Freebie Friday – This Week’s Big Data Free Stuff found on the Internet


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This week is BIRT software for Reporting & Data Visualization by Actuate.

“BIRT iHub F-Type will empower report developers with technology previously reserved for billion dollar corporations.

Developers can now take their business intelligence reports and visualization dashboards to the next level with instant interactivity, open data access, enterprise-class security, flexible scheduling, Excel & PDF export, and easy api embedding.

Download BIRT iHub F-Type today and you’ll be able to install and configure in 15 minutes or less. Get ready to instantly access your BIRT report and visualization architecture, completely free!”

Field Guide to Hadoop | Pentaho


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Field Guide to Hadoop | Pentaho.


Everyone loves free.  O’Reilly Media’s weekly newsletter includes a freebie and this week’s is courtesy of Pentaho.

“This book is recommended for IT managers, developers, data analysts, system architects, and similar technical workers, who are faced with having to replace current systems and skills with the new set required by NoSQL and Hadoop, or those who want to deepen their understanding of complementary technologies and databases.”

How Many People Have Read your Medical History? (and gotten it right)


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A new doctor or a new office … how many times have you filled in your personal medical information – from your address and insurance information down to the significant (or awkward) events of your medical history – the illness, the surgery, the procedure?  Not only is this excruciatingly private information, but it’s also important to you that it is accurate, timely AND secure.

Every time you write you name and information on a form a person has to read it, interpret it, and most likely enter it in some electronic form for a structured data base.  Will they get it right?  Would you know if they did or did not?

An entire job industry exists for medical data entry.  Not only are non-medical strangers reading your personal medical information time after time, but the information also potentially is incorrectly interpreted with errors in spelling, dates, treatments and more.  The data entry employee or outsourced contractor is not medically trained, and they are only human as far as reading and entering name after name. YOUR name and affliction and treatment are just a blip in the daily grind.,_N.J.,_files_medical_records_at_the_Michaud_Medical-Dental_Facility.jpg

I recently was scanning my military medical record – page by page. I don’t have much but somewhere in the middle I realized I had 10+ pages of every detail of someone else’s baby delivery. The last four of our socials were transposed. The record was several years old. Had that woman needed that information at some point only to get a shoulder shrug and “I’m sorry”?

… next post A Healthy Dose – Big Data Medical records

The Moneyball Effect: How smart data is transforming criminal justice, healthcare, music, and even government spending

Colette Grail:

Some awesome examples of Big Data in the Big World – NOT just business.

Originally posted on TED Blog:

Anne Milgram reveals what happened when New Jersey  moneyballed its criminal justice system. Photo: Marla Aufmuth

Anne Milgram reveals what happened when New Jersey moneyballed its criminal justice system. Photo: Marla Aufmuth

When Anne Milgram became the Attorney General of New Jersey in 2007, she was stunned to find out just how little data was available on who was being arrested, who was being charged, who was serving time in jails and prisons, and who was being released.

[ted_talkteaser id=1914]“It turns out that most big criminal justice agencies like my own didn’t track the things that matter,” she says in today’s talk, filmed at TED@BCG. “We didn’t share data, or use analytics, to make better decisions and reduce crime.”

Milgram’s idea for how to change this: “I wanted to moneyball criminal justice.”

Moneyball, of course, is the name of a 2011 movie starring Brad Pitt and the book it’s based on, written by Michael Lewis in 2003. The term refers to a practice adopted…

View original 832 more words

Eat Big Data


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Part 2 – How Big Data can tackle Big Obesity

Fighting obesity is a perfect example of Big Data capability – approach the battle of the bulge with no theory at all. Start with the data. Big Data won’t immediately provide the reasoning, but the data has patterns . . . and some answers.

Studying obesity and its flip side – “fit” – starts with information already in the cloud, not so much human experiments as human experience.  Google has approached figuring out where flu outbreaks begin by observing its massive search capability.  A similar method (and more) can be applied to observing fit and fat.  Utilizing Big Data to pool a data lake (habits, actions, information) that already exists and as it streams, observations and patterns in our lives that result in “fit” or “fat” are in the modeling.  Again, this is not a search for “why” but just “what” enables fit or fat.

This Big Data approach also works in concert, not opposition, with ongoing studies.  Past studies can be used again in this new perspective.

Is obesity simply calories in > calories out?

Is obesity a growth disorder?

A genetic disposition?

Big Data Exhaust also is free of the complications of choosing between environment observation methods: free-living or metabolic ward.  By absorbing multiple data sources, Big Data is the free-living components of both conscious and subconscious behavior, captured in a “ward” of data expression.

Fit or Fat The Data Lake feeds opportunity to observe the who/what/where/how of Fitness or Obesity

Fit or Fat
The Data Lake feeds opportunity to observe the who/what/where/how of Fitness or Obesity

Not THE Answer

Big Data isn’t the answer to the obesity issue. Big Data doesn’t replace current scientific methods. Big Data does provide a new method to learn more, faster by manipulating and “listening to” its muse.

Do I Look Fat?


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“Do I look fat?” It’s not just women asking a best friend or the mirror.

Woman looking at her body in the mirrorAs the US population continues down the train wreck track of increasing obesity, no one is immune.  Wired’s Sam Apple reports on the latest up-ending of nutrition rules to search for the Holy Grail of why we are so … fat.

Same Song, New Verse?

Haven’t we heard what a balanced diet was . . . and then it’s not . . . before?

The Future’s Take on Nutrition

Yes, theory after theory has been proposed and debunked by research as to how to eat well and not gain weight.  With so many theories and diets, no single path has emerged, or it has but then been rejected or at least qualified later.

The Nutrition Science Initiative, NuSI (pronounced new-see), though, is taking a fresh approach to the entire research process.  Not funded by the CDC or National Science Foundation, NuSI’s deep pockets are private grant – billionaire natural-gas trader John Arnold. Unbound by traditional research parameters, NuSI is out to challenge all the current diet thinking.

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NuSI is the creative passion of Gary Taubes (author of Good Calories, Bad Calories) and Peter Attia (former physician and medical researcher).   Taubes’ book not only challenged the current diet theories, but also tore apart the methodology that produced the results.

So what’s the Big Data Idea?   Eat Big Data!

Part 2 – How Big Data can tackle Big Obesity

A dive into “Data Lake”

Colette Grail:

Data Lakes are an integral part of Big Data.

Originally posted on Namit's Blog :

With the advancement in Big Data and Cloud lot of new concepts are surfacing. “Data Lake” is one such concept that is being talked about and in this blog I wish to de-mistify it.

So let’s begin with the need of Data Lake.

It is estimated that a staggering 70% of the time spent on analytics projects is concerned with identifying, cleansing, and integrating data, because of the following issues:

  • Data is often difficult to locate because it is scattered among many business applications and business systems.
  • Frequently the data needs reengineering and reformatting in order to make it easier to analyze.
  • The data must be refreshed regularly to keep it up-to-date when it is in use by analytics

Acquiring data for analytics in an ad hoc manner creates a huge burden on the teams that own the systems supplying data. Often the same type of data is repeatedly requested…

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Trust & Forgiveness in a Big Data World


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Big 3 Credit Reporting Agencies

What does your credit report say about you? When’s the last time you looked at that credit report to check what it does say?

Trust & Forgiveness

Credit history is one example of trust and forgiveness with personal information that pre-dates Big Data. We trust the credit agencies and system to report us accurately … but do they always?   When we have accidents or incidents, do we not want some promise of forgiveness?


What about the FB post or Tweet we wish we hadn’t sent? Like in a job interview or a pick up line at a bar, we all have things we wish we hadn’t said, but in a Big Data world, every social media post is captured for infinity.  (or is it? Can it be “erased?”)  Social media is also only a puff of your data exhaust as well.  Aren’t we entitled to make a mistake without it being digitally set in stone?  The answer isn’t so simple.

Created to evaporate after a few seconds ... but does it???
Created to evaporate after a few seconds … but does it???


What about “private” information for the “public” good? The position information on my cell phone as I drive helps the public – and myself – with collective, instantaneous feedback on traffic. But how else is that data used and am I good with it being “held” indefinitely?

Local Traffic

It’s a shady grey scale:  embarrassing drunk FB post,  borderline unlawful and inappropriate public official actions, the intermediate steps of a violent criminal.

Who has the say for what is public and what is private? How much trust is enough or too much? What are the forgiveness rules?

Experts Tim O’Reilly (O’Reilly Media) and Doug Cutting (Hadoop creator & Cloudera chief architect) give a brief overview of these delicate subjects, their effects and the challenges society faces with Big Data privacy.


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