Get a thorough assessment of your data assets and environments to understand platform health, gaps, and modernization priorities. Our modern data architecture consultants also evaluate AI readiness—data quality for training, lineage, privacy, and access patterns—while implementing metadata capture, cataloging, and search for Gen AI workloads.
Design a superior data ecosystem that will make the difference for your business growth. ITRex is one of the few modern data architecture consulting firms that can guide you through all data decisions and regulatory challenges, including AI governance basics (secure access, environments, and controls for model/agent workloads).
Build a modern data warehouse or data lake/lakehouse and pair it with the right processing engine so your teams can run BI, reporting, analytics, and data science with confidence. Our modern data warehouse architectures are AI-ready, with feature pipelines, secure access controls, and elastic computation for training and inference.
Improve analytics quality and AI outcomes through robust data management and governance, with privacy and security built in. Our modern data architecture consultants set up row-level security, PII masking, audit trails, retention and lifecycle policies, and role-based access. This way, our clients can safely use structured and unstructured data, powering ML and Gen AI.
Accelerate and scale your systems by migrating data workflows to the cloud. Our modern data architecture consultants create migration blueprints that cover environments, governance and security, enablement/training, cutover strategy, and go-live. Our data migration strategies help prevent disruptions to dashboards, integrations, and AI training or inference pipelines.
Process data in near real time to explore use cases like second-by-second forecasting, behavioral analytics, and IoT utilization insights. With modern data architecture services, streaming pipelines can also feed ML monitoring, anomaly detection, and event-driven automation, allowing you to detect issues early and respond quickly.
Bring AI/ML into production with a machine learning stack that speeds up data workflows, from ingestion and processing to advanced analytics. Your data foundation, backed by expert modern data architecture services, will support Gen AI and agentic systems by providing governance, observability, and scalable computation for training and inference.
Unlock secure, role-based access to databases, files, documents, images, videos, and transcripts—without turning governance into a bottleneck. We package critical sources into governed data products with consistent definitions and access rules, making them safe to reuse across BI, ML, and RAG initiatives.
Build pipelines that consistently deliver clean datasets, reusable features, and embeddings for vector search and retrieval. ITRex designs ingestion, transformation, and orchestration patterns that handle batch and streaming needs, support versioning, and reduce rework. This way, we validate that AI and Gen AI apps get trustworthy inputs as your data evolves.
Make AI behavior measurable and compliant by adding monitoring, logging, and guardrails across the data-to-model chain. As modern data architecture consultants, we implement access audits, quality checks, and drift signals, plus retention and approval workflows, to help you trace outputs back to sources, improve compliance, and troubleshoot issues faster.
We listen to your data challenges and immerse ourselves in your business. Then we design the best-fit solution based on best practices in modern data architecture consulting. This way, we help you become a forward-looking, data-driven enterprise that knows how to identify and exploit new sources of value and cultivate future opportunities.
Our modern data architecture consulting firm, with hands-on experience from dozens of deployments, helps businesses create secure and flexible data architecture and integration programs. We identify value-producing projects and data products while providing expertise and governance at every step of your data journey.
A poorly-performing data warehouse delays time to insight? Data storage and processing costs outstrip budgets? Legacy databases are not scaling? We identify your most pressing problems and translate them into clear use cases, including AI/ML and Gen AI opportunities.
Our modern data architecture consultants formulate a comprehensive data strategy that accounts for metadata management, unified data governance, data movement, and other critical aspects. The purpose is to get you clean and actionable use-case data from both structured and unstructured sources used for analytics, model training, and Gen AI retrieval.
We design an AI-ready modern data architecture that can evolve as new capabilities emerge—such as vector search, feature pipelines, and secure access patterns for AI agents. This includes data models and storage, systems that connect data to business processes, integration points, and the best ways to ingest, process, and analyze data at scale.
We help you select an analytics platform or modernize your existing stack to unlock better insights. Our team delivers easy-to-use interfaces that support self-service environments and a logical semantic layer reusable across projects. In addition, ITRex provides production-grade AI capabilities, including governed access and MLOps/LLMOps observability.
A modern data architecture is a blueprint for how your organization collects, stores, governs, and uses data across cloud and on-prem systems. It typically combines data warehouse/lakehouse patterns, integration, governance, and analytics so you can generate reports and implement AI faster—e.g., a logistics firm unifying TMS, GPS, and IoT feeds for real-time ETAs.
A practical “five pillars” view is:
How about an example? A healthcare organization that integrates EHRs, claims processing, and laboratory software while enforcing strict access control and auditability practices has successfully implemented all five pillars of modern data architecture.
AI fails when data is inconsistent, inaccessible, or non-compliant. Modern data architecture consulting services help set up trusted datasets, lineage, and secure access so you can train and evaluate models reliably. For example, a predictive maintenance system in manufacturing needs clean sensor streams plus governed work-order history to avoid noisy signals.
Gen AI increases demand for governed access to unstructured content (docs, tickets, images) and for retrieval workflows. A modern data platform architecture often adds document pipelines, metadata, and vector search while keeping security controls tight. In healthcare, this can power “policy Q&A” without exposing PHI.
Look for end-to-end delivery (assessment → strategy → architecture → implementation), proven governance, and platform expertise across Azure/AWS/GCP/Databricks/Snowflake—without lock-in. Strong modern data architecture consultants will translate business goals into a roadmap with cost levers, risks, and measurable outcomes.
A modern data warehouse architecture is best for standardized reporting and finance-grade metrics. A lakehouse is better when you also need large-scale data science, unstructured data, or streaming. Many organizations use both. For logistics, a warehouse can run KPIs, while the lakehouse supports route optimization and anomaly detection. For a detailed comparison, check out our blog post on data warehouses, data lakes, and lakehouse architectures.
AI readiness entails controlled access to structured and unstructured data, dependable pipelines for features, embeddings, and retrieval, and observability (quality checks, drift signals, and audit logs). On the factory floor, an AI-ready modern data architecture ensures that sensor data and maintenance logs are consistent from ingestion to model outputs. If you’re unsure your company can implement artificial intelligence in a safe and reliable way, you can book an AI/Gen AI readiness assessment with ITRex.
It depends on scope. A focused assessment by a modern data architecture consultant can take 2–6 weeks and yields an architecture blueprint, backlog, and phased roadmap. Implementation varies from 8–16+ weeks for a first release. In heavily regulated industries like healthcare, timelines often include extra time for security reviews and validation.
Tell us about your challenges, and we’ll come up with a viable solution!
