Latest read: Too Big to Know: Rethinking Knowledge Now That the Facts Aren’t the Facts, Experts Are Everywhere, and the Smartest Person in the Room Is the Room

Too Big to Know: Rethinking Knowledge Now That the Facts Aren’t the Facts, Experts Are Everywhere, and the Smartest Person in the Room Is the Room by David Weinberger is an amazing look at how vast amounts of knowledge in our digital world has changed our ability to not only comprehend data, but how data and the internet rewire how our brain’s process information.
Too Big to KnowIn a way this book is about networks of knowledge stored in databases and in people. So what happens to all the knowledge and expertise we now confront? Outside of it being somewhat accessible on the net, the large amounts of data are forcing us to reimagine data infrastructure.

This is pushing development of large “big data” solutions that will have the ability to process and dashboard results that are more easily “digestable” for larger and larger groups of people across the spectrum.

Weinberger confirms that there is so much data, information & knowledge today for the first time in our collective history that no single person can process it all. And that is not always a good thing. He stated “We see all too clearly how impotent facts are in the face of firmly held beliefs. We have access to more facts than ever before, so we can see more convincingly than ever before that facts are not doing the job we hired them for.”

And at the same time accounting for human nature – access to more data will only reinforce the worse as illustrated by Cass Sunstein: “Studies have shown that when people speak only with those with whom they agree, they not only become more convinced of their own views, they tend to adopt more extreme versions of those views.” And now you know the rest of the story.

Too Big to Know reveals in chapter eight how we are managed today. In the past we learned about Jack Welch of GE. He was the final, top decision maker for his company. But today with wikis, blogs and mobile technology GE’s strategic plans are made from the bottom up: “The CEO of General Electric could be entirely off the grid, but still GE’s engineers, product managers, and marketing folks are out on the Net, exploring and trying out the ideas that affect their branch of the larger decision tree.” Its the Wikipedia approach to business today. And this is also something Weinberger acknowledges in Don Tapscott’s work Wikinomics.

Finally I could not agree more with Weinberger’s example in chapter five regarding a marketplace of echoes. He describes the impact of David Halberstam‘s award winning The Best and the Brightest (my review here) Halberstam attempts to explain how the Kennedy White House, so full of superbly educated, dedicated men, could have failed so badly in Vietnam. The book’s world is populated by household names now known in few households: McGeorge Bundy, George Ball, Chester Bowles . . . the events it discusses are distant, recalled most often as an analogy to our worst current mistake. But Halberstam’s question remains deeply unsettling: How did the best and the brightest get us into the Hell of Vietnam? If these men, so well educated and so worldly, erred so badly, how can we trust the advice of lesser men?

No better lesson on diversity than our failure in Vietnam. This is a very good book.

Latest read: The Signal and the Noise: Why So Many Predictions Fail–but Some Don’t

The Signal and the Noise: Why So Many Predictions Fail – But Some Don’t by Nate Silver is another great book that completely absorbed my attention. This book offers in sights to many audiences. From weather forecasts, the Wall Street financial crisis in 2007, playing poker to even understanding and identifying signal relationships regarding the attacks on Pearl Harbor and New York on 9/11.
The Signal and the NoiseThe Signal and the Noise offers readers Silver’s insights on Bayesian thinking. Actually the book applies Bayesian in all the books lessons.

He nudges us to remember this when applying predictions in our own professions. Actually Nate’s study of predictions affects just about everything we do in life.

The strongest lesson for me is about understanding data-driven models can lead to tragic outcomes. He warns us about noisy data and Big Data that can set off false readings with horrific consequences. This alone makes this book a pretty important read.

Silver’s chapter on baseball and references to Michael Lewis‘s bestseller MoneyBall actually reveals to the reader the best thing math geek and baseball scouts can do is collaborate together to make the game more accurate in evaluating talent. Great lessons in applied statistics. Take this as just one key book in helping to improve your job and your life.

Reading Nate Silver’s The Signal and the Noise

Wow just started reading The Signal and the Noise: Why So Many Predictions Fail – But Some Don’t and see it carries the strong reputation as a though provoking book about prediction.
The Signal and the NoiseHe continues to look at data including out of sample data to provide greater context to long held assumptions to credit default swaps that strangled Wall Street and the housing bubble.

Even in defining why the US depression following the wall street collapse was worse than projected, his appeal of Too Big To Fail proves he has a good foundation from Andrew Ross Sorkin’s great book.

The second chapter of The Signal and the Noise focuses on pro baseball. Its another look at America’s game from a geek’s perspective. He acknowledges the impact of Moneyball by Michael Lewis. Lewis is a respected writer for all things wall street and metrics.

Now lets see how risk takers in Higher Education can improve a campus by understanding and absorbing these lessons….just pushing into chapter three.

My latest read: If I Die in a Combat Zone

If I Die in a Combat Zone by Tim O’Brien was a fast yet welcoming read last night. I finished this book in just under three hours. He writes about his experience in Vietnam, thoughts of escaping to Europe and stories about fellow soldiers in Alpha Company from 1969 to 1970 which included supporting the area of the My Lai Massacre just one year following the atrocities.
If I Die in a Combat ZoneO’Brien shares a brief story of growing up in the Midwest and life in Worthington Minnesota. He shares his experiences joining the army. If I Die in a Combat Zone shares how fellow soldiers were not fully committed by 1969 to fighting a losing war.

He shares his relationship with a solider “Erik” who also disagrees with the war and their experiences at Fort Lewis before begin shipped to Vietnam.

The topic of desertion is addressed as O’Brien planned to dessert while on leave and make his way to Sweden. Yet after all his detailed research and staying in a hotel with an AWOL bag fully packed, he does not desert. Midwestern values played a strong influence.

If I Die in a Combat Zone reveals O’Brien served around My Lai, the site of the US Army My Lai Massacre, but as the book closes he writes about getting a job out of the company’s combat zone and ends up working for an officer investigating the massacre led by William Calley and Charlie Company of the same battalion O’Brien served just one year later.

Latest read: Reliability Assurance of Big Data in the Cloud: Cost-Effective Replication-Based Storage

While focused on the task of generating data for astrophysics Reliability Assurance of Big Data in the Cloud is a worthy read when focused around designing cloud service contacts.
Reliability Assurance of Big Data in the CloudThe work of authors Yang, Li and Yuan surround capturing big data reliability, and measuring disk storage solutions including from noted cloud vendors.

Their work at Centre for Astrophysics and Supercomputing at Swinburne University of Technology focused on reducing cloud-based storage cost and energy consumption methods.

They also share the impact of multiple replication-based data storage approaches based upon Proactive Replica Checking for Reliability (PRCR). That was very interesting in their research data gathering.

I found Reliability Assurance of Big Data in the Cloud also supports moving data into the cloud across advanced research networks including Internet2.

Processing raw data inside the data center impacts network models (based upon available bandwidth) in their work. Their research gathers and stores 8 minute segments of telescope data that generates 236GB of raw data. By no means in the petabyte stage (yet) but it still sets a solid understanding of contractual demands on big data cloud storage.

My interest peaked around impacts developing knowledgeable contracts for cloud services. Their background regarding data gathering and processing should influence procurement contract language. This is even more applicable when applied to petabyte data sets and the SLAs regarding data reliability requirements. Never leave money on the table when scaling to the petabyte range. Must read for purchasing agents and corporate (and university) CPSMs.