Tag: big data

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Latest Read: The AI Factor

The AI Factor: How to Apply Artificial Intelligence and Use Big Data to Grow Your Business Exponentially by Asha Saxena. Asha holds a Masters in Data Science and Machine Learning from Southern Methodist University.

The AI Factor: How to Apply Artificial Intelligence and Use Big Data to Grow Your Business Exponentially by Asha Saxena

Asha is an Adjunct Professor in the Department of Health Policy and Management at the Mailman School of Public Health at Columbia University. Above all, Asha is the Founder and CEO of Women Leaders in Data and AI (WLDA). She has served as CEO and Chairperson of Future Technologies Inc., a data management firm that provided warehousing, analytics, and intelligence services.

The AI Factor is addressing a roadmap business leaders can understand while beginning their organization’s AI digital transformation. In fact, Asha provides a great introduction that will resonate with companies: Micheal Lewis’ Moneyball which tells the story of the Oakland A’s use of data analytics to find success as a small market baseball team competing against teams in huge metrpolitean areas across the country.

Asha is writing about AI transformations at Netflix and Starbucks. For instance, the key element for both companies was their extensive deployment of data analytics which provided a key advantage of their competitors. Netflix has fully embraced data analytics versus Blockbuster. Besides, this transition was at the right time. Broadband was beginning to deliver on the promise of the internet and tip the scales for amazon to continue launching into the giant they have become.

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Latest Read: Weapons of Math Destruction

Cathy O’Neil has written Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. Cathy holds a Ph.D. in mathematics from Harvard. She taught at MIT and Barnard College. After four years Cathy departed for Wall Street. Learning first hand how big data is manipulated, she departed disappointed.

weapons of math destruction

Cathy turned to applying large data sets to understand how big data reinforces old stereotypes of wealth and race.

Just as Wall Street and society were embracing big data, the subprime mortgage collapse arrived. Cathy was just starting her career on Wall Street and witnessed the collapse from a close, fresh perspective.

Cathy has insights to that timeframe — and backed by big data. Methods to create big datasets should undergo scrutiny. Cathy reveals errors in several datasets throughout the book. These are referred to as WMDs. The errors are very real and impact American society. To no surprise the largest impacted groups are minorities and the poor.

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Latest Read: Everybody Lies

Seth Stephens-Davidowitz wrote Everybody Lies Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are. Seth holds a Ph.D. in economics from Harvard. He is a former quantitative analyst at Google. Seth also writes for the NYTimes. The stories are similar to Freakonomics but are based upon much larger datasets.

Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are

Everybody Lies is able to utilize Google search data that reveals in the opening chapter that we live in a very racist society.

Seth reviews search results from the 2016 Presidential election. Data mining via Google Search revealed hard truths that most would not say in mixed company.

Search at at work or home, Google data clearly indicated racists supported Trump in the 2016 Presidential election.

The outcomes of data mining Google search, Wikipedia, Facebook, Pornhub and Stormfront. The results are somewhat surprising if you simply follow analog driven surveys popular in the 1950s and 1960s. Clearly the mobile revolution and search provides real insights to the sway of the country or just specific sets of groups.

Everybody Lies tackles some interesting topics with vast amounts of data sets:

  • How much sex do people really have?
  • How many Americans are actually racist?
  • What should you say on a first date if you want a second?
  • Is America experiencing a hidden back-alley abortion crisis?
  • Where is the best place to raise kids?
  • Can you game the stock market?
  • Do parents treat sons differently from daughters?
  • How many men are gay?
  • Do violent movies increase violent crime?
  • How many people actually read the books they buy?

Like Freakonomics, the results will surprise you.

One of the more interesting data sets is within chapter three: Bodies as Data and involved a great story of American Pharoah. What makes a great racehorse? Actually the percentile of the left ventricle. Jeff Seder found the way to measure success of a racehorse. A great story is here. Seder, a Harvard trained lawyer took his hedge fund experience and applied it to his love of champion racehorses.

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Latest read: Learning with Big Data – The Future of Education

Big Data has changed education forever. Learning with Big Data reveals If your school has not fully embraced big data you should consider moving your child’s education elsewhere. In higher education its fully integrated across the institution from the admissions office all the way through the office of alumni relations.
Learning with Big Data – The Future of EducationThis short e-read builds upon the success of Big Data: A Revolution That Will Transform How We Live, Work, and Think released in 2013. This book is not about MOOCs, but does dedicate pages to the background and success of Khan Academy.

Authors Viktor Mayer-Schonberger, Professor of Internet Governance and Regulation from Oxford and Kenneth Cukier from The Economist introduce Learning with Big Data by way of the role of machine learning at Stanford. The course is taught by Andrew Ng, cofounder of Coursera.

Ng has brought to the globe the ability to teach a world class curriculum in machine learning from California to students in Tibet. In many ways this very idea is threatening to close minded administrators sitting in their siloed office.

The focus in this special book is how big data, which reveals to educators what works and what does not is reforming education. The ability today to interactively track the performance of each individual student in real time throughout the semester can make a big difference because the data drives how focused, dedicated administrators can more effectively budget extremely tight dollars in guiding a campus forward.

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Latest read: Too Big to Ignore

Phil Simon’s book Too BIG to IGNORE: The Business Case for Big Data is another well written primer for Big Data in business. The focus is NOT the programmer’s dilemma of Hadoop vs. NoSQL vs NewSQL. Simon richly documents how Big Data has forever changed business and society.
Too Big to Ignore The Business Case for Big DataThe core message: for the first time we have a very inexpensive ability to data mine a wealth of information. Organizations that tap into this new capability can execute their business more accurately than ever before. However Simon also acknowledges the obvious fact that companies must understand the format of their data while the leadership understands the benefits of pushing big data solutions throughout the organization.

Too Big to Ignore begins by telling about the success of MoneyBall by noted author Michael Lewis. Too Big to Ignore reveals how sports franchises exploit data to win on the field and for the worse how Las Vegas casinos have been using A/B testing to pinch every penny out of their best customers. Probably the best but sad example. Similar to the approach by other authors addressing Big Data the focus is on the explosion of data from Google, Facebook, Apple and Netflix as the smartphone and wireless technologies began to change society in ways that drive unstructured data well beyond traditional structured environments.

Simon walks through the history of big data from Web2.0 to Predictive Analytics and touches The Internet of Things. Simon address the tool Hadoop lightly enough as to not scare off any non-database programmer to understand how this free tool is used by Yahoo, Google, Facebook and Apple just to name a few successful highly profiled companies. The growth of Hadoop and the emerging role of Cloudera is addressed in greater detail for the non-technical audience.