Our data project methodology
To ensure that the developed solution meets business needs
and to commit to a fixed, controlled overall budget

A two-step data project methodology, from use-case definition to operational deployment.

data project methodology

Icotype

Step 1
Requirements specification

  • Business interviews
  • Document collection and analysis
  • Data inventory, qualification, and selection
  • Co-creation workshops
  • Graphic and functional mockups
  • Specification document

Step 2
Development and deployment

  • Data collection and validation
  • Integration and automation
  • Interface and KPI development, algorithm documentation
  • Training and documentation
  • Assistance and support
  • Maintenance and updates

 

Which data can be leveraged?

  • Your internal data
  • Your partners’ data
  • Data you will collect (partners, acquisition)
  • Data you will generate
  • Open data sources

Our advantage: data

Before any analysis, our teams consolidate, verify, and correct the data, whether it is open, acquired from a third party, or owned by our clients.
This allows us to maintain a high-quality open data portfolio and a proven methodology that we make available to our clients.

Our uniqueness

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A fixed budget and final from the validation of the specification document

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Data analysts with diverse profiles, cultivating curiosity, knowledge sharing, and benevolence

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Technological innovation 100% European and sovereign

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A single point of contact for support from project scoping to change management

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An availability rate between 99.99% and 99.999% over the last 10 years, supporting on average 2,000 active users per week, enabled by a proactive continuity policy and a rigorous selection of subcontractors

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A flexible and iterative working method to promote performance, adaptability, and robustness

SPALLIAN’s data project methodology is based on a structured, proven and iterative approach, designed to support organizations at every stage of their data projects. From needs specification to production deployment, this data project methodology applies to all our solutions, whether supervision and analytics platforms, decision-support tools or territorial data valorization solutions.

This methodological approach structures the development and deployment of solutions such as SAB, SCOD and thelma, relying on in-depth use-case analysis, data qualification and reliability, integration of internal, partner and open data sources, as well as automation of data processing and indicators. The data project methodology therefore ensures the robustness, performance and scalability of the solutions, while supporting their adoption by end users.

Built on recognized expertise in data analysis, data engineering and complex project management, our data project methodology incorporates strong requirements in terms of security, European technological sovereignty and service continuity. It enables data to be transformed into an operational lever serving decision-making, operational efficiency and the sustainable performance of public and private organizations.