Consistent data
We build shared models and KPIs to reduce inconsistencies, duplication and conflicting interpretations of the same data.
DATA & BUSINESS ANALYTICS
From data to decisions, with a clear method.
We build data platforms, analytical models and management tools that make information reliable, readable and useful for decision-makers.
THE VALUE
A governed data journey, from source to decision.
Our approach combines technology, process knowledge and data governance to build measurable, sustainable solutions.
Readable information
Dashboards and reports are designed to make performance immediately understandable for management, business teams and operational functions.
Better decisions
We turn data and processes into practical tools for monitoring sales, margins, costs, budgets and objectives.
FROM DATA TO DECISIONS
A reliable view of data improves the quality of decisions.
Data platforms, analytical models and visualization must work as a single end-to-end pipeline. Value is created when data is consistent, understandable and available when it is needed.
Explore our approach →CAPABILITIES
Expertise across the entire data journey.
From data platform to visualization, we build analytics environments aligned with the client's architecture and business processes.
Modern Data Platform
Modern data architectures, Data Warehouse and Microsoft Fabric to integrate and govern heterogeneous data sources.
Power BI & Qlik
Dashboards, analysis and Business Intelligence models designed for management and operational needs.
KPIs & management models
Models for management control, sales, margins, budgeting and Operational Performance Management.
From source to visualization
A governed data pipeline that ensures consistency across sources, transformations, semantic models and final visualization.
TECHNOLOGY
A modern technology ecosystem.
Technologies are selected and integrated based on the desired outcome: architecture, governance, adoption and operational sustainability.
BEA METHOD
From analysis to results, quickly.
A pragmatic, incremental approach: the client sees a working model early and refines it progressively around real needs.
01
Analyze
Processes, data and systems.
02
Design
Target operating model and architecture.
03
Prototype
A solution tailored to the client's reality.
04
Validate
Iterations with users and stakeholders.
05
Consolidate
Release, adoption and continuity.
CASE STUDIES
Data & Analytics applied to real business processes.
Selected anonymized case studies showing how data, platforms and analytical models can generate tangible results.
INDUSTRY · SALES & MARGINS
Management Business Review
Need.An industrial company with multiple business lines needed a single view of sales, gross profit and rebates, overcoming fragmented analyses and lengthy consolidation activities.
E-project intervention.E-project developed an analytical model in Power BI with drill-down capabilities, period comparisons and reusable views.
Result.A consistent information base for the business review and faster interpretation of performance changes.
INDUSTRY · PRICING & BUDGET
Digitization of the commercial process
Need. A manufacturing company managed pricing and budgeting through manual activities and disconnected steps across ERP systems, working files and reporting tools.
E-project intervention.The process was redesigned by integrating management data, operational applications and analytics, with clearer rules and controls.
Result.Reduced manual activities, greater traceability and better consistency between planning and reporting.
DATA PLATFORM · MICROSOFT FABRIC
Data platform modernization
Need.An organization with an established Data Warehouse needed to modernize its analytics architecture and prepare for new use cases.
E-project intervention. E-project supported the migration to Microsoft Fabric using a Medallion architecture and automation connected to data pipelines.
Result. A more modern and scalable data platform, ready to support the evolution of reporting, analytics and AI.
We start with a real problem in your data landscape.
We analyze sources, processes, users and objectives to identify the architecture and analytics path that best fit your context.