Data Sciences for Decision

Modeling and industrialization of mathematical and Data Science models, to favor decision making, within a complex environment.

Differentiating axes

  • A use case and product-oriented approach (and not Proof of Concept)
  • A proper understanding of business issues to determine our features
  • Optimization of customer processes

Areas of intervention

          • Exploratory analysis to make the potential of your data progress and define the best methods and models to make the most of these.
          • Predictions based on Times Series processing. We analyze historical data to predict the future. Some examples of the covered areas:
            – Supply Chain in order to properly predict demand, optimize stocks as precisely as possible and reduce the carbon footprint
            – Marketing and/or Dynamic Pricing which leans on the analysis and frequency of a site, a place. Example: adjust the price according to weather conditions while associating a targeted marketing campaign with the latter.
            – Predictive/preventive maintenance to anticipate the change of a part, a system and reduce costs while ensuring better robustness.
            – Diagnostic support: identify common patterns related to different patients, to anticipate new health issues. The goal is to move from post-traumatic and chemical medicine to personalized preventive medicine.
              • Language analysis with NLP methods. We work on textual data (emails, social networks, article, report, etc.) to :

          – Enrich information and improve customer knowledge
          – Pinpoint new trends
          – Detect patterns

        • Computer-Vision or computer image processing. Just like NLP, by analyzing images or videos, we have the ability to provide additional information to our clients. This allows us to :
          – Trigger and create additional images
        – Recognize objects to facilitate recommendations
    – Extract key information: registration, flow of people, object recognition
    – Identify and highlight new trends via tweet analysis for example
All our expertise

Our methods of intervention

CONSULTING

We support Data Labs, Innovation, Marketing or Strategic Departments on their projects, through a very high added value, not to mention, along with the support of our employees.

Delivery

We associate our customer with a LittleBigCode team, iterating in AGILE/DevOps to deliver turnkey applications on our infrastructures but also those concerning our customers.

Solution

We develop our own solutions to offer our customers a catalog: Data/IA as a Service and therefore validate a concept to reduce the Time to Market.

Our methodology

We associate our customers with our teams in an AGILE mode, to quickly pinpoint high-impact areas and deliver effective solution, in a very short span of time. The latter can be easily deployed on a large scale.

LITTLEBIGSTART

  • Audit around the project
  • Workshops to validate the need, define the MVP, planning, and budget

    • MVP TARGETING

    • MVP Squad
    • End-User Focus
    • IS architecture and interaction

    Building

    • AGILE Interaction
    • Continious integration
    • DevSecOps
    • Deployment

    Transfering

    • Feedback
    • User training
    • IT team training
    • Support

    Our solutions

    The development of our solutions allows us to suggest a complementary offer to our customers and to stand out compared to our colleagues such as a Data/IA as a service catalog.

    Sentiments analysis

    Text and image analysis, in order to determine and understand the author's feelings on an issue.

    Pricing & dynamic marketing

    Analysis of consumers to suggest intelligent marketing services which contain customized products/services at adapted prices.

    Detection of fraud

    Analysis of identity documents (ID card, passport, visa, etc.) to check the authenticity of the document and identity its bearer, in order to detect and fight against identity theft.

    Data enrichment through Open Data

    To improve the performance of our Data applications, we have developed solutions for data enrichment by scrapping Open Data (OpenStreetMap, local government Open Data, weather data, etc.)

    Social network trend detection

    Identification of essential emerging themes and information on social networks, to be one step ahead of market trends.

    Automatic email processing

    To simplify and speed-up the processing of professional emails, our solution analyzes, classifies, and suggest a response, to each new email according to the user's profile and the history of responses.