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A Room with a View (of Crucial Big Data Insights)

What’s the problem with Big Data? You guessed right — it’s BIG.

Big Data empowers organizations to discern patterns that were once invisible, leading to breakthrough ideas and transformed business performance. But there is simply so much of it, and from such myriad sources — customers, competitors, mobile, social, web, transactional, operational, internal, external, structured, and unstructured — that, for many organizations, Big Data is overwhelming. The torrents of data will only increase as the Internet of Everything spreads its ever-expanding wave of connectivity, from 10 billion connected things today to 50 billion in 2020.

So, how can organizations learn to use all of that data?

The key lies not in simply having access to enormous data streams. Information must be filtered for crucial, actionable insights, and presented to the right people in a visualized, comprehensible form. Only then will Big Data transform business strategies and decisions. In effect, Big Data must be made small.

However, as McKinsey & Co. reported, many organizations don’t have enough data scientists, much less ones who understand the business well enough to draw conclusions. The trick is to get the scientists together with the experts who understand the business levers driving the organization. Put them in a room with the right tools, and watch the synergy fly.

But what sort of a room?

big_data_room_10_new

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Big Data in Security – Part II: The AMPLab Stack

TRAC

Following part one of our Big Data in Security series on TRAC tools, I caught up with talented data scientist Mahdi Namazifar to discuss TRAC’s work with the Berkeley AMPLab Big Data stack.

Researchers at University of California, Berkeley AMPLab built this open source Berkeley Data Analytics Stack (BDAS), starting at the bottom what is Mesos?

AMPLab is looking at the big data problem from a slightly different perspective, a novel perspective that includes a number of different components. When you look at the stack at the lowest level, you see Mesos, which is a resource management tool for cluster computing. Suppose you have a cluster that you are using for running Hadoop Map Reduce jobs, MPI jobs, and multi-threaded jobs. Mesos manages the available computing resources and assigns them to different kinds of jobs running on the cluster in an efficient way. In a traditional Hadoop cluster, only one Map-Reduce job is running at any given time and that job blocks all the cluster resources.  Mesos on the other hand, sits on top of a cluster and manages the resources for all the different types of computation that might be running on the cluster. Mesos is similar to Apache YARN, which is another cluster resource management tool. TRAC doesn’t currently use Mesos.

 

AMPLab Stack

The AMPLab Statck
Source: https://amplab.cs.berkeley.edu/software/

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Big Data in Security – Part I: TRAC Tools

TRACRecently I had an opportunity to sit down with the talented data scientists from Cisco’s Threat Research, Analysis, and Communications (TRAC) team to discuss Big Data security challenges, tools and methodologies. The following is part one of five in this series where Jisheng Wang, John Conley, and Preetham Raghunanda share how TRAC is tackling Big Data.

Given the hype surrounding “Big Data,” what does that term actually mean?

John:  First of all, because of overuse, the “Big Data” term has become almost meaningless. For us and for SIO (Security Intelligence and Operations) it means a combination of infrastructure, tools, and data sources all coming together to make it possible to have unified repositories of data that can address problems that we never thought we could solve before. It really means taking advantage of new technologies, tools, and new ways of thinking about problems.

Big Data

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Your Data, Yourself — in the Marketplace of Me

On a typical day, we leave a vast trail of data in our wake. Our browsing histories, online preferences, shopping habits, work decisions, social interactions—all are rendered in binary code, prompting a complex interaction of requests, responses, affirmations, and denials.

And that’s just from our laptops and smartphones.

What about when the Internet of Everything — with its explosion in connectivity from 10 billion “things” today to 50 billion in 2020 — truly shifts into overdrive? At that point, our clothing, our houses, our cars, our lawns, and our refrigerators may be generating ever-larger torrents of data — all about us.

This upsurge in personal Big Data has big implications. Indeed, each person’s emerging digital persona will go a long way toward defining their place in the world.  Furthermore, all of that data already has great intrinsic value to Internet giants, retailers, financial services companies, and many others. If we manage it right — in what I see as a burgeoning Marketplace of Me — some of that value may come right back to us.

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A Healthier You with Big Data

What if you had a “virtual doctor” who was available at any time—24x7—to give you a quick checkup, dispense friendly health advice, and even alert you to possible health problems before they become serious? What if your parents or grandparents got a gentle daily reminder to take their medication, so they would never have to worry about missing a dose? What if you could walk into any emergency room in the country and receive exactly the care you need because the hospital has instant access to all your medical records? While much of this may seem futuristic, it will become reality in a future not that far away.

Big Data and analytics are transforming healthcare as we know it. Let me share a few examples:

1. Patient care

Many healthcare providers are stretched to capacity, and can’t always follow up with patients to see how they’re doing and make sure they are following medical advice. Today, we are beginning to see pills with tiny ingestible sensors that send a message to your doctor or to a loved one to confirm that you have taken the pill—giving peace of mind to worried children of elderly parents, or anyone who needs to take medication at a specified time. In the future, these sensors will likely also be able to report whether the medicine results in the right impact, and to suggest a change of dose or even a different medication, if that is appropriate.

A high-risk pregnancy is a constant source of worry for many women. In the near future, small electronic “tattoos” will provide nonstop fetal monitoring through a sticker worn right on the skin. Wireless communications capabilities will send vital signs directly to the cloud, where Big Data and analytics capabilities can evaluate the information and send appropriate alerts to the mother and her doctor.

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