General Objectives

Featured

The Chair is linked to the research activity of two research groups in the Institute Mines-Telecom: the IC2/DBWeb team of Telecom ParisTech and the Management, Marketing and Strategy department of Telecom Ecole de Management. The focus is on massive data management and mining, web information extraction, social networks analysis, data visualization, online marketing and advertising, and business models.

The Big Data and Market Insights Chair aims to:

  • Tackle some key Big Data challenging problems, develop new solutions and tools
  • Promote Data-driven decision-making and marketing solutions, incorporate Big Data into Business Intelligence (BI), predictive analytics tools and marketing strategies
  • Serve as a framework of exchange between the researchers involved in this Chair and the industrial partners. Share concrete problems, data sets, experiments, innovative solutions, etc.

Its purpose is twofold: support and promote a high quality research activity, on the one hand, and heighten awareness of our students to the economic and technological challenges raised by the Big Data, on the other hand.

The Inaugural Paris Summit on Big Data Management

ParisBD_2016_Paris_Big_Data_Management_Summit_-_2016-02-17_09.44.24

On Thursday, March 24th 2016 at Telecom ParisTech will take place the Inaugural Paris Summit on Big Data Management.

There has been significant interest in big data techniques and applications in recent years. The goal of this all-day summit is to bring together researchers from the greater Paris area with an interest in big data management, together with invited industry experts, to discuss our collective research strengths and look for opportunities for future collaborations.

This summit will showcase a number of research projects of high relevance and impact, and present a plenary student poster session to broadly cover projects on big data management in the local area. Attendees will also hear from French industry about their data management needs, and pursue further discussion at the social event.

All researchers, industry experts, and practitioners are welcomed to participate, as well as all graduate students who work on related research topics in this area.

Practical details

Presentations will be in English.
The event will take place at Telecom ParisTech, 46 rue Barrault in the 13th arrondissement of Paris.

>> Program and free registration

Seminar – Jennifer Widom, Stanford University

Three Favorite Results

Thursday, January 28th 2016 at Telecom ParisTech, 46 rue Barrault, 75013 Paris
Amphi B 312 – 10:00 am. Welcome coffee at 09:30 am.

Conventional wisdom says good things come in threes. As an exercise recently, I reflected on the research I’ve conducted over my career to date and selected my three favorite results, which I will cover in this talk. For each one I’ll explain the context and motivation, the result itself, and why it ranks as one of my favorites. I’ll also make an attempt to decipher what the results have in common. The three results span computer science foundations, system implementation, and user interface questions, and they represent three of my favorite research areas: semistructured data, data streams, and uncertain data.

Jennifer Widom is the Fletcher Jones Professor of Computer Science and Electrical Engineering at Stanford University, and the Senior Associate Dean for Faculty and Academic Affairs in Stanford’s School of Engineering. She served as chair of the Computer Science Department from 2009-2014. Jennifer received her Bachelor’s degree from the Indiana University Jacobs School of Music in 1982 and her Computer Science Ph.D. from Cornell University in 1987. She was a Research Staff Member at the IBM Almaden Research Center before joining the Stanford faculty in 1993. Her research interests span many aspects of nontraditional data management. She is an ACM Fellow and a member of the National Academy of Engineering and the American Academy of Arts & Sciences; she received the ACM-W Athena Lecturer Award in 2015, the ACM SIGMOD Edgar F. Codd Innovations Award in 2007, and a Guggenheim Fellowship in 2000. She has served on a variety of program committees, advisory boards, and editorial boards.

Visit her website

Registration

Big Data et performance, du Graal à la réalité

Retour en images sur la conférence du 2 octobre 2015

Sébastien Pialloux (SNCF), Philippe Poirot (Groupe BPCE), Michel Elmaleh (Deloitte), Alain Monzat (Groupe Rocher)

La transformation numérique n’est pas un effet de mode pour les grandes entreprises française : une conférence organisée par la Chaire « Big Data & Market Insights » de Télécom ParisTech le 2 octobre dernier a permis de voir comment les entreprises abordent cette délicate question, et en quoi le Big Data est moteur dans cette métamorphose.

A l’occasion de la conférence annuelle de la Chaire, les quatre entreprises partenaires, le Groupe BPCE, Deloitte, le Groupe Rocher et la SNCF ont débattu sur l’importance du big data dans leur transformation numérique et sur les étapes clé de la mise en place d’une stratégie data. Le groupe AccorHotels, invité cette année, a également apporté sa vision stratégique.

Cinq intervenants, dont le porteur de la Chaire, le professeur Talel Abdessalem, se sont prêté au jeu des questions-réponses :

  • En quoi le Big Data est un levier de la transformation digitale des entreprises ?
  • Quels sont les principaux points à considérer pour la mise en place d’une stratégie data dans une grande entreprise française ?
  • Le Big Data a-t-il fait ses preuves dans l’amélioration de la performance de votre entreprise ?

Talel Abdessalem
Professeur à Télécom ParisTech, titulaire de la Chaire Big Data & Market Insights

Philippe Poirot
Directeur du développement digital, transformation et qualité du Groupe BPCE

Frédéric Burtz
Directeur Technologie et Innovation de la Direction Digital SNCF
Président du comité de pilotage de la Chaire

Michel Elmaleh
Associé membre du Comité Exécutif et responsable Marketing, Innovation et Offres chez Deloitte France

Vivek Badrinath
Directeur général adjoint en charge du marketing, du digital, de la distribution et des systèmes d’information d’AccorHotels

 

Annual Technion seminar – Applying Big Data

visuel-technion-2015

On Monday, December 14th, will take place the annual seminar of the French Technion Association, with the participation of Telecom ParisTech.

The Technion is the Israel Institute of Technology and the oldest university in Israel. The French Technion Association is aimed at promoting the Technion’s activities in France. Its annual seminar is this year is dedicated to “Applying Big Data: towards data economics“. Four topics will be addressed:

  • e-Health
  • Connected Devices
  • Connected Medias
  • Personnalized Education

Professor Talel Abdessalem, holder of the Big Data & Market Insights Chair, will participate in the #2 session on Connected devices and smart technologies, at 11:15.

This major event in the digital field is placed under the patronage of French President François Hollande. Axelle  Lemaire, State Secretary in charge of the Digital, will introduce the conclusion cocktail.

Practical details

  • All the sessions will be simultaneously translated into English.
  • The event will take place at the Maison de la Chimie, 28 Rue Saint-Dominique, in the 7th arrondissement of Paris.
  • More information on www.technionfrance.org

 

Journée de la Chaire Big Data & Market Insights le 2 octobre 2015

big-data-2-octobre
Logo-Groupe-BPCE-200px Logo-Deloitte-200px   Logo-Groupe-Rocher-200px

A l’occasion de sa journée annuelle, la chaire « Big Data & Market Insights » de Télécom ParisTech propose une session publique sur le thème de la transformation digitale de l’entreprise par le big data.

Si les technologies Big Data sont souvent mises au service de l’entreprise sur des aspects bien précis, tels que le marketing et la gestion de la relation client, la maintenance prédictive ou la détection de fraude, l’expérience montre que le lancement d’un projet fait souvent boule de neige, entraînant d’autres projets sur des aspects parfois bien différents. La stratégie « data » se développe ainsi et trouve sa légitimité à tous les niveaux de l’entreprise, pouvant devenir un levier majeur de sa transformation.

Cette journée est l’occasion pour la Chaire de présenter au public un aperçu de ses travaux de recherche et de partager des retours d’expérience. Notre invité cette année est Vivek Badrinath, directeur général adjoint en charge du marketing, du digital, de la distribution et des systèmes d’information d’AccorHotels. Il présentera sa vision du Big Data et son rôle dans la transformation digitale du groupe Accor.

Suivra une table ronde sur le thème de la transformation digitale de l’entreprise avec la participation de :

  • Frédéric Burtz, Directeur Technologie et Innovation de la Direction Digital SNCF et Président du comité de pilotage de la Chaire
  • Philippe Poirot, Directeur du développement digital, transformation et qualité du Groupe BPCE
  • Michel Elmaleh, Associé membre du Comité Exécutif et responsable Marketing, Innovation et Offres chez Deloitte France
  • Alain Monzat, Responsable Pilotage et Innovation, Direction Digital IT du Groupe Rocher

Programme

  • 16h00 Accueil, rappel des objectifs de la Chaire, présentation de ses travaux, retours d’expérience
  • 16h30 Exposé de Vivek Badrinath, Directeur général adjoint du groupe AccorHotels « Le Big Data, levier de la transformation d’Accor »
  • 17h00 Table ronde « La transformation digitale de l’entreprise » avec le Groupe BPCE, Deloitte, la SNCF et le Groupe Rocher
  • 17h45 Échanges avec le public
  • 18h00 Cocktail

Informations pratiques

Date et heure : le 2 octobre 2015 de 16h à 18h
Lieu : Télécom ParisTech, 46 rue Barrault, 75013 Paris

Inscriptions closes

ParisTech 1st Data Science Game – May-June 2015

DataScienceGame

ENSAE ParisTech and ParisTech, along with Ensta ParisTech and Telecom ParisTech, invite all data science students from Universities all around the world to participate to the 1st edition of the Data Science Game.

By solving a data driven issue, students will be able to enlighten their data science expertise in a both competitive and friendly spirit.

The competition is supported by two major partners : Google Inc., who will provide the scope and material of the competition, and Capgemini, who will provide an amazing setting for the competition in Paris.

Because data are both major input and output in our connected lives, because data science students are the builders of tomorrow and because we believe that they deserve
to be in the limelight, we encourage you to come and join this first international data science event in Paris. Build a team, handle data provided by our partner, try to answer very challenging questions and demonstrate yours skills among data science students from all around the world.

A two Phases competition:

  • An online non-eliminatory phase from mid-May to mid-June 2015
  • A two-days competition in Paris, the 20th and 21st of June 2015

More information, schedule and registration on www.datasciencegame.com

Real-Time Big Data Stream Analytics – Seminar by ​Albert Bifet on April 30th

​Albert Bifet (http://albertbifet.com) will be invited by the Big Data & Market Insights Chair to give a talk on Thursday, April 30th at the National University of Singapore (NUS) School of Computing, Computer Science department.

data-stream

Big Data is a new term used to identify datasets that we cannot manage with current methodologies or data mining software tools due to their large size and complexity. Big Data mining is the capability of extracting useful information from these large datasets or streams of data. New mining techniques are necessary due to the volume, variability, and velocity, of such data. In this talk, we will focus on advanced techniques in Big Data mining in real time using evolving data stream techniques: using a small amount of time and memory resources, an being able to adapt to changes. We will discuss some advanced state-of-the-art methodologies in stream mining based in the use of adaptive size sliding windows. Finally, we will present the MOA software framework with classification, regression, and frequent pattern methods, and the new Apache SAMOA distributed streaming software.

Albert.Bifet.250x250Dr. Albert Bifet is a Senior Researcher at Huawei. He is the author of a book on Adaptive Stream Mining and Pattern Learning and Mining from Evolving Data Streams. His main research interest is in Learning from Data Streams. He published more than 60 articles. He is serving as Industrial Track co-Chair of ECM-PKDD 2015. He is one of the leaders of MOA and Apache SAMOA software environments for implementing algorithms and running experiments for online learning from evolving data streams. He has been Co-Chair of BigMine (2015, 2014, 2013, 2012), and ACM SAC Data Streams Track (2015, 2014, 2013, 2012).

Telecom ParisTech will host the 2015 ASONAM Conference

asonam

The 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) will be held in Paris, from August 25th to 28th. About 300 social network analysis experts are expected at Telecom ParisTech, in the 13th arrondissement.

The study of social networks originated in social and business communities. In recent years, social network research has advanced significantly; the development of sophisticated techniques for Social Network Analysis and Mining (SNAM) has been highly influenced by the online social Web sites, email logs, phone logs and instant messaging systems, which are widely analysed using graph theory and machine learning techniques.

People increasingly perceive the Web as a social medium that fosters interaction among people, sharing of experiences and knowledge, group activities, community formation and evolution. This has led to a rising prominence of SNAM in academia, politics, homeland security and business.

The ASONAM 2015 will primarily provide an interdisciplinary venue that will bring together practitioners and researchers from a variety of SNAM fields to promote collaborations and exchange of ideas and practices. The conference solicits both experimental and theoretical works on social network analysis and mining along with their application to real life situations.

More details on http://asonam.cpsc.ucalgary.ca/2015

Groupe BPCE joins the Big Data & Market Insights Chair

Groupe BPCE is joining Groupe Yves Rocher, Voyages-sncf.com and Deloitte as a partner of Télécom ParisTech’s Big Data & Market Insights Research Chair launched with Télécom Business School in December 2013. The Chair’s inter-disciplinary work is geared to improving companies’ knowledge of their clients, to helping them to personalise products and services and to develop techniques for preventing IT fraud and intrusions.

“We are delighted to welcome Groupe BPCE as a partner of the Big Data & Market Insights Chair. Firstly, like our existing partners, Groupe BPCE recognises the major challenges raised by big data and the interest of joining forces with a specialist research team in order to maximise the understanding and use of this data both for the benefit of the Group and of its clients. And secondly, the fact that our partners come from different sectors of activity enables us to enhance our knowledge of the various business issues and needs linked to big data and to develop effective solutions tailored to these individual issues and needs. Groupe BPCE’s entry into the Chair means we can incorporate the needs of the banking and insurance industry into our research work” underlines Talel Abdessalem, the Chair holder.

Download the Press Release (PDF)

Seminar: Platforms and Applications for “Big and Fast” Data Analytics

On Wednesday, January 14th at 2 pm, the Big Data & Market Insights Chair will welcome Yanlei Diao, Associate Professor at the Department of Computer Science of the University of Massachusetts, Amherst.

The seminar will be held at the LINCS, 23 avenue d’Italie, 75013 Paris (See directions here), in the Salle du Conseil.

Talk overview

Recently there has been a significant interest in building big data systems that can handle not only “big data” but also “fast data” for analytics. Our work is strongly motivated by recent real-world case studies that point to the need for a general, unified data processing framework to support analytical queries with different latency requirements. Towards this goal, our project is designed to transform the popular MapReduce computation model, originally proposed for batch processing, into distributed (near) real-time processing.

In this talk, I start by examining the widely used Hadoop system and presenting a thorough analysis to understand the causes of high latency in Hadoop. I then present a number of necessary architectural changes, as well as new resource configuration and optimization techniques to meet user-specified latency requirements while maximizing throughput.

Experiments using typical workloads in click stream analysis and Twitter feed analysis show that our techniques reduce the latency from tens or hundreds of seconds in Hadoop to sub-second in our system, with 2x-7x increase in throughput. Our system also outperforms state-of-the-art distributed stream systems, Twitter Storm and Spark Streaming, by a wide margin. Finally, I will show some initial results and challenges of supporting big and fast data analytics in the emerging domain of genomics.

Diao-academic-tinyBiography

Yanlei Diao is Associate Professor of Computer Science at the University of Massachusetts Amherst. Her research interests are in information architectures and data management systems, with a focus on big data analytics, data streams, uncertain data management, and RFID and sensor data management. She received her PhD in Computer Science from the University of California, Berkeley in 2005, her M.S. in Computer Science from the Hong Kong University of Science and Technology in 2000, and her B.S. in Computer Science from Fudan University in 1998.

Yanlei Diao was a recipient of the 2013 CRA-W Borg Early Career Award (one female computer scientist selected each year), IBM Scalable Innovation Faculty Award, and NSF Career Award, and she was a finalist of the Microsoft Research New Faculty Award. She spoke at the Distinguished Faculty Lecture Series at the University of Texas at Austin. Her PhD dissertation “Query Processing for Large-Scale XML Message Brokering” won the 2006 ACM-SIGMOD Dissertation Award Honorable Mention.

She is currently Editor-in-Chief of the ACM SIGMOD Record, Associate Editor of ACM TODS, Area Chair of SIGMOD 2015, and member of the SIGMOD Executive Committee and SIGMOD Software Systems Award Committee. In the past, she has served as Associate Editor of PVLDB, organizing committee member of SIGMOD, CIDR, DMSN, and the New England Database Summit, as well as on the program committees of many international conferences and workshops. Her research has been strongly supported by industry with awards from Google, IBM, Cisco, NEC labs, and the Advanced Cybersecurity Center.