Data analysis: a growth driver

Since the analysts at Gartner linked Big Data with Big Analytics, enterprises from across the board are coming to see this as a new field for innovation, competition and productivity, as summarised in the McKinsey institute report. In the public sector alone, the potential cost savings are estimated at 15 to 20%.

According to a Transparency Market Research study: healthcare, banking/finance and the public sector accounted for over 55% of the Big Data market in 2012. This global market was estimated, according to the consumption disparity index (the "Indice de Disparité de Consommation" or "IDC"), at some 27.7 billion dollars in 2012 and is expected to double by 2016 , including around 12% dedicated to specialised software and 80% to services.

Sogeti High Tech's Big Data services, drawing on the competencies of over 150 specialised analysts and scientists, meet the needs of industrial innovation, optimisation and analysis.

The extension of simulation

From data collection, storage, queries and mining, to the analysis and interpretation of findings, mastery of the simulation process and design complexity is a significant fundamental asset.

Sogeti High Tech's Big Data service catalogue, in the extension of simulation as well as outside of the simulation segment, is geared towards industrial organisations from all sectors with a variety of services, including:

  • Consulting, such as organising workshops, based on case studies in order to work out a project's potential impact, nature, scope, organisation, and the resources involved
  • Development of analysis models in the following contexts:
    • Heterogeneous data analysis
    • Real-time data analysis (streaming, data packets, peak loads)
    • Analysis of very high volumes of structured relational data (on the order of petabits)
    • Ad-hoc analysis within the framework of a research and experimentation project
    • Reinforcement of a data structure in order to provide a solid foundation for recurring queries
    • Elaboration of description and diagnosis models and predicative and prescriptive models
  • Management of the project to implement Big Data, the infrastructure in custom data analysis models and, at the end of the chain, predictive or forward-looking models in response to a problem With the following phases:
    • Collection
    • Organisation, storage
    • Predictive model development
    • Proposed measures
    • Validation of the ROI (Return On Investment) and transfer of knowledge

todo todo
  • Philippe Ravix
    Philippe Ravix
    Innovation Director
    +33 (0)5 34 46 93 16