Superforecasting: The Art and Science of Prediction by Wharton’s Philip Tetlock and Dan Gardner is another great read addressing analytics, human behavior and analytic technologies for establishing and sharpening forecasting abilities for any organization.
The book title is a wonderful attention grabber for me that demonstrates we live in the era of big data with business driving the age of immediacy.
Superforecasting acknowledges data lessons supplied by Nate Silver’s The Signal and the Noise as helping to define standards to data and how it misled the national media.
Yet just into the second chapter Tetlock and Gardner point to the research by Daniel Kahneman excellent work Thinking Fast and Slow to help determine behaviors shaped over time that have fundamentally changed how we predict success.
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The emerging IoT developer community received a much anticipated jolt of news when Amazon finally announced new enterprise services dedicated to the AWS IoT cloud launch at their 2015 re:Invent conference.
This new AWS IoT cloud service will permit web based interfaces to manage IoT events from various devices: sensors, wearables, drones, and of course mobile tools and apps around an established AWS ecosystem.
The AWS IoT cloud emerges as Amazon’s long term platform following the SalesForce Thunder platform announced last month. Both vendors look to establish key IoT cloud solutions in the corporate enterprise space. They join Cisco’s IoT, Microsoft’s Azure IoT, Oracle’s Movintracks along side GE’s energy launch of Current IoT. The race is now on to process millions of data events from light bulbs to dishwashers and cars over the MQTT protocol and process those messages in their respective clouds.
Amazon is leveraging 11 services around their IoT Cloud strategy to include existing AWS services: Kinesis, Redshift, S3, SNS, SQS, ML, DynamoDB and Lambda. A key investment to this strategy was the recent acquisition of 2lemetry, a IoT enterprise company tuned for transforming raw data from IoT devices onto their ThingFabric platform.
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Tim Wu’s second book The Master Switch: The Rise and Fall of Information Empires is wonderful examination how American information empires were established and stifled innovation at the same time. This is my second book by Wu following his brilliant Who Controls the Internet.
Wu identifies long business cycles surrounding the birth of information systems. While they begin open over time they were consolidated and driven by the market to become closed.
We displays how they become open again following amazing innovations force a business change in order to survive in the new marketplace.
The Master Switch opens with the birth of the Bell AT&T telephone monopoly. This is a facinating story when held against the garage startups of Apple and Google.
There is an amazing look at how countries and cultures also view information empires differently. The case for Wu is the capitalist, independent market approach to radio vs the UK’s BBC dominated by the royal family.
The Master Switch reveals how four key markets actually hold government infrastructure: telecommunications, banking, energy and transportation. These four and their capitalist owners for generations established control over any citizen’s attempt at challenging their monopolies. The lesson Wu establishes is corporate control by closed technologies. Yet one cannot help but understand they magically protected the country from the devastating affects of revolution leading up to and more importantly the horrific aftermath of World War I that forever removed Paris as the hub for film entertainment.
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Over breakfast this weekend at a popular farmhouse two high school teachers sat next to me to discuss how their respective LMS solutions made teaching difficult. Both were from wealthy suburbs outside Milwaukee. What really peaked my interest was hearing how one spent over 45 minutes trying to add polling for in-class feedback.
I helped lead the adoption of a Moodle LMS at a private Wisconsin college in 2007 that is still in use today and also had the pleasure of attending a conference at UW-Madison with Martin Dougiamas the founder of Moodle.
Yet over that breakfast I was intrigued by their difficulty with all things LMS for the upcoming school year. Frustration ranged from how one teacher received no LMS training (poll example above) while the second teacher spoke about her district migrating to a new LMS vendor over the summer.
Of course no technology discussion can avoid a teacher mentioning K12 servers going offline for hours during the school day making their teaching even more difficult. Seems like teachers have a lot to confront on a daily basis in delivering education to a classroom of twenty plus students. A local LMS run from an empty closet is no longer acceptable.
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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.
This 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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Kudos to Microsoft’s Cybersecurity briefing team for providing a great three day briefing on Greenfield and Red Forest solutions. With 24 pages of hand written notes but no swag from Ignite, Microsoft has provided a solid foundation to continue moving Azure cloud services forward for small or large corporate IT infrastructure.
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.
The core message of Too BIG to IGNORE: 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.
Actionable Intelligence: A Guide to Delivering Business Results with Big Data Fast! falls into the must read category for leaders of any organization. Actionable Intelligence is in the Lean model well beyond the vanity metrics that so many leaders have embraced. Lessons on implementing a secure framework comes from lessons including Estee Lauder, Procter & Gamble, Lifetime Brands and the CIA. Yes the CIA.
Reading this book I have found tested lessons by Keith B. Carter regarding the lack of Actionable Intelligence in many organizations. The start always seems to be the lack of organized data and determining which is the most pressing to actually use in order to be successful in a fast changing world.
Maybe his most powerful work revolves around how executives at any company (or university) even question the value of actionable intelligence regardless of the tools already in place. Too many silo examples reinventing the wheel while overlooking the need to understand their own data reporting methods.
Sustaining delivery of actionable intelligence by the evolution from Dashboards to Cockpits. IMHO to many university leaders are just beginning to understand the Dashboard and their tools miss the Cockpit opportunities.
Business lessons alone describe how to mine actionable intelligence prove the validity of this book. Lessons from Estee Lauder include how the company was able to leverage secure data reporting in order to adjust following the powerful Japanese earthquake and tsunami that triggered the Fukushima Daiichi nuclear disaster. And in some ways Carter points to a crisis in order for executives to embrace actionable intelligence:
People do not trust data, they trust other people and their opinion of the data. So when the data owners, the people who input the data and/or use it, raise their hands and say, “This data is good; I trust it,” that will make it more likely for other people in the organization to believe it. It also means that it’s clear. It’s not just that they trust it from the point that 1 + 1 = 2. It is also clear how the data has to be used, and the definition of the data is clear.
Carter helps breakdown the old data principle “People don’t trust data – they trust other people.” Its true. Estee Lauder’s use of actionable intelligence is such that every organization should be striving towards in order to stay competitive.
There is nothing boring in the established insights and support for Big Data Using smart big data analytics and metrics to make better decisions and improve performance.
Read one big data book you’ve read them all right? Not so fast. This book reveals how a well planned understanding of your business can better embrace select data sets for your company, organization or school to not only remain competitive but thrive in the new global economy.
For all of the Big Data blogs, books and white papers that I have read Big Data by Bernard Marr is one of the better written books. Many will benefit from this knowledge.
Bernard Marr’s challenge continues to be what most senior managers do not understand about Big Data. And he does an admirable job in chapter six: Transforming Business. There are so many examples of how Big Data can actually re-define your objectives, but many are surrounded by a sales approach I recall from work Apple’s Michael Mace.
Michael was Director of Competitive Analysis at Apple and eloquently addressed FUD at a sales conference in the 90s. The same lessons apply today regarding Big Data. FUD is Fear, Uncertainty & Doubt.
Continue reading “Latest read: Big Data Using smart big data analytics and metrics to make better decisions and improve performance”
The recent pre-release of The Data Science Handbook is a fast, easy read. There is nothing better in business today than the still exploding market of data science. While some marketing statements indicate many are trying data science, here are the voices of recognized data science leaders. I have read my share of data science and big data books as well but like the direction of this pre-release.
Maturing technologies like Hadoop and even MapReduce prove yesterday was the time for every organization, business unit and non-profit to understand how data science is fundamentally changing the game.
Data Science hits your data sweet spot due to the ability of large systems to process your data in real-time. Notice how Microsoft is acquiring data science companies?
Data Science was just in its early stages not more than 10 years ago. Yahoo and Google helped move this forward. Even “legacy” companies like Sears Holdings understands the impact of MapReduce and Hadoop, they are well outside Silicon Valley. Just wait until some great advancements for public health are established by non-profits as a result of implement data science to forecast their business.
There is a great deal of excitement as the full release publication date inches closer. Cannot wait to see this book ship.
There can be no doubt today that Big Data has changed everything. Jeffery Needham has written a great book Disruptive Possibilities: How Big Data Changes Everything. Its all about the impact of Hadoop in the cloud as the ultimate computing platform.
I was very pleased reading his work when I found his personal story at the end regarding the application of Hadoop in neuroscience as a method to address Sturge-Weber Syndrome. We know it as having a port wine stain on your face.
His story made me appreciate his desire to throw Hadoop at the datasets that may one day reveal a cure for this syndrome. I am amazed at how he described reteaching himself not only how to walk down a hallway, but train his body to hit a baseball after losing vision in his right eye.
My favorite segment of Disruptive Possibilities is chapter five: When Clouds meet Big Data. Needham also makes a very easy read in chapters one to four where he lays the foundation based upon his deep experiences with Hadoop. And yes you can run Hadoop off laptops found in a dumpster.
There is much to learn in university circles about the impact of Disruptive Possibilities and Hadoop. Worry not its not the computing or research units that I am thinking about but rather HR, Admissions and just about every other campus unit that would benefit from moving their data into a Hadoop cluster in order to data mine their future.
Online Payments Risk Management is certainly a hot topic. The 2013 holiday data breach at Target and more recently, a new large data breach at Home Depot the need for organizations to understand Online Payments Risk Management is more important today truly than ever before.
I think there is no better way than for companies and payment card providers to step back and acknowledge many “security” measures are not effective today in combating cyber crime.
Ohad Samet’s book is a great introduction to payment risk management from multiple angles and can be a good base document to build upon in bringing PCI compliance efforts to online payment websites.
It may even be interesting to see how Samet positions of Loss over Fraud. The implications can be rather surprising.
Samet has organized this book into logical sections regarding approaches and the use of analytics to optimize tracking losses while also addressing the role of the organization and the people implementing secure transactions. Regardless of its 2013 publication, section 3 on Tools and Methods provides solid, industry tested solutions that should be reviewed annually.
That said its time to roll up your sleeves and begin protecting consumers.