Télécom ParisTech

Big Data Economics Conference highlights

Big Data Economics : Patrick DuvautBig Data Economics : Renaud Di Francesco, Pierre-Jean Benghozi et Patrick Duvaut
Big Data Economics : Pierre-Jean BenghoziBig Data Economics : Pierre-Jean BenghoziBig Data Economics : Pierre-Jean BenghoziBig Data Economics : Renaud Di Francesco

Big data economics, workshop at Telecom ParisTech, on Jan. 12, 2015

Presentation by Renaud Di Francesco, PhD, followed by a Speech by Pierre-Jean Benghozi

1. Presentation summary

The scope of big data is broader than business intelligence, and extending towards:

  • real world to digital, analytics AND decision, feedback to real world
  • real time

This implies a change in needed technology portfolio, beyond NoSQL and search technologies, with other technologies determining success:

  • signal processing
  • maximum likelihood decision methods
  • optimal control
  • real time system engineering

The digital economy relies on three pillars, two of which have identified pricing schemes and economic mechanisms:

  • software
  • network
  • however, the third one, data, does not always have recognised value, and economic mechanisms.

For instance, what is the price of an electrocardiogram as usable data? What is the price of my geographic position?

Nevertheless in some sectors and categories, data can have pricing schemes and economic mechanisms:

  • content (e.g. movie) industry
  • news
  • loyalty schemes
  • etc.

Starting from these chartered territories of big data, one can start considering adapted economic schemes for new data categories, which are not yet priced and covered by economic schemes. The software licensing scheme offers a starting framework for data contracts, which cover rights on data.

The enforcement of rights is helped by Digital Right Management systems granting authorised access to the data. The target for a data economy to work efficiently is the development of data market places, where data collectors, data owners, data users, and data processors, meet as data offer has to meet data demand.

The raw material or commodity market places established for physical goods give a reference framework from which data market places can be derived. Moreover, in some categories, digital data market places are already in operation. For instance Getty Images buys and sells pictures, which are a special case of data.

2. Speech summary

The concept of data covers a wide range of items:

punctual and static information or dynamic traces, digital or textual or image information, geolocation. In Big data Economics, the value may lie in the data or the processing algorithms. In one case, the data value is almost zero and the processing capacity creates the value (Google). In other cases, treatment tools are commonplace and the value lies in the scarcity of databases (cf. eHealth).

The data does not have an absolute value per se. It varies according the business models and over time. It does in the example of the exploitation windows of a movie on the multiple platforms: cinema, theatre, TV, internet services.

The market of Big data is not confined to B2C. B2B is an important an important field of application as well.

Market places for trading data are essential for the data economy to grow and the setting of dominant players. Their control is a competitive strategic resource. The control and the validation of data are a key issue when the value of data intents to inflating artificially the databases (cf. the market for "friends" and "followers" on social networks).

For whatever type of data linked directly or indirectly to individuals, managing the privacy protection of the individual is a prerequisite.

One may discuss the actual freshness of the concept of Big Data (change of scale in the volume and nature of the data, new methods, new uses ?). Many applications are not very different from the old marketing techniques.

3. Q&A summary

Industrial data?

Currently industrial data are part of closed systems, and the suppliers and users of such systems are very protective about sharing with third parties. However, some intents are being made.

Luxury data?

Some data can be seen as Giffen good, where high price is expected and desired as part of the value proposition (luxury car, etc). Some "gem" data exist. High value financial information is part of this category. Beyond any open economy, State Security data has a somewhat comparable exclusive status.

Key sectors?

Business intelligence is a very active market for big data solutions already. Health Care and Care for the ageing population is another area, where big data solutions could support the people in care and support the carers, especially in the Ambient Assisted Living framework.

Data management?

This determines the possibility of economic exploitation of data. In particular, ensuring that data owners keep control of multiple, possibly cascaded use.

Open Data?

Not to be forgotten. Success is not guaranteed, and data need care: make data available in full compliance with regulation, ensuring quality and veracity.

4. About Telecom ParisTech and its Big Data Post-Master’s degree curriculum

This programme addresses a unique and comprehensive set of topics and matching skills for wide-scope big data in any industry or sector. To know more about the Big Data Post-Master's Degree.