implementation process

How the engagement runs

  1. 01

    Assessment and business case

    Inventory current workloads, size cloud equivalents, and produce a defensible cost comparison.

  2. 02

    Landing zone

    Networking, identity, environments, tagging, and budget alerts configured as code.

  3. 03

    Sliced migration

    One domain at a time, run in parallel and validated against the legacy output before cutover.

  4. 04

    Optimisation

    Right-size compute, add auto-suspend and caching, and tune the workloads driving spend.

  5. 05

    Operating model

    Runbooks, monitoring, and a cost review cadence your team owns after handover.

Sample screens

What the finished work looks like

Representative layouts using demonstration data — client work is never shown without written permission.

Migration tracker

Domains

8

Migrated

6

Variance

0.00%

Migration tracker

Domains migrated, in parallel run, and validated.

Platform spend

Monthly

$6.2K

vs Budget

-12%

Auto-suspend

on

Platform spend

Monthly cloud cost by workload with budget threshold.

Workload mix

BI

48%

ETL

37%

Ad hoc

15%

Workload mix

Compute consumption split across BI, ETL, and ad hoc.

Illustrative example

How a cloud analytics engagement typically plays out

Anonymised scenario · not a verified client record

Credit union, $2.8B in assets

Challenge

Reporting ran on an ageing on-premise SQL Server that slowed to a crawl during month-end close, and a hardware refresh quote had just landed with a six-figure number attached.

Solution

A sliced migration to Azure with Fabric: landing zone as code, budget alerts from week one, and eight reporting domains moved one at a time in parallel run until every figure tied to the legacy system.

Result

Month-end reporting no longer degrades under load, the hardware refresh was avoided, and monthly platform spend has stayed within the budget set at the start.

Illustrative figures

0.00%

Variance at cutover

Avoided

Hardware refresh

-12%

Spend vs budget

This is a composite illustration of the scope, approach, and range of results this service is designed to deliver. It does not describe a specific named client, and the figures are demonstration values rather than audited outcomes. We're happy to talk through real references under NDA on a call.

Deliverables

What you receive

  • Migration assessment and cost model
  • Infrastructure-as-code landing zone
  • Migrated and validated reporting domains
  • Cost monitoring dashboard with budget alerts
  • Operations runbook and team enablement

FAQs

Questions we get asked

Azure or AWS?
Usually whichever your organisation already runs. If you're greenfield and Microsoft-centric, Azure and Fabric shorten the path to Power BI considerably.
How do you avoid a runaway bill?
Budgets and alerts in week one, auto-suspend on every compute resource, tagging by workload, and a spend dashboard reviewed weekly during the project.
Can we run hybrid?
Yes. Several clients keep transactional systems on-premise and move only analytics, connected through a gateway or replication.
What happens to our existing reports?
They're validated in parallel against the migrated data and only switched over once outputs tie. Nothing is decommissioned before that.

Related services

Often scoped alongside this

Data Engineering

Lakehouse, streaming, orchestration, and observability.

View data engineering

Data Warehousing

Dimensional models on Snowflake, Fabric, SQL Server, and Azure.

View data warehousing

ETL Development

Reliable ingestion pipelines from any source to any target.

View etl development

Talk through your Cloud Analytics project

A 30-minute call is usually enough to tell you whether this is a two-week fix or a two-month build — and roughly what it costs.

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