Data is distributed across multiple systems, none of which provides a complete view. Answering a business question requires combining information from different sources, and creating a unified view of customers, operations, or results becomes a recurring effort.
Data Engineering
A data platform ready for decision-making and AI-powered growth
We turn scattered information into a consistent, scalable data platform. We integrate, transform, and store data from multiple sources to prepare it for analytics, AI, and enterprise applications.
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We are a Microsoft Top Partner
What happens when data is not prepared
Information sources are inconsistent with one another. The same metric produces different values depending on the system consulted, departments debate which figure is correct, and the organization loses confidence in the data it uses to make decisions.
Information takes too long to become available. By the time the data arrives, the window for action has narrowed, and decisions are delayed or made using outdated information.
Integration processes are manual, and every analytics project requires excessive data preparation. The team spends more time extracting, cleaning, and consolidating information than analyzing it, reducing productivity and limiting the scalability of any new initiative.
How we build your data platform
We assess your data sources and flows, design the target architecture, build pipelines that integrate and transform information, and model consolidated datasets for consumption. We then improve the platform's quality and performance during operation.
Data ecosystem assessment
We assess existing data sources and flows to understand where information comes from and how it moves. Deliverable: data map.
Data architecture design
We define the platforms and patterns on which the solution will be built. Deliverable: target architecture.
Pipeline development and data modeling
We integrate and transform data through automated processes and build analytical models. Deliverables: automated processes and consolidated datasets.
Operational optimization
We improve information quality and platform performance once it is in operation. Deliverable: optimization plan.
Technology stack
Each technology plays a defined role: Microsoft Fabric for data integration, storage, and processing; Databricks for advanced transformation and processing; Azure for integration and infrastructure services; and Microsoft Power BI for analytical consumption of information.
How we work
Each platform is built through the Possumus Adoption Framework, our four-stage adoption framework. This ensures that the work does not end when the pipelines are running. It continues with platform operations and optimization.
1
Prepare
We identify and assess your organization's data sources and flows. This stage produces the data map.
2
Incorporate
We design the architecture, build the integration and transformation pipelines, and model the information into consolidated datasets.
3
Impact
We validate the quality of the data produced by the platform before it is consumed by analytics, AI, and applications.
4
Scale
We operate and optimize the platform, improving quality and performance. This stage produces the optimization plan.
What your organization gains
A well-built data platform turns scattered information into a trusted foundation for analytics, artificial intelligence, and enterprise applications.
Data you can trust
Centralized, consistent data improves the reliability of the information used across departments.
Timely decisions
Faster access to information enables timely decisions.
Less manual work
Automating integration and transformation helps reduce operational effort and manual tasks.
A foundation built for growth
Scalable analytics platforms support future growth, while better information quality strengthens digital initiatives.

Why Companies Choose Possumus
Proven Expertise Across the Microsoft Ecosystem
Our specialization as a Microsoft Solutions Partner demonstrates our ability to design and implement solutions that integrate with each organization’s technology ecosystem.
Engineering Integrated with Adoption
We combine engineering and adoption from the start so technology is not only implemented, but also incorporated into operations, used, and continuously evolved over time.
A holistic view of technology
We connect AI, data, security, software, and cloud under a single vision, avoiding isolated solutions and reducing technology fragmentation.
Audited Management Processes
Our operations are supported by processes audited under ISO 9001.
Frequently asked questions
The most common signs are clear: data distributed across multiple systems that prevents a unified view, inconsistencies between sources that undermine trust, manual integration processes that do not scale, long information availability times that delay decisions, and analytics projects that require excessive data preparation. If your organization recognizes several of these situations, a data platform is the starting point before moving forward with analytics or AI.
Turn scattered data into a trusted foundation for decision-making
Assess my data ecosystemWe start with your current sources and flows to define the architecture your organization needs for analytics, AI, and applications.
We Are a Microsoft Solutions Partner
We hold designations across all Microsoft Cloud solution areas.
Microsoft Cloud
- Adoption and Change Management
- Custom Solutions for Microsoft Teams
- Meetings and Meeting Rooms for Microsoft Teams
- Secure AI Productivity
- Microsoft 365 Copilot
- Analytics on Microsoft Azure
- Identity and Access Management
- Threat Protection
- Microsoft 365 Copilot
- Analytics on Microsoft Azure
- Agentic DevOps with Microsoft Azure and GitHub
- Infra and Database Migration
- Azure Virtual Desktop
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Federico Tagliani
Managing Director
Our work doesn’t end with implementation. We make sure the technology is adopted and delivers results.