COURSE TITLE: Applied Data Analytics Project Course


INSTRUCTORS: Thomas Lee, Dave Rochlin


CLASS WEB PAGE LOCATION:   Course video also available at

MEETING DAY(S)/TIME: Mondays  6:00 – 9:30PM – “Fall B” (starting October 19th)

PREREQUISITE(S):  MBA296-8B or EWMBA296.13 (Data Science and Data Strategy.)    Note: Students with a grad-level course on Data Mining, Machine Learning, or Data Visualization, or relevant background/work experience in data analytics can request consideration for the course by contacting

CLASS FORMAT:  Mixture of lecture, group work/breakouts, and client deliverable meetings.

REQUIRED READINGS Project specific info and course reader.

BASIS FOR FINAL GRADE Project work, team performance, class participation, reflection paper. 

CAREER FIELD:  Consulting, project management, general management, data analytics. 

ABSTRACT OF COURSE'S CONTENT AND OBJECTIVES:  The Applied Data Analytics Project Course offers students a chance to complete a data analytics project for a real client using real data - to develop impactful solutions to the client‘s business challenge.  MBA students from Haas will work on teams with data science focused graduate students from UC Berkeley’s School of Information (“The I-School”), with support from Accenture’s big data group. Together you will take on a data-driven project, focused on solving a challenging issue for one of Accenture’s clients. Your team will take the challenge from data assessment and problem definition through to final client recommendations.  The outcome of your project should be a set of strategic and tactical recommendations to increase the client’s effectiveness. 

Successful analytics projects require managerial discipline, iterative problem solving skills, a solid grounding in the client’s business (whether an internal or external client) effective communications with both team and client, and data analytics tools and techniques  -- including data set analysis, modeling, interpretation, and presentation.  The primary objective of this course -- and of the projects -- is to gain valuable experience in applying the approaches, skills, and tools needed to have an impact on business results through the use of data analytics.


Important notes:


·        The course runs 8 weeks (“Fall B”)

·        The focus is on the project based application of data to drive a client’s business decision making. We will not be teaching the technical foundations or practical software for data analytics:  Students are expected to contribute prior knowledge either in hard data analytics skills or strategic analysis of business problems using data-driven frameworks.   As a result, we require that students have completed the basic data course (Data Science and Data Strategy). Equivalent work experience or prior background may also be accepted.  Please contact the Haas@Work program office for further details

·        For each project, there will be 2-3 formal client workshops/presentations outside of normal Monday evening class hours, in addition to the normal outside work and coordination needed to manage your client, the deliverables, and your team responsibilities.

·        Once assigned a project, you may be required to sign an NDA and IP waiver

·        As is the case with many of the Experiential learning courses,  we need to make early client commitments and share information in advance of the  course. Therefore, please note that there is no add/drop period for this course.


Tom Lee

Thomas Lee teaches and conducts research on information and communication technologies to support innovation and new product development.  Specifically, he develops and applies text and data mining methods for processing user-generated content. His goal is to discover and select opportunities for product and service innovation.  Recent research has mined the text of online customer reviews to induce market structure and mined electronic medical records to redesign emergency department healthcare service processes.

He holds Ph.D. and M.S. degrees from MIT's Engineering Systems Division and B.A. and B.S. degrees in Political Science and Symbolic Systems (Artificial Intelligence) from Stanford University.  He has served as a visiting scientist at the Computer Security Division of the National Institute of Standards and Technology, a research engineer in data security  at the MITRE Corporation, and as a contractor for DynCorp-Meridian supporting the Defense Advanced Research Projects Agency doing research on Internet privacy and security.

At Haas, Tom teaches the core undergraduate course on decision modeling and an MBA elective on Design and Development of Web-based Products and Services. He has also developed and delivered courses on Web innovation and product development for Wharton's San Francisco campus. In addition to being a “club six” instructor at Haas for several years, he is a recipient of an Excellence in Teaching Award and the David W. Hauck Award for Excellence in Undergraduate Teaching, the highest award for undergraduate teaching at The Wharton School of the University of Pennsylvania. 



Dave is an innovation leader and educator with a passion for building teams that can turn ideas into action, solving tough and ambiguous challenges, and developing others to do the same.   He is both a professional faculty member at UC Berkeley’s Haas School of Business, and the Executive Director of the Haas@Work Program. As executive director, Dave manages both the overall program and relationships with program partners, and scopes projects for the program’s courses.  He also developed and helps teach both the Haas@Work Applied Innovation project course and the EW cohort-wide MPAR course. As an instructor, he’s been a multiple “club six” member, and a campus-wide faculty teaching fellow. He also founded and chairs the Berkeley Roundtable on Applied Innovation and Design (BRAID).

Outside of Haas, he is a consultant and social entrepreneur, focused on market-based approaches to social/environmental issues including deforestation, climate change, corporate social responsibility, sustainable business, and ethical globalization.

Prior to coming to Berkeley in 2010, he founded a hybrid social venture called ClimatePath, and was COO of the NGO Fair Trade USA, a 4 time winner of Fast Company/Monitor’s social capital award. He was also professional faculty member in the Executive MBA program at St Mary’s, where he developed and taught the technology and ebusiness strategy course. He is a frequent writer and speaker, and author of the textbook “Hunter or Hunted: Technology, Innovation, and Competitive Strategy” (Thomson/Cengage 2006).

Dave has held key executive VP and C-level positions with several fast growing internet pioneers, including helping to build, grow, and eventually sell businesses to Hollywood Video and Earthlink, and placing companies on both the Deloitte 50 and INC 500 lists. He started his career in brand management and management consulting.

Dave earned his MBA (with distinction) at the JL Kellogg Graduate School of Management at Northwestern, and his B.S. from the Haas School at U.C. Berkeley.