Data & AI Architecture - Cloud Design, Security and Performance

Data Lake and Data Warehouse play complementary roles in a modern architecture.The Data Lake is a massive, flexible storage area that holds all data, whether structured (SQL databases), semi-structured (JSON files, logs, CSVs) or unstructured (images, videos, documents). It is often hosted in the cloud (Azure Data Lake, Amazon S3) and serves as the basis for exploratory research, AI modeling and machine learning.The Data Warehouse, on the other hand, contains cleansed, organized data ready for analysis in BI dashboards or analytical tools. A high-performance company combines the two: the Data Lake for innovation and prediction, and the Data Warehouse for operational and strategic management.

Cloud computing is now the standard for data management and artificial intelligence projects. It offers instant scalability, enhanced security and reduced infrastructure costs.
Unlike an on-premise environment, the cloud offers unlimited resources on demand. You only pay for what you use, with no hardware investment.
Platforms such as Microsoft Azure or Microsoft Fabric enable you to combine storage, processing, BI, AI and governance in a single ecosystem. They also integrate advanced functions for high availability, supervision and recovery in the event of an incident.
Finally, the cloud encourages collaboration between teams: data can be accessed anywhere, with strict access controls, and AI models can be deployed globally in a matter of minutes.

At IT Systèmes, security is not an add-on at the end of the project: it's integrated by design, right from the conception of the architecture.
We apply the "Zero Trust" principle, based on systematic verification of every user, device and data flow. Access is managed via RBAC (Role-Based Access Control) and MFA (Multi-Factor Authentication) policies.
Data is encrypted at every stage: at rest, in transit and during transformation. Environments are segmented to limit the risk of propagation in the event of an incident.
We also implement real-time monitoring tools, automatic alerts and regular audits.

The duration depends on your organization's scope and Data maturity: an initial foundation (Data Lake, governance and security) can be operational in 4 to 8 weeks. For a complete architecture, integrating cloud migration, Data Warehouse, automated pipelines and AI, it takes between 3 and 6 months.success depends above all on the quality of the scoping phase and the level of preparation of existing data.at IT Systèmes, we work according to an agile methodology: we rapidly deliver visible results (MVP) while pursuing the continuous evolution of the platform. This iterative approach ensures a rapid return on investment while securing the project in the long term.

Conventional data architecture is limited to collecting, storing and retrieving data. It is essential for BI, performance reporting or financial consolidation, but remains descriptive.
An AI-ready architecture is designed to exploit data in a predictive and prescriptive way. It integrates specific building blocks: learning pipelines, training environments (AI sandboxes), GPU resources for deep learning, and MLOps orchestration tools to automate the model lifecycle.
It enables the industrialization of AI projects - sales prediction, fraud detection, predictive maintenance, automatic language processing - while ensuring security, traceability and supervision.
It is this approach that enables companies to evolve towards a truly data-driven organization.

Common mistakes include a lack of governance strategy, poor anticipation of future needs, or an overly rigid architecture.
Some companies prioritize tools over strategic thinking, leading to complex, costly and inefficient integrations.
Others neglect data quality, making analyses biased and AI models unreliable.
IT Systèmes helps avoid these pitfalls by laying the foundations before any implementation: audit, blueprint, governance, security and scalability. Each project is documented, supervised and designed to last.

A successful Data & AI architecture generates immediate and measurable benefits:

• Faster, better-informed decisions thanks to a consolidated, real-time view of key indicators.
• Reduce operating costs by pooling infrastructures and automating processes.
• Improved security and compliance thanks to centralized, traceable access.
• Accelerate innovation with the ability to rapidly test new AI use cases.
  Companies that structure their data observe an average productivity gain of 25 to 40%, better decision-making agility and greater user satisfaction.

IT Systèmes differentiates itself through its comprehensive, certified approach, combining cutting-edge technical expertise (Azure, Fabric, Power BI, OpenAI) with complete mastery of governance, security and compliance. Our teams, based in France, are involved in every stage of the project: scoping, design, deployment, automation and 24/7 supervision. We are recognized for our ability to transform complex environments into unified, high-performance ecosystems aligned with business challenges. With over 60 technical certifications and 400 active customers, IT Systèmes is a trusted partner in turning your data into a sustainable strategic asset.

Data governance brings together all the rules, processes and responsibilities aimed at ensuring that data is reliable, secure, traceable and compliant.
It defines who can access what, for what purpose and according to what policies.
Without governance, companies risk duplication, loss of quality, RGPD violations and a loss of trust in their information.
Good governance brings consistency, complete visibility of data assets and a sound basis for artificial intelligence projects.

Our approach is structured around four pillars:

1. Organizational: definition of roles (Data Owner, Steward, Analyst) and responsibilities.
2. Technical: cataloguing, lineage and access control tools.
3. Regulatory: RGPD, AI Act and ISO 27001 compliance.
4. Operational: continuous supervision, alerts, quality reports and audits.
   Thanks to Microsoft Purview and Fabric, we offer centralized, automated and measurable governance.

Microsoft Purview is the reference tool for efficient, automated and compliant data governance within a modern information system.
In a Data & AI architecture, Purview acts as a central governance brain: it maps, classifies, traces and secures all enterprise data, whether hosted in the cloud, on-premises or in hybrid environments.

Thanks to its Data Catalog function, Purview automatically identifies all data sources (SQL databases, Data Lake, files, business applications) and creates a unified view of information assets. It applies sensitivity labels (confidential, internal, public, critical) and detects personal data, facilitating RGPD and AI Act compliance.

Its Data Lineage engine makes it possible to track the complete lifecycle of each piece of data - from its creation to its consumption - and to identify the transformations carried out at each stage. This traceability is essential to guarantee the transparency, reliability and accountability of data processing, particularly in artificial intelligence projects.

Purview also offers access control and unified security via integration with Azure Active Directory (RBAC). This enables role-based authorization management, ensuring that only the right people have access to the right data.

Last but not least, Purview integrates seamlessly with the Microsoft Fabric ecosystem, Power BI, Azure Data Factory and Synapse Analytics, ensuring transverse governance across the entire information system.
In short, Microsoft Purview transforms data governance into a continuous, automated and measurable process, guaranteeing a secure, compliant and sustainable architecture at the service of Data & AI projects.