Master of Science Data Analytics & Marketing Manager

Perfect comprehension and communication techniques in English in a broader context than the field of commercial English. Learners may be required to take the TOEIC depending on the host campus.

The aim is to acquire the key skills in terms of budget management and reporting. Particular emphasis will be placed on the budget architecture, with the implementation of summary documents, project management control and its link with budget management, implementation and steering of dashboards. 

This module aims to deepen the skills of learners in computer science to meet the demand of companies for budget or commercial monitoring, project management, personnel management and communication: Excel, Word, Powerpoint, team tools, business software.  It aims to be efficient on office tools, quickly identify and correct errors, customize existing tools or create your own tools. 

This seminar focuses on negotiation in a national and international context.  In particular, the cultural dimension must be taken into account and its impact defined in an international negotiation. National negotiation will focus on the sales process through role play. 

This module allows learners to improve their CV and posture through situations (business game, professional simulation, speaking, etc.); practical and professional workshops (CV, professional social networks, coaching, etc.) as well as business and master class conferences. 

A precise methodology for analyzing customer needs, market structure and competitor dynamics to identify opportunities and threats in the environment is presented.

Through case studies, this module aims to master the tools specific to Internet marketing and communication, addressing mainly: 

• The latest trends in e-commerce (m-commerce/ f-commerce, etc.). 
• Integrating Web 2.0 with marketing strategies. 
• Presentation and mastery of Web analytics tools. 
• Development of a marketing and sales strategy on the various social media.

Know the positioning of the company in the legal environment.  Know the legal constraints surrounding online commerce, and more broadly business on the internet. 

Apply variables in Python programming to store, edit, and retrieve data. Evaluate loop implementations in terms of performance and readability, and create complex loop structures to solve advanced programming problems. Apply Pandas for handling tasks.

Overview of website creation solutions (CMS, PHP development, WYSIWYG tools, etc.).  Presentation of the various analysis tools, website traffic, main indicators: origins, conversion rate, time spent… 

The objective of this course is to give an overview of the Big Data ecosystem and how these technologies can help achieve new goals through new data analysis techniques, offering a fundamental introduction to the main components of all new technologies related to Data and its use cases in various fields.

The R and Python programming languages will be presented and implemented in order to understand their interests from a managerial point of view and thus be able to choose the most relevant analysis methods. 

Data analytics is the exploration, transformation and analysis of data to identify trends and patterns that reveal relevant actionable insights and improve efficiency, helping to optimize decision-making. A modern data analytics strategy enables systems and businesses to act on automated analytics in real time, ensuring immediate and impactful results. 

Data-driven marketing is a process used by marketers to gain insights and identify trends about consumers and their behavior – what they buy, the effectiveness of ads, and how they navigate. 

Apply SQL skills to create, read, update, and delete data in a database, using advanced functions such as joins, subqueries, and aggregation functions. 

Analyze customer data and campaign results to improve marketing strategies, using marketing CRM and automation tools for segmentation, targeting and personalization. 

The objectives of this course are to present an overview of statistical methodologies and data visualization methods in order to be able to describe in a synthetic way and to highlight the information of data sets. The data consist of one or more quantitative variables and/or one or more qualitative variables, measured on the same sample of individuals.  The following topics will be addressed: descriptive statistics, data analysis, classification of individuals or variables, inferential statistics.  The theoretical aspects of the approaches and methodologies presented will be briefly discussed. These statistical approaches and methodologies will be illustrated on practical cases and implemented on the statistical software.

Whether it is an Agile environment or a more traditional structure, set up a fine management of projects and teams. Taking into account the impact of the techniques used and the measurement of the return on investment in the management of such projects. Define and negotiate cost, quality and time objectives. Break down a project and set up concurrent engineering. Organize a project. Define responsibilities and tasks. Lead a project and manage human and financial resources. Support change. Set up a Data Management Platform.

Whether it is an Agile environment or a more traditional structure, set up a fine management of projects and teams. Taking into account the impact of the techniques used and the measurement of the return on investment in the management of such projects. Define and negotiate cost, quality and time objectives. Break down a project and set up concurrent engineering. Organize a project. Define responsibilities and tasks. Lead a project and manage human and financial resources. Support change. Set up a Data Management Platform.

The economic and societal potential of data is enormous: it can enable new products and services based on new technologies, make production more efficient and provide tools to combat societal challenges. Overview of the laws around data. 

From large amounts of data, coming from very diverse sources, deduce regular or potential behaviors, through modern techniques of targeting, segmentation and scoring of e-consumers. Master real-time behavioral analysis to promote multi-channel promotions and influence consumer behavior directly at the point of sale (or on the website). 

Knowledge of the basic tools of data analysis. Explore, describe and interpret data in its multidimensional aspect. Ask the right statistical questions in line with a marketing problem. Perform simple statistical processing to make marketing recommendations. 

Monitor and analyze online data that is most relevant to business activity. Identify the right information at the right time and place, to improve decision-making and optimize organizational performance.  Choose the appropriate tools to understand and capitalize on this new reality. Anticipate changes in markets and customer behavior. Data Mining applied to Customer Intelligence. Implement a Customer Intelligence project in a company. 

Know the various solutions available on the market to optimize the choices of heavy investments generated by Big Data: benchmarking services, knowledge of rates, clauses and sources to keep up to date. Overview of technologies that revolutionize everyday life and customer relations (RFID – Radio Frequency Identification, NFC – Near Field Communication). Know the information transmitted in bulk in order to build new strategies. 

Data mining is defined as a process used to extract usable data from a wider set of raw data. Companies can learn more about their customers and develop more effective strategies related to the various functions of the company, allowing them to leverage resources more optimally and wisely. 

Digital makes it possible to obtain a colossal set of information on individuals. However, without immediate processing, this data quickly becomes obsolete. Know the sources of information available to the Marketer to accurately describe the situation or desires of its customers and prospects in real time. 

Analysis of study data: descriptive, explanatory or predictive analyses of simple or complex treatments. Text analysis and CRM: understand the possibilities offered by text analysis tools to understand data with a high degree of automation.  Improve the quality of the database (homogeneity, qualification, management of inactive contacts, etc.). 

Apply Looker for data mining, reporting, and dashboard creation. Understand the fundamentals of UX and UI design, including design principles and user-centric design. 

Challenges of the algorithm in the value chain of companies. Algorithms now allow machines to learn how to detect patterns or models among millions of data: search for groups of similar elements. Predicting a sequence. Predicting a continuous attribute. 

Determine the value of customers and prospects by developing activity-specific scores based on all the data provided. Develop an acquisition or loyalty strategy according to the defined objectives. Use scoring to better target, avoid SPAM complaints, email unsubscribes, and manage marketing pressure in real time. Beyond targeting, the real added value of data also lies in the predictability of consumer behaviour. Predict future customer behavior. Identify the most profitable, influential. 

Analyze large volumes of data at the right time to evaluate those that come from new sources, such as traffic from social media or clicks made by a prospect on a company’s website, making profile targeting and segmentation as accurate as possible. Know the consumer’s position in real time. Use the right tools to collect and use this information. Study models of analysis and implementation simulations. Analyze the behavior of attendance or purchase of the consumer to optimize decision making. 

Overview of the different types of data. Unstructured or semi-structured data, public or cloud data (online storage), whether it’s social media interactions, videos, Excel files or email attachments. Development and administration of big databases. Knowledge of the tools underlying the major advances in mass data management. Understanding of basic technology architecture to anticipate investments. Hadoop, Map Reduce, NoSQL tools. Consolidate and reconcile data for optimal ROI of marketing actions. 

Master the international regulatory environment of data management, both in the context of collection and sharing. Identify the different approaches to personal data protection. The consent of individuals on their personal data. Integrate the rapid changes in legislation at State level and their impact on the use and strategies of the companies of tomorrow. 

This module allows learners to improve their CV and posture through situations (business game, professional simulation, speaking, etc.); practical and professional workshops (CV, professional social networks, coaching, etc.) as well as business and master class conferences. 

The R and Python programming languages will be presented and implemented in order to understand their interests from a managerial point of view and thus be able to choose the most relevant analysis methods. 

The digital project management module aims to make the student aware of the world of interactive professions, immersing him in the daily issues of an interactive communication agency. 

Now a common practice of Design Thinking methods, learners will be led to manage a challenge to solve a design problem, simplify a process, meet a need. The Design Sprint leads to reflect on the following points: Does my challenge lead to an ultimate impact? Does it consider context and constraints? Does it allow for a variety of potential solutions? Compose and refine proposals to confront customers. 

Introduce a qualitative dimension in addition to the quantitive aspect. This approach will explore crucial aspects such as setting up and analyzing Heatmaps, A/B Testing, creating and refining audiences, setting up Insight capture pages and retargeting. 

Allow learners to know the expectations of the applied research thesis. Formulate a problem, build a literature review, choose the methodology of the study, issue recommendations.