what big data is, how to get it, and how to use data about individual
behavior to elevate a company’s level of performance.
Big data—especially data about individual behavior and how it is
impacted by interaction with others—gives valuable insight into a
variety of business scenarios. The
frameworks taught in this program constitute a new kind of "R&D"
that draws on the strengths of digitization to speed innovation,
increase customer loyalty, and improve execution.
Big Data: Making Complex Things Simpler
Certificate Track: Management and Leadership
Location: Cambridge, Massachusetts
Tuition: $3,300 (excluding accommodations)
Program Days (for certificate credit): 2
Today, businesses can measure their activities and customer relationships with unprecedented precision. As a result, they are awash with data. This is particularly evident in the digital economy, where clickstream data give precisely targeted and real-time insights into consumer behavior, but leading edge companies in every industry are using big data to replace intuition and guesswork.
Collectively, the practices taught in this program constitute a new kind of "R&D" that draws on the strengths of digitization to speed innovation, increase customer loyalty, and improve execution.
Through examples, case studies, and discussion in buzz groups, participants will learn how organizations are using big data effectively in fields as diverse as marketing, retailing, branches of government and healthcare. The program will encourage participants to apply these concepts in the context of their own organizations—including defining problems that could benefit from the application of big data concepts, brainstorming sources of data, and designing experiments to collect and analyze data in ways that are acceptable to customers—to create new value.
Participants in this program will learn:
Sample Schedule - Subject to Change
|DAY 1 SAMPLE|
|07:45AM - 08:30AM||Registration and Continental Breakfast|
|08:30AM - 09:00AM||Welcome and Introduction|
|09:00AM - 10:30AM||Overview: The big data revolution; the payoff from data-driven decision-making; how digitization is transforming innovation|
|11:00AM - 12:30PM||Information flows: within companies; patterns of information; integration of distance workers|
|12:30PM - 01:30PM||Luncheon|
|01:30PM - 03:30PM||Three case studies: using Google searches to predict the housing market; using email and sociometric badges to understand information worker productivity; using experiments to understand causality in advertising|
|04:00PM - 05:15PM||Using behavior to guide marketing: digital breadcrumbs; stratifying; real estate management; mobile marketing; predicting rate of adoption based on social networks|
|05:15PM - 06:00PM||Reception|
|DAY 2 SAMPLE|
|07:45AM - 08:30AM||Continental Breakfast|
|08:30AM - 09:00AM||Welcome Back and Preview of Day 2|
|09:00AM - 12:00PM||Organizational, social and cultural considerations; Matrix of change exercise; How to get access to the right kind of data; Social network data (organic growth); Data design|
|12:00PM - 01:00PM||Luncheon|
|01:00PM - 03:30PM||Social network data (organic growth)-social networks and trust networks; the future of big data; a plan for action|
|03:30PM - 04:00PM||Adjournment|
MIT professors Erik Brynjolfsson and Andrew McAfee have just published their book "The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies," which looks at the impact of technology on society, and discusses the role technology plays in work and inequality.VIEW
Erik Brynjolfsson and Andrew McAfee, both at MIT's Sloan School of Management, are co-authors of "The Second Machine Age".
James Manyika is head of the McKinsey Global Institute.
As the worldwide slump stretches into its sixth year, we hear ever-louder and more insistent cries that we've reached the end of innovation, and that growth is dead.
Don't believe them.
The Second Machine Age and the future of enjoying your job.VIEW
Congratulations. You bought into Big Data and its paying off Big Time. You slice, dice, parse and process every screen-stroke, clickstream, Like, tweet and touch point that matters to your enterprise. You now know exactly who your best and worst customers, clients, employees and partners are. Knowledge is power. But what kind of power does all that knowledge buy?
Big Data creates Big Dilemmas. Greater knowledge of customers creates new potential and power to discriminate. Big Data and its associated analytics dramatically increase both the dimensionality and degrees of freedom for detailed discrimination. So where, in your corporate culture and strategy, does value-added personalization and segmentation end and harmful discrimination begin?
A decade ago, MIT professors Erik Brynjolfsson and Andrew McAfee would have told you that driving a car is something machines just cant do.
Now the two zoom down Route 101 in a self-driving vehicle, marveling at the mundanity of watching a machine do its work.
Its another example of how rapidly technology progresses, from smartphones that accurately carry out instructions to 3-D printers that can fabricate nearly anything. The authors new book, The Second Machine Age, is all about that technological progress and how society should deal with the challenges, disruptions, and opportunities it presents.
In "The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies," co-authors Erik Brynjolfsson and Andrew McAfee discuss how the world is adapting to the changes brought about by rapid digital innovation and the further possibilities for that innovation. They write that "the key building blocks are already in place for digital technologies to be as important and transformational to society and the economy as the steam engine." In short, they compare the potential of this era, which they deem the Second Machine Age, to that of the Industrial Revolution.VIEW
The most consistently creative and insightful people are explorers. They spend an enormous amount of time seeking out new people and different ideas, without necessarily trying very hard to find the best people or best ideas.
Instead, they seek out people with different views and different ideas.
Taped by WGBH Forum Network, Erik Brynjolfsson and Andrew McAfee, visited the Brattle Theater in Harvard Square to discuss their new book, The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies, with host Meghna Chakrabarti.VIEW
Focus on how people relate to each other, says MIT's Sandy PentlandVIEW
Catherine F: This course presented contemporary views on implications and opportunities that come with the big data move in he industry. The professors were dynamic, interesting and relevant. Materials were well developed and engaging. This is the first class for me that did not provide the PPT ahead of time. Too bad...it's nice to take notes or highlight points as you go along. I think it could actually have been a 3 day course with the 3rd day turned to a workshop where teams work together to frame-up some problems to solve or specific situations they have an opportunity to address. As an aside, this was the youngest crowd I have seen at a class. My sense is it was also the least senior. This was not an executive program but rather a 'game changers' program - IMHO. We had very good, diverse, thoughtful conversations at our table. This was by far my favorite class in the program. Relevant, contemporary, eye-opening, mind expanding... Thank you to Sloan, the students, and the professors.
Leonardo F: Of all the courses I had this one is by far the best! Faculty is top-of-the-field and it was greatly balanced for the whole duration of the program. Lectures and inter-active exercises are perfectly intertwined with no chance given to boredom. Topic itself is extremely exciting and evenly distributed throughout its economical, social and business applications. Course material is powerful and really engaging as well as "right-out-of-the-press" complimentary books. Last but not least, having the class at MIT Lab is definitively a plus that no other course has so far. On my company internal blog I shared this same appreciation and invited other people to attend. For all those who wants to be part and lead the new industrial revolution of "Big Data" this course is a must!
Kevin E: Great program! A couple of sets of feedback; 1. If the ppts could be uploaded rather than pdfs of presentations, that would be more effective. The ppts that Erik and Sandy had animations on them and the pdfs don't take the animations or build slides so the pdfs were missing info 2. Any way we could be on the MIT campus rather than a hotel? Feel as though the campus experience adds to the learning. Thanks!
Julio Mario L: It would be useful to have a demo about how to collect and treat Raw data and the strategies to reduce the data set. This course coulde be allocated at MIT Campus .
Grace H: Course content felt dated with old research and older concepts. Disappointed there was not more "how to" on processing complex data sets. Or more modeling and technology on big data. Class discussions and classmates were great.
Bramwell K: We got to know the wide range of applications of "Big Data". I wish I had won more insights in a detailed case study (project procedures, costs, IT architectures and used software tools). Also exciting were not expected topics such as "social learning".
Claudia L: the combination of off-line was online disturbing and did not do anybody justice. the rest was cool even if many sessions are more informative than "to be used".
Caswell S: The depth and quality of the material provided insights and framework that one can leverage to understand and leverage Big Data maybe in ways that you had not considered before. The Professors were awesome! The incorporation of Avitars for students that attended on-line was a fascinating interaction to observe.
Jedd W: The online integration is causing significant delay in the class and for people like me that paid to attend the course live, it is taking away from me. I'd strongly encourage getting the technology working (fix the delay) before trying this again.
Stacey W: The content is relevant and it's reassuring to hear other folks are dealing with the challenges I am tackling at work. I feel the phrase "Big Data" created too much random hype. Some of the topics are basic data analysis, not necessarily "Big Data". It's fine to mix the traditional data topics into this seminar but we should just call it out that way. The session is lively to keep us engaged throughout the day. The virtual session is an interesting experiment.
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