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Show Results For
- All HBS Web
(6,756)
- News (1,202)
- Research (4,389)
- Events (115)
- Multimedia (62)
- Faculty Publications (3,009)
- 21 Jun 2018
- Video
KPMA HBX Live: Cracking the Data Aggregation Problem - Paul Giusti
- April 2002
- Case
In vivo to in vitro to in silico: Coping with Tidal Waves of Data at Biogen
By: Juan Enriquez-Cabot, Gary P. Pisano and Gaye Bok
Biogen is a successful biotech company facing a critical juncture. CEO John Mullen ponders how technological changes introduced into the research function will shape larger corporate decisions. This world in which biotechnology companies operated had changed... View Details
Keywords: Change; Decisions; Product Development; Research and Development; Expansion; Technology; Biotechnology Industry
Enriquez-Cabot, Juan, Gary P. Pisano, and Gaye Bok. "In vivo to in vitro to in silico: Coping with Tidal Waves of Data at Biogen." Harvard Business School Case 602-122, April 2002.
- Spring 2016
- Article
The Billion Prices Project: Using Online Prices for Inflation Measurement and Research
By: Alberto Cavallo and Roberto Rigobon
New data-gathering techniques, often referred to as “Big Data” have the potential to improve statistics and empirical research in economics. In this paper we describe our work with online data at the Billion Prices Project at MIT and discuss key lessons for both... View Details
Keywords: Billion Prices Project; Online Scraped Data; Online Price Index; Economics; Research; Price; Analytics and Data Science
Cavallo, Alberto, and Roberto Rigobon. "The Billion Prices Project: Using Online Prices for Inflation Measurement and Research." Journal of Economic Perspectives 30, no. 2 (Spring 2016): 151–178.
- August 2018 (Revised September 2018)
- Supplement
LendingClub (C): Gradient Boosting & Payoff Matrix
By: Srikant M. Datar and Caitlin N. Bowler
This case builds directly on the LendingClub (A) and (B) cases. In this case students follow Emily Figel as she builds an even more sophisticated model using the gradient boosted tree method to predict, with some probability, whether a borrower would repay or default... View Details
Keywords: Data Analytics; Data Science; Investment; Financing and Loans; Analytics and Data Science; Analysis; Forecasting and Prediction
Datar, Srikant M., and Caitlin N. Bowler. "LendingClub (C): Gradient Boosting & Payoff Matrix." Harvard Business School Supplement 119-022, August 2018. (Revised September 2018.)
- February 1996
- Article
Explaining the Term Structure of Interest Rates: A Panel Data Approach
By: E. S. Mayfield and R. Murphy
Mayfield, E. S., and R. Murphy. "Explaining the Term Structure of Interest Rates: A Panel Data Approach." Journal of Economics and Business 48, no. 1 (February 1996): 11–21.
- January 2016
- Case
Acxiom
By: John Deighton
Acxiom built the market for personal data, yet sales have been flat for a decade during which marketing's appetite for data has exploded. Will the acquisition of a digital data onboarder LiveRamp give marketers what they want from a data broker? View Details
- Web
Research & Data Services for HBS Faculty & Doctoral Students | Baker Library
Research & Data Services for HBS Faculty & Doctoral Students We advance the intellectual ambition of HBS faculty and doctoral students by providing leading- edge services at every stage of the research... View Details
- May 16, 2018
- Other Article
How Companies Can Use the Data They Collect to Further the Public Good
By: Edward L. Glaeser, Hyunjin Kim and Michael Luca
Glaeser, Edward L., Hyunjin Kim, and Michael Luca. "How Companies Can Use the Data They Collect to Further the Public Good." Harvard Business Review (website) (May 16, 2018).
- Article
Detecting Adversarial Attacks via Subset Scanning of Autoencoder Activations and Reconstruction Error
By: Celia Cintas, Skyler Speakman, Victor Akinwande, William Ogallo, Komminist Weldemariam, Srihari Sridharan and Edward McFowland III
Reliably detecting attacks in a given set of inputs is of high practical relevance because of the vulnerability of neural networks to adversarial examples. These altered inputs create a security risk in applications with real-world consequences, such as self-driving... View Details
Keywords: Autoencoder Networks; Pattern Detection; Subset Scanning; Computer Vision; Statistical Methods And Machine Learning; Machine Learning; Deep Learning; Data Mining; Big Data; Large-scale Systems; Mathematical Methods; Analytics and Data Science
Cintas, Celia, Skyler Speakman, Victor Akinwande, William Ogallo, Komminist Weldemariam, Srihari Sridharan, and Edward McFowland III. "Detecting Adversarial Attacks via Subset Scanning of Autoencoder Activations and Reconstruction Error." Proceedings of the International Joint Conference on Artificial Intelligence 29th (2020).
- March 2022 (Revised January 2025)
- Technical Note
Prediction & Machine Learning
This note provides an introduction to machine learning for an introductory data science course. The note begins with a description of supervised, unsupervised, and reinforcement learning. Then, the note provides a brief explanation of the difference between traditional... View Details
Keywords: Machine Learning; Data Science; Learning; Analytics and Data Science; Performance Evaluation; AI and Machine Learning
Bojinov, Iavor I., Michael Parzen, and Paul Hamilton. "Prediction & Machine Learning." Harvard Business School Technical Note 622-101, March 2022. (Revised January 2025.)
- Article
DEA Model with Shared Resources and Efficiency Decomposition
By: Yao Chen, Juan Du, H. David Sherman and Joe Zhu
Data envelopment analysis (DEA) has proved to be an excellent approach for measuring performance of decision making units (DMUs) that use multiple inputs to generate multiple outputs. In many real world scenarios, DMUs have a two-stage network process with shared input... View Details
Chen, Yao, Juan Du, H. David Sherman, and Joe Zhu. "DEA Model with Shared Resources and Efficiency Decomposition." European Journal of Operational Research 207, no. 1 (November 2010): 339–349.
- 2015
- Chapter
Investigating Population Dynamics of the KUMBH MELA through the Lens of Cell Phone Data
By: Jukka-Pekka Onnela and Tarun Khanna
Onnela, Jukka-Pekka, and Tarun Khanna. "Investigating Population Dynamics of the KUMBH MELA through the Lens of Cell Phone Data." In Kumbh Mela, January 2013: Mapping the Ephemeral Mega City, edited by Rahul Mehrotra and Felipe Vera, 202–218. Ostfildern, Germany: Hatje Cantz Verlag, 2015.
- 09 Dec 2015
- Research Event
How Do You Predict Demand and Set Prices For Products Never Sold Before?
predict demand and set prices to maximize revenue of products that have no historical sales data? To that end, they set out to develop a pricing decision support tool that... View Details
- Fall 2012
- Article
How 'Big Data' Is Different
Many people today in the information technology world and in corporate boardrooms are talking about "big data." Many believe that, for companies that get it right, big data will be able to unleash new organizational capabilities and value. But what does the term "big... View Details
Keywords: Big Data; Analytics; Mathematical Methods; Information Management; Information Technology Industry
Davenport, Thomas H., Paul Barth, and Randy Bean. "How 'Big Data' Is Different." MIT Sloan Management Review 54, no. 1 (Fall 2012).
- Research Summary
Finding their voice: Time and the conditions that elevate participation of lower-power members in teams [Dissertation, data analysis and writing]
This dissertation paper develops theory about how gaining voice and “speaking up” by low-power members is not sufficient to create changes that benefit them and their low-power colleagues; that, in fact, speaking up when the team is not ready to listen results in... View Details