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Visual Data Analytics Platform to detect your deep business.

Generate your deep machine learning business

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  • Mydataball révèle le potentiel de vos données

    MyDataBall is a tool that makes data speak for itself

    MyDataBall structures complex datasets into trees and identifies relevant correlations from all your variables and indicators.

    It allows you to navigate to the heart of your company’s data, and there find the right combinations of levers to pull in order to greatly impact your results.

     

    Thus, your BI is driven by learning employee data questions and builds an AI that optimizes the detection of the priority elements of performance

  • La sphère Mydataball

    MyDataBall makes 3D visualisation of data analysis possible

    MyDataBall is an intuitive and original navigation at the heart of your business intelligence.
    This proprietary model frees business teams for in-depth analysis with no limit of granularity.
    A true innovation that opens the door to an immediate exploitation of the promises of Big Data,
    for an operational and concrete implementation.
    A considerable saving of time to effectively share the figures between the collaborators,
    to validate a diagnosis quickly and to accelerate the interpretation.

    Through its visualization mechanics, MyDataBall solves the problem of data complexity detecting
    rules with more than 3 dimensions.

  • Exportez vos données

    MyDataBall is compatible with data mining, data analytics, data visualization and data discovery tools

    MyDataBall works on all data and formats available and immediately brings you the analysis axes with significant results.

    MyDataBall is the only solution that manages up to 2000 axes of analysis and indicators.

    The wealth of your high-value analysis is automatically exportable in the classic standards (Qlik, Tabeau, PowerBI, Matlo, …) for a quick sharing and an effective communication to your decision-making and collaborative bodies.

    In addition, our technique that combines the calculation of trees (random forest) and perceptrons (neural networks), is the only solution that allows your AI to be auditable (it’s no longer a black box).

Mydataball rassemble vos données

Data Mining – data Visualization

EXPLOIT THE GROWTH IN DATA AMOUNTS TO DETERMINE THE MAIN KEYS TO PERFORMANCE

By combining statistical and datamining methods and a spherical visualisation of results, MyDataBall makes full use of the growing amount of data accumulated. MyDataBall provides a unified view of data diversity, whether it is structured or unstructured, and whatever its source is: activity database, internet data, etc.

Our Blog (only in french)

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Les vrais chiffres du BigData

Livre Blanc sur les tendances du BigData : de la data analytic à la data visualisation, contribution MyDataBall pour GFI et PAC’. Cliquez pour voir le communiqué de presse et télécharger le livre blanc. On discute ici du positionnement des outils de data management, de statistique, de data mining et maching learning sur les principes de Knowledge Discovery […]

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OpenData INSEE par MyDataBall

Sur la plate forme MyDataBall, vous trouverez l’application sur des données INSEE en ligne.  Vous pourrez interroger les 70 indicateurs sur les 36 677 communes et les croiser avec plus de 98 variables. Vous pouvez sur la plate forme poser vos questions et détecter des règles explicatives et prédictives : Tester l’application Un exemple d’utilisation […]

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Article « An Analysis of Memory Power Consumption in Database Systems »

Article passionnant sur la mesure de la consommation énergétique de l’IT. La modélisation par arbres semblent être le chemin (distributed layers). Lien de l’article : DAMON17-MemPower

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IA sur IoT : la machine learning MyDataBall sur la consommation d’énergie dans les bâtiments

Le prototype IoT R2C Panga vous donne un résultat qui provient d’un apprentissage profond de comportements de consommation d’énergie dans des bâtiments sur 4 critères : consommation m3 eau, température, dépense électricité et présence humaine. Ainsi, après une série d’itérations d’apprentissage, notre robot est capable de détecter des comportements déviants et de suggérer des corrections […]

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