Специализация Business Analytics

Начался мар 27

Специализация Business Analytics

Make Data-Driven Business Decisions

Achieve fluency in business data strategies in four discipline-specific courses.

Об этой специализации

This Specialization provides an introduction to big data analytics for all business professionals, including those with no prior analytics experience. You’ll learn how data analysts describe, predict, and inform business decisions in the specific areas of marketing, human resources, finance, and operations, and you’ll develop basic data literacy and an analytic mindset that will help you make strategic decisions based on data. In the final Capstone Project, you’ll apply your skills to interpret a real-world data set and make appropriate business strategy recommendations.


5 courses

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Beginner Specialization.
No prior experience required.
  1. 1-Й КУРС

    Customer Analytics

    Текущая сессия: мар 27–май 8.
    4 weeks of study, 5-6 hours/week
    English, Spanish, Chinese (Simplified)

    О курсе

    Data about our browsing and buying patterns are everywhere. From credit card transactions and online shopping carts, to customer loyalty programs and user-generated ratings/reviews, there is a staggering amount of data that can be used to describe our past buying behaviors, predict future ones, and prescribe new ways to influence future purchasing decisions. In this course, four of Wharton’s top marketing professors will provide an overview of key areas of customer analytics: descriptive analytics, predictive analytics, prescriptive analytics, and their application to real-world business practices including Amazon, Google, and Starbucks to name a few. This course provides an overview of the field of analytics so that you can make informed business decisions. It is an introduction to the theory of customer analytics, and is not intended to prepare learners to perform customer analytics. Course Learning Outcomes: After completing the course learners will be able to... Describe the major methods of customer data collection used by companies and understand how this data can inform business decisions Describe the main tools used to predict customer behavior and identify the appropriate uses for each tool Communicate key ideas about customer analytics and how the field informs business decisions Communicate the history of customer analytics and latest best practices at top firms
  2. 2-Й КУРС

    Operations Analytics

    Предстоящая сессия: апр 3–май 8.
    Продолжительность курса - 4 недели, 2-3 часа в неделю.
    English, Chinese (Simplified)

    О курсе

    This course is designed to impact the way you think about transforming data into better decisions. Recent extraordinary improvements in data-collecting technologies have changed the way firms make informed and effective business decisions. The course on operations analytics, taught by three of Wharton’s leading experts, focuses on how the data can be used to profitably match supply with demand in various business settings. In this course, you will learn how to model future demand uncertainties, how to predict the outcomes of competing policy choices and how to choose the best course of action in the face of risk. The course will introduce frameworks and ideas that provide insights into a spectrum of real-world business challenges, will teach you methods and software available for tackling these challenges quantitatively as well as the issues involved in gathering the relevant data.
  3. 3-Й КУРС

    People Analytics

    Текущая сессия: мар 27–май 1.
    Продолжительность курса - 4 недели, 1-2 часа в неделю.

    О курсе

    People analytics is a data-driven approach to managing people at work. For the first time in history, business leaders can make decisions about their people based on deep analysis of data rather than the traditional methods of personal relationships, decision making based on experience, and risk avoidance. In this brand new course, three of Wharton’s top professors, all pioneers in the field of people analytics, will explore the state-of-the-art techniques used to recruit and retain great people, and demonstrate how these techniques are used at cutting-edge companies. They’ll explain how data and sophisticated analysis is brought to bear on people-related issues, such as recruiting, performance evaluation, leadership, hiring and promotion, job design, compensation, and collaboration. By the end of this course, you’ll understand how and when hard data is used to make soft-skill decisions about hiring and talent development, so that you can position yourself as a strategic partner in your company’s talent management decisions. Organizations flourish when the people who work in them flourish. Analytics can help make both happen. This course in People Analytics is designed to help you flourish in your career, too.
  4. 4-Й КУРС

    Аналитика Учета

    Предстоящая сессия: апр 3–май 8.
    4 недели, 3 -5 часов в неделю
    English, Mongolian

    О курсе

    Аналитика Учета исследует как данные финансовой отчетности и нефинансовые показатели могут быть связаны с финансовыми показателями. В этом курсе, созданном известными профессорами бухгалтерского учета школы Уортон, Вы получите знания о том, как данные используются для оценки того, что движет финансовыми показателями и как предсказывать будущие финансовые сценарии. В то время как многие бухгалтерские и финансовые организации предоставляют данные, Аналитика Учета раскрывает именно ту полезную информацию, которая содержится в данных, и этот курс будет исследовать многие области, в которых данные учета обеспечивают лучшее понимание других областей бизнеса, включая прогноз поведения потребителей, корпоративную стратегию, управление рисками, оптимизацию и так далее. К концу данного курса Вы будете понимать, как финансовые и нефинансовые данные взаимодействуют для прогноза событий, оптимизации операций и определяют стратегию. Этот курс создан с целью помочь Вам принимать более качественные бизнес-решения с учетом увеличивающейся роли Аналитики Учета так, что Вы сможете применять то, что выучили для принятия решений в Вашем собственном бизнесе и создания стратегии использования финансовых данных.
  5. 5-Й КУРС

    Business Analytics Capstone

    Предстоящая сессия: июнь 12–июль 17.
    4 weeks of study, 4-5 hours/week

    О дипломном проекте

    The Business Analytics Capstone Project gives you the opportunity to apply what you've learned about how to make data-driven decisions to a real business challenge faced by global technology companies like Yahoo, Google, and Facebook. At the end of this Capstone, you'll be able to ask the right questions of the data, and know how to use data effectively to address business challenges of your own. You’ll understand how cutting-edge businesses use data to optimize marketing, maximize revenue, make operations efficient, and make hiring and management decisions so that you can apply these strategies to your own company or business. Designed with Yahoo to give you invaluable experience in evaluating and creating data-driven decisions, the Business Analytics Capstone Project provides the chance for you to devise a plan of action for optimizing data itself to provide key insights and analysis, and to describe the interaction between key financial and non-financial indicators. Once you complete your analysis, you'll be better prepared to make better data-driven business decisions of your own.


  • Пенсильванский университет

    The Wharton School of the University of Pennsylvania is recognized globally for intellectual leadership and ongoing innovation across every major discipline of business education.

    The University of Pennsylvania (commonly referred to as Penn) is a private university, located in Philadelphia, Pennsylvania, United States. A member of the Ivy League, Penn is the fourth-oldest institution of higher education in the United States, and considers itself to be the first university in the United States with both undergraduate and graduate studies.

  • Noah Gans

    Noah Gans

    Anheuser-Busch Professor of Management Science, Professor of Operations, Information and Decisions
  • Sergei Savin

    Sergei Savin

    Associate Professor of Operations, Information and Decisions
  • Senthil Veeraraghavan

    Senthil Veeraraghavan

    Associate Professor of Operations, Information and Decisions
  • Ron Berman

    Ron Berman

    Assistant Professor of Marketing
  • Eric Bradlow

    Eric Bradlow

    Professor of Marketing, Statistics, and Education, Chairperson, Wharton Marketing Department, Vice Dean and Director, Wharton Doctoral Program, Co-Director, Wharton Customer Analytics Initiative
  • Martine Haas

    Martine Haas

    Associate Professor of Management
  • Wharton Teaching Staff

    Wharton Teaching Staff

  • Christopher D. Ittner

    Christopher D. Ittner

    EY Professor of Accounting
  • Brian J Bushee

    Brian J Bushee

    The Geoffrey T. Boisi Professor
  • Cade Massey

    Cade Massey

    Practice Professor
  • Raghu Iyengar

    Raghu Iyengar

    Associate Professor of Marketing
  • Matthew Bidwell

    Matthew Bidwell

    Associate Professor of Management
  • Peter Fader

    Peter Fader

    Professor of Marketing and Co-Director of the Wharton Customer Analytics Initiative


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