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Volver a Capstone: Create Value from Open Data

Capstone: Create Value from Open Data, ESSEC Business School

3.5
22 calificaciones
7 revisiones

Acerca de este Curso

The Capstone project is an individual assignment. Participants decide the theme they want to explore and define the issue they want to solve. Their “playing field” should provide data from various sectors (such as farming and nutrition, culture, economy and employment, Education & Research, International & Europe, Housing, Sustainable, Development & Energies, Health & Social, Society, Territories & Transport). Participants are encouraged to mix the different fields and leverage the existing information with other (properly sourced) open data sets. Deliverable 1 is the preliminary preparation and problem qualification step. The objectives is to define the what, why & how. What issue do we want to solve? Why does it promise value for public authorities, companies, citizens? How do we want to explore the provided data? For Deliverable 2, the participant needs to present the intermediary outputs and adjustments to the analysis framework. The objectives is to confirm the how and the relevancy of the first results. Finally, with Deliverable 3, the participant needs to present the final outputs and the value case. The objective is to confirm the why. Why will it create value for public authorities, companies, and citizens. Assessment and grading: the participants will present their results to their peers on a regular basis. An evaluation framework will be provided for the participants to assess the quality of each other’s deliverables....

Principales revisiones

por EU

Jul 11, 2016

This was hard, but I was happy and the end and have a good grade. Thank to my classmates , thank to ESSEC

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7 revisiones

por Wolf-Dietrich Zabka

Sep 03, 2018

The initial setting is attractive. Unfortunately, the second half is repetitive. Further, grading scale appears to be somewhat inappropriate: If your topic is not frequently in the news, you have only 2 points left to lose. If the expected revenue is not in the range of billions you are already very close to failing the project. The grading scale is something that can be improved very easily. Further, working with more than one dataset should be encouraged, which would invite to explore more ways of data analysis and visualization.

por Nadia Vazquez Novoa

Aug 02, 2017

I think the contents of this specialization were interesting, but it was very difficult to reach a compromise between the time that was supposed to be dedicated to the peer-review assignments and the expectations that many participants had on the deliveries. Even if all tasks were supposed to be done in around 2 hours, it is definitely not possible to satisfy your classmates' expectations if you only invest 2 hours... it will be even difficult to satisfy them if you invest less than 8-12 hours per assignment. This might be due to the differences in backgrounds of the participants and also to the examples provided in the courses (which were clearly not made in 2 hours).

por Vishal Vilas Mohite

Jun 08, 2017

The Course provided valuable insights in Strategy, Marketing. Introduced me to R and its vast capacity to analyse data. Accenture cases were helpful. And it has definitely improved my presentation skills.

por Tim Scongack

Feb 12, 2017

Great course!

por William Florez

Oct 11, 2016

The worse course ever

por ELINGUI Pascal Uriel

Jul 11, 2016

This was hard, but I was happy and the end and have a good grade. Thank to my classmates , thank to ESSEC

por Wendy B.

Apr 12, 2016

I would not recommend this specialization to anyone. The first assignment is just a first review of the final project, but it is almost impossible to pass, because the questions are not organized in a manner of constructive feedback.