
Financial management system
Our client is a US-based clean energy company. Their solution combines financial and technological innovation to accelerate the deployment of solar, wind, and other critical infrastructure worldwide.
Transform your data architecture into a high-performing engine for growth with CHI Software’s data modeling pros. Whether your goal is building from scratch or improving existing systems, our data modeling consultants help you make data work for your business – not the other way around.
We define clear relationships between data entities, map out technical architectures, and create efficient schemas that match your specific use case. This layered approach ensures your model is both business-relevant and technically sound, ready for implementation at any scale.
CHI Software’s team can build modern data models for cloud-native platforms (AWS, Azure, GCP) that provide scalability and compatibility with your entire tech stack. We optimize our models for fast deployment, easy integration, and high flexibility as your cloud strategy evolves.
Choose the right architecture (Star, Snowflake, or hybrid) to support high-performance analytics and reporting, including BI tools and custom dashboards. We synchronize every model with your reporting goals, KPIs, and data granularity requirements to eliminate confusion and rework.
We help you reduce redundancy and improve query performance across relational and non-relational databases. Our tasks include schema normalization, indexing strategy improvements, and restructuring poorly designed tables to support data management.
Hire data modeling experts from CHI Software to maintain visibility and traceability across your data flows – a must-have for compliance, audits, and trust in AI outputs. We help you understand where data comes from, how it transforms, and how to track its usage across systems.
Our engineers collaborate closely with data scientists and analysts to model inputs for machine learning systems, predictive engines, and advanced reporting solutions. With well-structured data models, your algorithms perform more accurately and deliver results with less overhead.
Need ongoing support? Our data modeling managed services cover continuous optimization, version control, and documentation updates to support your evolving business needs. We act as an extension of your team, helping you adapt to change without technical debt.
A well-structured data model lets your team pull reports faster and with fewer errors, even when working with real-time streams or complex technology ecosystems.
Accurate modeling provides cleaner input data for machine learning and BI platforms, especially when grounded in a well-defined data methodology, providing more reliable outcomes.
You can migrate to cloud platforms with clean, well-structured data models that minimize cost, reduce performance issues, and improve post-migration performance.
With our help, you can merge data from CRMs, ERPs, customer platforms, and external APIs into a single, consistent data model that’s easy to access and govern.
Clear data lineage and metadata modeling reduce audit risks and support compliance with GDPR, HIPAA, and other data protection regulations.
Our team of data modeling consultants includes certified architects and engineers with real-world experience in finance, healthcare, retail, logistics, and more. We understand how to translate industry-specific requirements into structured and usable data systems.
We go beyond diagrams. CHI supports your whole data ecosystem – from architecture planning and modeling to implementation and handover. Whether you need one-time data modeling consulting or ongoing services, we’re here for your business.
From day one, you’ll have full visibility of our progress, with frequent check-ins to align on goals and incorporate your feedback. With this approach, the final data model will reflect your business needs, not just technical specs.
We’ve gathered the key questions clients ask about our data modeling services and answered them for you below.
Data modeling services focus on structuring your data before development begins. While database development handles implementation, modeling defines the logic, including relationships, structures, rules, and formats, to make your data scalable and consistent.
Yes, especially if you plan to scale, integrate new systems, or improve analytics. Many legacy databases weren’t built with long-term flexibility or cloud compatibility in mind. Our data modeling consultants can assess and optimize your current architecture for future growth.
You should consider hiring data modeling experts if:
- Your team lacks experience with advanced data modeling techniques (dimensional modeling, normalization, or metadata management);
- You’re preparing for a cloud migration and need to redesign your data architecture for platforms like AWS, Azure, or GCP;
- Your analytics, AI, or BI projects are underperforming due to poor data structure or inconsistent data sources;
- You’re integrating data from multiple systems or departments and need a unified model;
- You want to accelerate delivery without hiring and onboarding full-time data architects;
- You need an outside perspective or specialized consulting to validate your current models or recommend improvements.
Our experts often work as an extension of internal teams, bringing in niche skills to avoid delays, rework, or performance bottlenecks.
We’ve successfully delivered projects for:
- Finance and insurance: For secure and audit-ready data models and advanced risk analytics;
- Healthcare: Creating compliant data structures for analytics and AI;
- Retail & e-commerce: Supporting personalization, inventory management, and omnichannel insights;
- Logistics and manufacturing: Optimizing operational data and predictive maintenance workflows;
- Telecom and IoT: Structuring large volumes of real-time and sensor data.
No problem! Cloud transformation is one of the top reasons clients turn to us. Our engineering consultants redesign your AWS, Azure, or GCP models, ensuring minimal downtime and improved data quality.
Here’s our typical flow:
- Discovery and requirements gathering: We align on your business needs, data sources, and project goals;
- Data analysis and profiling: We assess data quality, relationships, and gaps to inform model design;
- Model design and validation: Our team builds conceptual, logical, or physical models and tests them with your real data and use cases;
- Implementation support: We help your engineering teams transform models into functional systems;
- Documentation and handover: You get full visibility and control over the model, plus optional training and support.
If needed, our data modeling managed services will keep your models aligned with changing requirements over time. Contact our team to get your project plan.
Timelines depend on your goals, data complexity, and the number of systems involved. Here’s a general breakdown:
2–4 weeks for focused projects like modeling a single data source or preparing for a BI tool rollout;
1–2 months for end-to-end data model design across multiple departments or platforms;
We also provide ongoing support if your data ecosystem is evolving.
We’ll define a clear roadmap during the discovery phase so you know exactly what to expect – no guesswork involved.
Sure thing! We deliver well-structured documentation with every engagement. If needed, we also offer workshops or technical walkthroughs to help your internal teams understand and maintain the models long-term.
es, we often collaborate with ML engineers to create high-quality datasets. Proper modeling is essential for accurate and reliable AI outputs, whether you're building a predictive engine or a real-time recommendation system.
It all starts with a discovery call. We’ll discuss your current data landscape, business goals, and technical challenges to see where our data modeling consultants can bring the most value.
From there, we’ll provide:
- A tailored proposal with a clear scope, timeline, and deliverables;
- Recommendations based on your tech stack, industry, and future plans;
- Optional guidance on whether a one-time project or data modeling managed services would suit you best.
There is no pressure, no jargon – just a practical, expert-driven conversation to move your project forward confidently.