Enhanced interrogation is simply today’s political spin to a torture technique used for over 500 years. Waterboarding as a method of torture dates back to Spain in the 1500s. The Senate’s declassified report regarding the role of the CIA’s use of torture in the war on terror after 9/11 has been a most revealing so far. I wonder if the full report will ever be declassified. Maybe to further strengthen our democracy it should take less than the 40 year wait for the Pentagon Papers.
In today’s instant twitter-world of “news” the world has learned of CIA techniques as abhorrent as rectal rehydration and a technique — so innocent at first glance — prolonged standing until you realize how this form of torture, as written by Aleksandr Solzhenitsyn in The Gulag Archipelago is hideous to a human under interrogation.
In just reading the Senate’s executive overview the most chilling issue is that the CIA specifically withheld their acknowledgement of torture to the President. The second most important, but seemingly forgotten is the destruction of videotapes by the CIA of prisoners under torture. Clearly the CIA learned from Nixon’s Watergate.
I am beginning to feel again, after reading the Pentagon Papers that our democracy and leader of nations in today’s complex world has taken a temporary step backward.
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.
Today marks the 47th anniversary of the Battle of Ong Thanh. This battle was a tremendous loss for American troops, ambushed forty miles northwest of Saigon during Operation Shenandoah II.
Ong Thanh Battle date 1967
On this weekend in 1967 the battle in Vietnam and a student protest turned riot in Madison resulted in a turning point for the State of Wisconsin. While affluent students were protesting Dow Chemical at Bascom Hill, blue collar boys from the south side of Milwaukee were dying in battle.
The soldiers including Danny Sikorski, Jack Schroder and football All American Don Holleder served under the command of Terry Allen Jr. on this fateful day.
In Madison Paul Soglin, (the city’s current Mayor) led student protests that turned violent. After this battle 64 Americans were dead. Even today this is a shocking number of American losses in a small battle. The Tet Offensive began less than 90 days later.
It was in David Maraniss’ award winning book They Marched Into Sunlight the Sikorski family in Milwaukee would receive ~$740 from the Army to bury their son Danny. He was one of the first Black Lyons killed in Bravo Company. Yet at the same time The Pentagon Papers reveal the Michelin Corporation secured a reimbursement agreement from the U.S. Government for ~$700 per tree destroyed in combat on their rubber plantations in Vietnam.
The Army’s report on the battle of Ong Thanh remained classified for almost four years until released in 1971.
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.
3. Item Bank/Risk Pool is a fascinating chapter about Florida insurance policies. Hurricane seasons come and go and yet an established city mayor and established businessman could not maintain an ongoing insurance business even with years of experience in state government. I found this chapter interesting to discover how the state games the insurance system say for say….Hurricane Wilma. For Higher Education this chapter also reveals Admissions related stories that are most interesting when compared to hospital billing. Fung also brings into focus the Golden Rule lawsuit that successfully charged discrimination against minority applicants in the insurance industry. Continue reading →
The impact of cloud computing on O’Reilly’s 2008 Art of Capacity Planning has shifted quite a bit to say the least. Its still a great resource and well worth the read for any web administrator, manager or director.
My interest in revisiting is remembering Chapter 4: Predicting Trends. This touches two important factors today: cloud and procurement.
While in 2008 it was possible to ramp up a cloud, today a very high capacity cloud can be deployed in less than 10 minutes.
At the time of the book’s publication (2008) AWS pricing looked competitive. Yet today those prices are considered somewhat excessively high.
But the Art of Capacity Planning touches on the very important component of Procurement. Procurement and Cloud contract solutions taught by UCLA has been very beneficial to my cloud projects. Continue reading →
We live in a world of constant change in IT. O’Reilly’sThe Changing Role of the CIO provides a foundation regarding Big Data for any IT team and every manager, executive or board member. Today if your not embracing change your getting run over by it whether you know it or not.
From the corporate boardroom to the campus research lab we indeed are undergoing a fundamental paradigm shift in our digital lives.
Without a doubt it is also an educational shift. Questions of Excel cubesets in a world of unstructured big data analytics will be a much needed training opportunity not for your IT team but actually or your entire workforce.
The Changing Role of the CIO is about the opportunities to engage your IT team over data. Today data is fueling actionable analytics not just vanity metrics. The IT team needs to embrace the idea that data is the new oil.
After leading your organization to a cloud solution that eliminates in-house, legacy enterprise systems you never can look back. Helping my organization migrate to a CMS public cloud that reduced just one enterprise service $400,000 annually resulted in our senior leadership never looking at me the same way. You gain a seat at the table.
And due to the nature of the mobile beast, The Changing Role of the CIO shows its now easier than ever to measure quality engagements in real time with your customers. The future of data, how it can be measured, immediately reported within your office or from the other side of world is a game changer.
Big Data at Work is a good book for reviewing tested analytics case studies by Tom Davenport. As I began reading this I found myself reading an update to Tom Davenport‘s great analytics book Competing on Analytics that I read in 2008 which IMHO really set the standard. Big Data at Work is the follow up with tested business cases.
It seemed like an eternity that analytics are now realized as a critical business strategy for universities. Peter Drucker said it best: if you cannot measure it, you cannot manage it.
While much shorter than his Competing on Analytics, Big Data at Work is a must read. In Higher Education alone the Big Data at Work case studies by Davenport can serve as near perfect blueprints in the dynamic world of campus networks and services migrating to cloud.
Davenport needs to convince nobody that Big Data is a growing field, yet even in 2014 the number of colleges offering degrees in Big data science is not yet up to speed. More importantly he shares how traditional Business Intelligence is struggling to adjust to the analytics and big data era.
For as much as Big Data at Work contributes to the requirements in both technology and IT professionals, his suggestions that management stands in the way of more game changers outside of Silicon Valley. Yes Hadoop and MapReduce have forever empowered LInkedIn, Google, Yahoo and other startups. Healthcare, banking and insurance are markets who have already embraced and are excited about the abilities of big data for their customers.
Davenport is pretty upfront about what is needed: colleges have not fully embraced Big Data. Their mistake is assuming Big Data is a Computer Science degree. A good chapter of this book reflects on the inability of management to adopt Big Data for today’s competitive market. Is it surprising to see only a hand full of college programs sending grads to the likes of Google? More and more companies are looking to regional campus partnerships for Hadoop big data efforts. Yet many of those colleges still have no existing undergraduate or masters-level degrees in Big Data.