Develop the value of your information with Data Modeling

Develop the value of your information with | Data Modeling

the added-value we bring you


Workshop facilitation

Project management

Program Management
Project Management
Scope Management

Data Modeling

Definition of common vocabulary across silos
Definition of entities, business definition and business rules
Declare the grain
Identify the dimensions
Identify the facts
Definition of constraints between entities

Turn-key Data Models Implementation

Database creation
Physical creation of the data models
Data models optimization
Creation of an abstraction layer to ease the access to the data model
Development & optimization of complex queries

Data Models Deployment & Maintenance

Deployment of the data models
Evolutive maintenance of the data models
Corrective maintenance of the data models
On-call support

Our exclusive methodology to define logical data models with agility

Deliver faster, Improve quality, Maintain required agility

Defining a formal business model or data model is a key success factor (and even mandatory factor) for any project aiming to leverage data as an asset.

This logical data model allows to define Determine a common language between IT & Business Lines. It is an essential elements of project quotation and planning.

Based on our past experiences over the last 15 years, we developed our own approach to build logical data models.

data model

  1. Identify & Define entities
  2. Identify links between entities
  3. Identify & Define attributes

By Entity:

  1. Definition of source system(s)
  2. Definition of Business Management Rules


Our methodology to define data models comes out with document templates allowing to rationalize and industrialize the data modeling phase.


Based on our exclusive approach to build a logical data model, we have built some accelerators to create the underlying physical data models.
Our data models aimed to be:

  • Easy-to-understand: Comprehensive modeling allowing fast appropriation and easy maintenance
  • Efficient: Optimized for fast answers even in context of large volumetry
  • Agile: Ability to evolve easily

The physical data models we are creating are based on our numerous past experiences in this field.

create data models with

Feed data models with