Category Archives: Internet2

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 Know

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.

Took 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: Reliability Assurance of Big Data in the Cloud

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.

The Vietnam War: Unstructured data reporting and counterinsurgency

After reading No Sure Victory: Measuring U.S. Army Effectiveness and Progress in the Vietnam War I could not help but think about the consequences failed data reporting by MACV can serve a historical lesson for re-implementing or adjusting campus data reporting systems.

data reporting during Vietnam War

Data report tickets used by MACV in the early stages of The Vietnam War

Key stakeholders on campus should easily state their reasons for data collection and reporting. No Sure Victory benefits campus units by revealing an early, dare I say Big Data approach to unstructured data reporting and delivering actionable data.

Today we immediately understand Google’s Compute Engine or an Amazon Elastic MapReduce cloud for this demand.

Universities can thrive with diverse reporting teams. Working with Institutional Research and striving to improve enrollment and retention efforts are key goals. Yet important roles are filled with student workers. Here unstructured data often fragments over mismanagement. Many ad hoc Microsoft Excel documents are created without data governance and become silo’d from the campus data warehouse. Key stakeholders on any campus including CIOs, IR Directors, Research staff, Program Directors, campus data reporter writers and student workers. Even seasoned campus data report writers are not leveraged to streamline actionable data insights.

No Sure Victory brings to light a tragic failed data reporting implementation by Secretary of Defense Robert McNamara in addressing a war in Vietnam. The was his reputation as one of The Wiz Kids, the World War II Statistical Control unit that analyzed operational and logistical data to manage war.

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Latest read: The Changing Role of the CIO

We live in a world of constant change in IT. O’Reilly’s The 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.

The Changing Role of the CIO 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.

Latest read: Big Data at Work

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.