Lecture

Design for Sustainability I

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In course

HUM-397: Design for sustainability I

This course explores and practices some of the fundamental tools of designing for sustainability with a focus on the sustainability, desirability, and economic viability of solutions. ...

Description

This lecture introduces the concept of sustainability, focusing on the importance of sustainable projects and their impact on society. Students discuss key words related to sustainability, analyze projects based on SDGs, and distinguish between well-defined and ill-defined problems.

Instructor

Marc Laperrouza

Marc is a scientist and lecturer at the Swiss Federal Institute of Technology (EPFL) and at the University of Lausanne (HEC). Marc obtained his PhD on China's telecommunication reforms from the London School of Economics. He holds a Master Degree in International Management (HEC, 1997) and an undergraduate degree in Business Management from the University of Lausanne (1993). He studied Chinese Language and Economics for two years at Fudan University, Shanghai (1993-1995) and one semester at the Richard Ivey School of Business, University of Western Ontario, Canada (1996). Marc was previously senior research associate at EPFL working on the coherence between institutional and technological governance in infrastructures (2007-2011). In a former life, he worked as a research analyst at Swiss Re and at McKinseys Business Technology Office. He served as deputy director and senior advisor to the Evian Group, a think tank based at IMD (Lausanne, Switzerland) and lectures regularly on China and emerging markets at undergraduate, graduate and executive levels. Marc contributes frequently to Swiss media. He is the Founder and President of the bonopro association and recipient of the Swiss Re Civilian Service Prize (2011).

Official source

Related concepts (26)

Data

In common usage and statistics, data (USˈdætə; UKˈdeɪtə) is a collection of discrete or continuous values that convey information, describing the quantity, quality, fact, statistics, other basic units of meaning, or simply sequences of symbols that may be further interpreted formally. A datum is an individual value in a collection of data. Data is usually organized into structures such as tables that provide additional context and meaning, and which may themselves be used as data in larger structures.

Data analysis

Data analysis is the process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, and is used in different business, science, and social science domains. In today's business world, data analysis plays a role in making decisions more scientific and helping businesses operate more effectively.

Big data

Big data primarily refers to data sets that are too large or complex to be dealt with by traditional data-processing application software. Data with many entries (rows) offer greater statistical power, while data with higher complexity (more attributes or columns) may lead to a higher false discovery rate. Though used sometimes loosely partly because of a lack of formal definition, the interpretation that seems to best describe big data is the one associated with a large body of information that we could not comprehend when used only in smaller amounts.

Data warehouse

In computing, a data warehouse (DW or DWH), also known as an enterprise data warehouse (EDW), is a system used for reporting and data analysis and is considered a core component of business intelligence. Data warehouses are central repositories of integrated data from one or more disparate sources. They store current and historical data in one single place that are used for creating analytical reports for workers throughout the enterprise. This is beneficial for companies as it enables them to interrogate and draw insights from their data and make decisions.

Data mining

Data mining is the process of extracting and discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems. Data mining is an interdisciplinary subfield of computer science and statistics with an overall goal of extracting information (with intelligent methods) from a data set and transforming the information into a comprehensible structure for further use. Data mining is the analysis step of the "knowledge discovery in databases" process, or KDD.

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