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  • All HBS Web  (1,564)
    • News  (204)
    • Research  (1,137)
    • Events  (16)
    • Multimedia  (1)
  • Faculty Publications  (665)
← Page 8 of 1,564 Results →
  • March 2019
  • Case

Wattpad

By: John Deighton and Leora Kornfeld
How to run a platform to match four million writers of stories to 75 million readers? Use data science. Make money by doing deals with television and filmmakers and book publishers. The case describes the challenges of matching readers to stories and of helping writers... View Details
Keywords: Platform Businesses; Creative Industries; Publishing; Data Science; Machine Learning; Collaborative Filtering; Women And Leadership; Managing Data Scientists; Big Data; Recommender Systems; Digital Platforms; Information Technology; Intellectual Property; Analytics and Data Science; Entertainment and Recreation Industry; Entertainment and Recreation Industry; Canada; United States; Philippines; Viet Nam; Turkey; Indonesia; Brazil
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Deighton, John, and Leora Kornfeld. "Wattpad." Harvard Business School Case 919-413, March 2019.
  • February 2013
  • Case

Recorded Future: Analyzing Internet Ideas About What Comes Next

Recorded Future is a "big data" startup company that uses Internet data to make predictions about events, people, and entities. The company primarily serves government intelligence agencies, but has some private sector clients and is considering taking on more. The... View Details
Keywords: Big Data; Analytics; Internet; Analytics and Data Science; Internet and the Web; Entrepreneurship; Forecasting and Prediction; Business Startups; Information Technology Industry
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Davenport, Thomas H. "Recorded Future: Analyzing Internet Ideas About What Comes Next." Harvard Business School Case 613-083, February 2013.
  • February 2021
  • Tutorial

Getting Started in RStudio Cloud

By: Chiara Farronato and Caleb Kwon
This video provides an introduction to the free programming language R using an online cloud version of RStudio, which is the most popular editor and interface for writing and executing R code. The video begins by providing a brief background of R and RStudio and... View Details
Keywords: Data Analysis; Data Analytics; Experiment; Experimental Design; Analytics and Data Science; Analysis; Applications and Software
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Farronato, Chiara, and Caleb Kwon. Getting Started in RStudio Cloud. Harvard Business School Tutorial 621-708, February 2021.
  • December 2021
  • Case

Burning Glass Technologies: From Data to Product

By: Suraj Srinivasan and Amy Klopfenstein
In May 2021, Matt Sigelman, CEO of Burning Glass Technologies, a company that provided labor market analytics for a variety of markets, navigates his company’s transition from data company to product company. Burning Glass originated as a service that used artificial... View Details
Keywords: Information Technology; Applications and Software; Digital Platforms; Internet and the Web; Strategy; Expansion; Business Strategy; Labor; Employment; Human Capital; Jobs and Positions; Job Design and Levels; Job Search; Human Resources; Selection and Staffing; Recruitment; Employees; Retention; Competency and Skills; Experience and Expertise; Talent and Talent Management; Analytics and Data Science; Business Model; Technology Industry; North and Central America; United States
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Srinivasan, Suraj, and Amy Klopfenstein. "Burning Glass Technologies: From Data to Product." Harvard Business School Case 122-015, December 2021.
  • June 2023
  • Simulation

Artea Dashboard and Targeting Policy Evaluation

By: Ayelet Israeli and Eva Ascarza
Companies deploy A/B experiments to gain valuable insights about their customers in order to answer strategic business problems. In marketing, A/B tests are often used to evaluate marketing interventions intended to generate incremental outcomes for the firm. The Artea... View Details
Keywords: Algorithm Bias; Algorithmic Data; Race And Ethnicity; Experimentation; Promotion; Marketing And Society; Big Data; Privacy; Data-driven Management; Data Analysis; Data Analytics; E-Commerce Strategy; Discrimination; Targeted Advertising; Targeted Policies; Pricing Algorithms; A/B Testing; Ethical Decision Making; Customer Base Analysis; Customer Heterogeneity; Coupons; Marketing; Race; Gender; Diversity; Customer Relationship Management; Marketing Communications; Advertising; Decision Making; Ethics; E-commerce; Analytics and Data Science; Apparel and Accessories Industry; Apparel and Accessories Industry; United States
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Israeli, Ayelet, and Eva Ascarza. "Artea Dashboard and Targeting Policy Evaluation." Harvard Business School Simulation 523-707, June 2023.
  • January 2020
  • Case

Banorte Móvil: Data-Driven Mobile Growth

By: Ayelet Israeli, Carla Larangeira and Mariana Cal
In mid-2019, Carlos Hank was deliberating over the results for Banorte Móvil—the mobile application for Banorte, Mexico’s most profitable and second-largest financial institution. Hank, who had been appointed as Banorte´s Chairman of the Board in January 2015, had... View Details
Keywords: Data Analytics; Customer Lifetime Value; Financial Institutions; Mobile and Wireless Technology; Growth and Development Strategy; Customers; Technology Adoption; Communication Strategy; Banking Industry; Mexico; Latin America
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Israeli, Ayelet, Carla Larangeira, and Mariana Cal. "Banorte Móvil: Data-Driven Mobile Growth." Harvard Business School Case 520-068, January 2020.
  • March 2022 (Revised January 2025)
  • Technical Note

Linear Regression

By: Iavor I. Bojinov, Michael Parzen and Paul Hamilton
This note provides an overview of linear regression for an introductory data science course. It begins with a discussion of correlation, and explains why correlation does not necessarily imply causation. The note then describes the method of least squares, and how to... View Details
Keywords: Data Science; Linear Regression; Mathematical Modeling; Mathematical Methods; Analytics and Data Science
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Bojinov, Iavor I., Michael Parzen, and Paul Hamilton. "Linear Regression." Harvard Business School Technical Note 622-100, March 2022. (Revised January 2025.)
  • January 2018
  • Article

Big Data and Big Cities: The Promises and Limitations of Improved Measures of Urban Life

By: Edward L. Glaeser, Scott Duke Kominers, Michael Luca and Nikhil Naik
New, "big" data sources allow measurement of city characteristics and outcome variables at higher frequencies and finer geographic scales than ever before. However, big data will not solve large urban social science questions on its own. Big data has the most value for... View Details
Keywords: Analytics and Data Science; Urban Scope; City
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Glaeser, Edward L., Scott Duke Kominers, Michael Luca, and Nikhil Naik. "Big Data and Big Cities: The Promises and Limitations of Improved Measures of Urban Life." Economic Inquiry 56, no. 1 (January 2018): 114–137.
  • April 2022
  • Teaching Note

Banorte Móvil: Data-Driven Mobile Growth

By: Ayelet Israeli and Carla Larangeira
In mid-2019, Carlos Hank was deliberating over the results for Banorte Móvil—the mobile application for Banorte, Mexico’s most profitable and second-largest financial institution. Hank, who had been appointed as Banorte´s Chairman of the Board in January 2015, had... View Details
Keywords: Data Analytics; Customer Lifetime Value; Financial Institutions; Mobile and Wireless Technology; Growth and Development Strategy; Customers; Technology Adoption; Communication Strategy; Banking Industry; Mexico; Latin America
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Israeli, Ayelet, and Carla Larangeira. "Banorte Móvil: Data-Driven Mobile Growth." Harvard Business School Teaching Note 522-095, April 2022.
  • June 2022 (Revised January 2025)
  • Technical Note

Causal Inference

By: Iavor I Bojinov, Michael Parzen and Paul Hamilton
This note provides an overview of causal inference for an introductory data science course. First, the note discusses observational studies and confounding variables. Next the note describes how randomized experiments can be used to account for the effect of... View Details
Keywords: Causal Inference; Causality; Experiment; Experimental Design; Data Science; Analytics and Data Science
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Bojinov, Iavor I., Michael Parzen, and Paul Hamilton. "Causal Inference." Harvard Business School Technical Note 622-111, June 2022. (Revised January 2025.)
  • September 2024
  • Exercise

Assessing the Value of Unifying and De-Duplicating Customer Data

By: Elie Ofek and Hema Yoganarasimhan
This exercise provides an opportunity for students to gain hands on experience with assessing the value of unifying various customer databases that a firm may have (e.g., across the different brands it markets) and of properly identifying customers to avoid duplication... View Details
Keywords: Customer Relationship Management; Measurement and Metrics; Analytics and Data Science; Value
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Ofek, Elie, and Hema Yoganarasimhan. "Assessing the Value of Unifying and De-Duplicating Customer Data." Harvard Business School Exercise 525-023, September 2024.
  • August 2022
  • Supplement

Zalora: Data-Driven Pricing Recommendations

By: Ayelet Israeli
This exercise can be used in conjunction with the main case "Zalora: Data-Driven Pricing" to facilitate class discussion without requiring data analysis from the students. Instead, the exercise presents reports that were created by the data science team to answer the... View Details
Keywords: Pricing; Pricing Algorithms; Dynamic Pricing; Ecommerce; Pricing Strategy; Pricing And Revenue Management; Apparel; Singapore; Startup; Demand Estimation; Data Analysis; Data Analytics; Exercise; Price; Internet and the Web; Apparel and Accessories Industry; Apparel and Accessories Industry; Apparel and Accessories Industry; Singapore
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Israeli, Ayelet. "Zalora: Data-Driven Pricing Recommendations." Harvard Business School Supplement 523-032, August 2022.
  • Research Summary

Overview

By: Ayelet Israeli
Professor Israeli utilizes econometric methods and field experiments to study data driven decision making in marketing context. Her research focuses on data-driven marketing, with an emphasis on how businesses can leverage their own data, customer data, and market data... View Details
Keywords: Channel Management; Pricing; Pricing Policies; Online Marketing; E-commerce; Analytics; Econometrics; Field Experiments; Data Analytics; Artificial Intelligence; Value Of Data
  • August 2015 (Revised January 2017)
  • Technical Note

From Correlation to Causation

By: Feng Zhu and Karim R. Lakhani
To make sound business decisions, managers must be comfortable with the concepts of correlation and causation. This background note provides an overview of correlation and causation using examples and explains why the former does not imply the latter. It also describes... View Details
Keywords: Statistics; Regression; Data Analytics; Decisions; Forecasting and Prediction; Judgments
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Zhu, Feng, and Karim R. Lakhani. "From Correlation to Causation." Harvard Business School Technical Note 616-009, August 2015. (Revised January 2017.)
  • October 2022
  • Supplement

Single Earth: Science White Paper Supplement

By: Rembrand Koning and Emer Moloney
Science White Paper prepared by Single.Earth to give an overview of the models and solutions it has developed. View Details
Keywords: Business Startups; Entrepreneurship; Climate Change; Environmental Sustainability; Green Technology; Natural Resources; Pollution; Analytics and Data Science; Marketing; Product Marketing; Product Launch; Product Positioning; Markets; Market Timing; Strategy; Green Technology Industry; Estonia
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Koning, Rembrand, and Emer Moloney. "Single Earth: Science White Paper Supplement." Harvard Business School Supplement 723-389, October 2022.
  • May 8, 2020
  • Article

Which Covid-19 Data Can You Trust?

By: Satchit Balsari, Caroline Buckee and Tarun Khanna
The COVID-19 pandemic has produced a tidal wave of data, but how much of it is any good? And as a layperson, how can you sort the good from the bad? The authors suggest a few strategies for dividing the useful data from the misleading: Beware of data that’s too broad... View Details
Keywords: COVID-19 Pandemic; Health Pandemics; Analytics and Data Science
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Balsari, Satchit, Caroline Buckee, and Tarun Khanna. "Which Covid-19 Data Can You Trust?" Harvard Business Review (website) (May 8, 2020).
  • May 2018
  • Article

Nowcasting Gentrification: Using Yelp Data to Quantify Neighborhood Change

By: Edward L. Glaeser, Hyunjin Kim and Michael Luca
Data from digital platforms have the potential to improve our understanding of gentrification and enable new measures of how neighborhoods change in close to real time. Combining data on businesses from Yelp with data on gentrification from the Census, Federal Housing... View Details
Keywords: Forecasting Models; Simulation Methods; Regional Economic Activity: Growth, Development, Environmental Issues, And Changes; Geographic Location; Local Range; Transition; Analytics and Data Science; Measurement and Metrics; Economic Growth; Forecasting and Prediction
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Glaeser, Edward L., Hyunjin Kim, and Michael Luca. "Nowcasting Gentrification: Using Yelp Data to Quantify Neighborhood Change." AEA Papers and Proceedings 108 (May 2018): 77–82.
  • July 2022
  • Case

Operation Overlord

By: Boris Groysberg, Greg Goullet, Katherine Connolly Baden and Sarah L. Abbott
On June 6, 1944, nearly 5,000 ships, 11,000 planes, and 160,000 infantrymen under an Allied joint-command of American, British, and Canadian leaders were sent across the English Channel, with hopes of re-establishing a foothold in Nazi-occupied France. Known as D-Day,... View Details
Keywords: Execution; Data Analytics; Leadership; Planning; Operations; Crisis Management; War; Organizational Structure; Decision Choices and Conditions; Information Management; France; England
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Groysberg, Boris, Greg Goullet, Katherine Connolly Baden, and Sarah L. Abbott. "Operation Overlord." Harvard Business School Case 422-098, July 2022.
  • August 2024
  • Technical Note

Introduction to Data Analysis in Python

By: Michael Parzen and Jo Ellery
This note introduces Python as a tool for data science, including the Pandas library for data analysis. View Details
Keywords: Analytics and Data Science
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Parzen, Michael, and Jo Ellery. "Introduction to Data Analysis in Python." Harvard Business School Technical Note 625-016, August 2024.
  • October 2017
  • Case

Quantopian: A New Model for Active Management

By: Sara Fleiss, Adi Sunderam, Luis M. Viceira and Caitlin Carmichael
Keywords: Big Data; Hedge Fund; Crowdsourcing; Investment Fund; Quantitative Hedge Fun; Algorithmic Data; Analytics and Data Science
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Fleiss, Sara, Adi Sunderam, Luis M. Viceira, and Caitlin Carmichael. "Quantopian: A New Model for Active Management." Harvard Business School Case 218-046, October 2017.
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