The processing of big data is one of the main challenges of the beginning of the 21st century, with many new issues related to the use, storage and information contained in this data. The birth of big data is estimated to have taken place in 1997. The phenomenal volume of data requires the use of specific data management and analysis tools and has also led to the birth and development of new activities and new professions.
Topic 1 - Big Data and Customer Relationship Management (CRM)
Big data can be very useful, especially in terms of Customer Relationship Management (CRM). By collecting a certain amount of data on its customers, its prospects, on the habits of customers, their geographical origins, their income, etc., a company can constitute an effective database, a real gold mine for its future promotional actions, for example. By knowing its customers better, it can be closer to them, offer them products more suited to their needs or expectations, and bring them greater satisfaction.
Problem: what are the advantages and disadvantages of big data in terms of Customer Relationship Management?
The student can start by defining the concepts of big data and Customer Relationship Management. It will be interesting to develop how big data can be a real asset for the CRM, then to show its limits by indicating that for certain aspects of CRM, big data cannot be sufficient and can even sometimes have deleterious effects. The student can use a concrete example of a company to show the good and bad sides of big data for the CRM.
Topic 2 - Big data and insurers
Insurers and other players in the insurance market (brokers, intermediaries, reinsurers) understood very early on the interest of big data for their sector. Many elements of the insurance contract, and in particular, of course, the pricing is based on elements of risks and large-scale statistics, which are significantly improved and facilitated by the use of big data. Insurers have been using these tools since the early 2000s.
Problem: what is the impact of big data for players in the insurance market?
Here we will discuss the impact and facilitating effects of big data on market players, their facilitation of statistical models based on the laws of large numbers, for example. It will, nevertheless, be necessary for the student to show that big data poses new problems for insurers and that they must now adapt quickly and nimbly to these powerful tools.
Topic 3 - Big data and personal data
The use of big data is often seen by certain players in the economy as the use of private, confidential data and, therefore, as an intrusion into the privacy of their customers or prospects. Big data thus poses new challenges in terms of use, storage and protection of data.
Problem: can we reconcile big data and personal data?
The aim here is to show that big data is a powerful tool on a large scale but that it encounters limits and difficulties linked to its size, in particular, concerning the protection of users' personal data.
Topic 4 - Big data and SMEs
Big data is most often quite obscure and difficult to understand for many companies. For SMEs in particular, it is often a sort of overly complex black box, which some decide to ignore for the moment, not necessarily having the time or the resources required for further research. However, big data can bring a lot to SMEs without always requiring a large IT investment or hiring a team of dedicated engineers.
Problem: how can SMEs use big data quickly and easily?
Big data should be defined here. It will be crucial for the student to show that the use of big data is possible, and even sometimes easy for SMEs, sometimes at ridiculous costs. It will be advisable to insist on the “facilitated” procedures and on the sometimes “degraded” solutions, allowing the use of big data in small structures, even without adequate training and even without recourse to an army of engineers. It will be interesting to show how some SMEs have succeeded in integrating big data by selecting the easiest and most interesting aspects for them.
Topic 5 - Big data and Human Resources
Human Resource is a service in which big data is developing, but its deployment is slower than in certain operational or production functions.
Problem: what are the advantages and disadvantages of big data for a Human Resources department?
It will be interesting for the student to show how big data can be an exciting and very useful lever for Human Resources and to give several examples to illustrate this dissertation. It will then be necessary to indicate all the limits encountered by big data, in particular data protection and privacy, for its wider deployment within HR departments.
Big data is a fascinating subject, which is constantly evolving in the process of regulation, for which the examples of trials, developments, failures and successes are numerous.
Source : Définition : Qu'est-ce que le Big Data ? - LeBigData.fr
