Current-state
What your data loads look like today, what you track versus what you want to track, and how the estate is wired.
Data Strategy and Architecture Services, Built Around Your Constraints
We start with your current setup, pressure-test it against your real loads and growth plans, then commit to on-prem, cloud, or hybrid based on what your security, cost, and team can support
What a Data Architecture Review Covers
Grounded in NeenOpal's AWS Cloud Assessment practice, our data architecture consulting services examine four areas before proposing a platform. This is where an enterprise data strategy stops being a slide and starts being an architecture.
Cloud cost
Your existing environment is measured against security, performance, and cost, with a TCO view of where spend leaks across cloud vs. on-prem.
Warehouse fit
Whether your warehouse and pipelines fit real-time and streaming workloads, or whether a lakehouse, data fabric, or data mesh pattern fits better.
AI readiness
How ready your data is for BI, AI, and ML, and what modernisation would demand, from data catalog coverage to master data management.
Assessment before proposal
Start with our Assessment and see your estate as an architect does. Your data strategy consultant separates what matters now from what can wait, sizing our data strategy and architecture services to your budget. You leave with a phased data architecture roadmap, a data operating model, and a target modern data platform architecture.
PARTNERS
How We Decide: On-Prem, Cloud or Hybrid
We weigh security and compliance first, then cost, then how much infrastructure your team can realistically run, the same order every time. Here’s how it looks:
When on-prem
When cloud
When Hybrid as the right path
Security or compliance rules block data sharing or storage with third-party vendors and outside locations.
A fresh build with no in-house team available to run and maintain the infrastructure.
An on-prem estate being migrated to cloud in phases, with hybrid as the intermediate step.
The estate is already fully on-prem with a well-staffed infrastructure and DevOps team in place.
Existing workloads or unused cloud credits already sit with AWS, Azure or Google Cloud.
On-prem capacity is maxed out and processing is slow, with no appetite to upgrade internally.
Workloads are stable, with little incremental processing or scaling expected in the near term.
Infrastructure management is off the table, or hosting costs need to come down fast.
Some data must stay on-prem while other workloads move to cloud.
Real Data Architecture Outcomes
Results from NeenOpal's own data architecture and cloud modernization engagements.
80%
Faster data pipeline execution
30–50%
Projected infrastructure savings identified
~50%
Lower operational cost
Why NeenOpal for Data Strategy and Architecture
Most architecture decisions are made once and lived with for years. We write down the reasoning behind ours, the same order every time, so a data leader can audit the call years later.
Logic-led
Our data strategy consulting picks the deployment model from security, cost, team capability, and growth, in that order, every time, so you can check our logic.
Certified architects
AWS Data & Analytics Competency and Microsoft Solutions Partner credentials with the Analytics on Azure specialization, held by architects who design for your actual loads and growth.
Cost-mindful
Scope sized to your budget, with an explicit now-versus-later split and cloud credits pursued on your behalf wherever AWS or Azure make them available for your project.
The Thinking Behind Every Recommendation
NeenOpal's co-founder walks through what happens before a recommendation gets made. Security and compliance are checked first, then cost, then what your team can realistically run, worked out by AWS- and Microsoft-certified architects across regulated and high-growth industries alike. Watch how that judgment gets applied before a single line of infrastructure gets built.
Related Data Engineering services
At NeenOpal, we build data engineering solutions end-to-end, from raw, scattered source systems to clean, governed pipelines your business can reliably run on.
Data Platform Engineering Services
Architecting scalable, secure data platforms that unify your organization's data for AI and reporting.
Discover More
Data Pipeline Engineering Services
Designing and building automated, reliable data pipelines that keep your analytics always current.
Discover More
Data Warehouse Modernization Services
Modernizing legacy data warehouses into scalable, cloud-native architectures built for speed and governance.
Discover MoreChoose the Engagement Model That Fits Your Needs
Managed Architecture Engagement
A dedicated data architect plus the full team your rollout needs, owning the assessment, target-state architecture, governance design, and handover end-to-end.
Request an architecture assessment
Architects on Your Team
Certified AWS and Azure architects join your existing team for the migration, governance modeling, or platform work you don't have in-house bandwidth for.
Find available data architects
Fixed-Scope Architecture Assessment
One estate assessed, fixed scope, fixed price, and milestone-based delivery, so you know the cost, timeline, and outcome before work begins.
Get an assessment estimate
Data Strategy and Architecture FAQs
What clients ask before they sign, answered here so you can compare us on specifics.
Security and compliance lead, then cost, then your capability to run infrastructure. Fast growth or unconfirmed usage favours cloud pay-as-you-go; strict compliance or a well-staffed on-prem team favours on-prem; phased migrations and maxed-out capacity favour hybrid.
When compliance rules prevent third-party or off-site storage, when you already run fully on-prem with a strong infrastructure and DevOps team, and when workloads are stable enough that scaling is not a near-term concern for the business.
When you are migrating to cloud in phases, when on-prem capacity is maxed out and slowing processing, or when policy keeps some data on-prem while other workloads move across. Hybrid is then the design, not the fallback.
Yes. Where we can secure AWS or Azure credits to offset your initial costs, that weighs meaningfully on the call, because it changes the real cost curve of a modern data platform architecture across the first year.
Assessment first, then a two-way scoping conversation that separates essential now from later and sizes the work to your budget. Our data architecture consulting services are quoted against that scope, not a fixed package you grow out of.