Data & All the Little Fishes That Swim in the Sea

Interesting article from +james m connolly about efforts by +Google Analytics, +SkyTruth  and Oceana who together form +Global Fishing Watch. I agree with him completely - it relies on everyone having an Automatic Identification Systems (AIS) in order to map their location but that is not likely so whilst those that have one know they are being watched anyone that does not have one has a carte blanche to go into areas the others can't in order to fish.  Great idea just issues with the execution.

Regression Analysis using R

While dealing with any prediction problem, the easiest, most widely used yet powerful technique is the Linear Regression. Regression analysis is used for modeling the relationship between a response variable and one or more input variables.

This blog from +suresh kumar Gorakala is great at talking through examples and providing R code which could help anyone still learning the basics.  It's actually good for the rest of us to remind us too.

So you wanna be a data scientist? A guide to 2015's hottest profession

Are you good at math? Like, really good at math? Do you also know Python and, oh yeah, have deep knowledge of a particular industry?

On the off chance that you possess this agglomeration of skills, you might have what it takes to be a data scientist. If so, these are good times. LinkedIn just voted "statistical analysis and data mining" the top skill that got people hired in 2014.

Continue to read this interesting article on +Mashable

Know More, Sell More With Data Science in 2015

Yes, 2014 was a big technology year for sales teams. We saw the launch of Salesforce’s Analytics Cloud, HubSpot’s entrance into CRM, and a flurry of new startups trying to change the way selling and forecasting gets done. Venture capitalists invested over a quarter of a billion into the industry in 2014 because they know technology that makes sales teams better means big value.

Continue to read here on +Information Management

The Future of Data Scientists

Since our days as cavemen, people and companies have been tasked with what seems like an impossible job: Take in massive amounts of data, process that data, and make decisions based on that data for our benefit and the benefit of others. And while the types of data have changed and the tools used to analyze data have grown exponentially more sophisticated, the process is as old as our species itself.

Continue to read here on +Information Management

Cheat Sheets for Data Science

Blog by Steve Miller on +Information Management with some links to cheat sheets/

I would also recommend looking at this article of cheat sheets by +Vincent Granville which I find more comprehesive.

Will Big Data Resolve Questions of Measurement in Social Research?

The big five personality traits are some of the most well researched concepts in the field of psychology. It is a framework used to understand human personality along five factors; openness, conscientious, extraversion, agreeableness, and neuroticism. Each factor has its own spectrum and an individual may rank anywhere between the points of the two extremes. An individual’s personality will be an amalgam of these factors.

Continue reading on +SteamFeed 

Live Map Shows Thousands Of Cyber Attacks As They Happen

Sony got nuked, said one security expert. But it’s hardly the only attack aimed at a major corporation. Tens of thousands of cyber attacks are launched every second – a majority of which are directed at the United States – but few have the impact that can force a Hollywood studio to cancel a film.

Look at this article on +Forbes to see a real tie map of cyber attacks.  It is both fascinating and scary.

How does the typical data science project life-cycle look like?

This blog post looks at practical aspects of implementing data science projects. It also assumes a certain level of maturity in big data and data science management within the organisation.

By Maloy Manna

Finding Maturity in Your Metadata Strategy

Metadata has always been around. There used to be a theory that organizations needed to devise one and only one way of defining a concept, making it official, and then keeping it in one place for everyone to access and use. That goal was never achieved in most organizations, and thus the information lifecycle continues to evolve. We create reference data, master data, metadata, operational metadata, business metadata and process metadata, and I guess it is all really data. Or is it?

Continue reading here on +Information Management 

Why 2015 Will Be Year of Big Data: Oracle's Seven Predictions

Data is a new form of capital. Ultimately, information about people, places and things will truly differentiate enterprises.

Oracle has been handling big data-type workloads in its parallel databases since long before the term "big data"—and even the Internet—was born.

Continue reading here on +eWEEK.com

Hadoop Tutorial - How to visualise website Clickstream Data

This Hadoop tutorial is from the Hortonworks Sandbox – a single-node Hadoop cluster running in a virtual machine. Download to run this and other tutorials in the series. The tutorials presented here are for Sandbox v2.0

SLIDESHOW - 8 Hadoop Big Data Predictions for 2015

Where is Hadoop, the open source Big Data platform, heading in 2015? No doubt, a growing number of businesses will build smart applications atop Hadoop. But the effort will push beyond analytics, according to Forrester Research Inc. – which offers up these eight Hadoop predictions for 2015.

See the slideshow here on +Information Management

How Big Data Changed the World in 2014

Data accumulation has been so fast in the last two years that it is even bigger than all the data collected since the first record of human civilization. It got so big that it is now called “big data”. In fact, Google CEO Eric Schmidt in 2010 said that the amount of data collected since the dawn of humanity until 2003 was the equivalent to the volume we now produce every two days.

Continue to read here on +Infinit Datum

A Tale Of Two Cities: Why Europe Is Struggling To Compete In The Big Data Market

There’s a pervasive belief in the tech world that Europe is a year behind New York and two years behind Silicon Valley when it comes to technological innovation. While there is still an undeniable lag, European tech companies are seeking to bridge the gap.

Continue reading on +BusinessIntelligence.com

3 Hacks for Using Big Data to Increase Sales Revenue

In today’s market, data accuracy, quite simply, is the price of admission for doing business. But today’s sales teams are faced with a fundamental lack of knowledge about their customers and what those customers need.

Continue reading here on +Data Informed

5 Business Areas Poised for Big Data Opportunities in 2015

The term “big data” prompts a range of different responses and emotions. For some, it might evoke anticipation and excitement in the knowledge that, if analyzed properly and put to good use, the reams of collectible data available today can have a profound positive impact on business performance, quality of life, and society. For others, the term might be met with an “enough already” eye roll and frustration or a feeling of being overwhelmed by the notion of this nonstop machine of information.

Continue reading here on +Data Informed

We're all being mined for data – but who are the real winners?

A year on from the Snowden/NSA revelations, John Naughton examines whether big data – the masses of online information collected from all of us – is a force for good or bad?

Read in this article from +The Guardian

Getting to the Business of Big Data: Overcoming the Marketer's Dilemma

If you're a marketer and Big Data is keeping you up at night, take comfort in knowing you're not alone. According to a recent IBM survey, the percentage of CMO's who feel under prepared to deal with the "data explosion" increased from 71% to 82% between 2011 and 2014. Big Data is a source of unrelenting angst among marketers everywhere.

Continue reading here on Smart Data Collective

Why Open Source Storage May Not Be for You

Open source storage (OSS) software has been in the news a lot in 2014. This reflects the growing interest in open-source technology in general, which relies on software with a source code generally given to the public free of charge by a public collaboration project (often, some commercial vendors also offer a supported distribution of the software for a service fee).

Continue reading here on +Data Informed

5 Ways the Internet of Things Can Change Retail

For years, imagination and modelling propelled the very sci-fi idea of computers running our lives. Think of people in the late 1960s imagining our life now — as illustrated in this 1969 film from the Philco-Ford Corporation that reveals what life will be like for a family living in 1999.

Continue reading on +Salesforce

Big Data: The Key Vocabulary Everyone Should Understand

The field of Big Data requires more clarity and I am a big fan of simple explanations. This is why I have attempted to provide simple explanations for some of the most important technologies and terms you will come across if you’re looking at getting into big data.

Guest blog post by +Bernard Marr on Data Science Central

10 data science predictions for 2015

These predictions were published by the International Institute for Analytics (IIA). They produced a nice infographics, featured below, and re-tweeted many times by various bloggers, using the hash tag #2015Analytics. Other interesting predictions include those by Tableau, those by Pivotal, as well as +Vincent Granville's  own predictions.

Continue to read here.

IBM, Apple Intro Big Data Enterprise Apps for iPhone, iPad

Five months after Apple Inc. (AAPL)’s partnership with International Business Machines Corp. (IBM) was announced, the companies are unveiling the initial fruits of the deal: 10 applications made for governments and businesses.

Read on +Information Management

Top ten hottest BI Analytics skills for 2015

Gartner’s recent CIO insights document shows that BI/analytics is the number one (and growing) priority for CIOs globally.

Additionally, respondents to the recent Computerworld Forecast survey who said they plan to add IT positions in the next 12 months, listed BI/analytics expertise as the skill set they expect to have the hardest time finding.

Continue to read article on +KDR Recruitment

Will Spark, Google Dataflow Steal Hadoop's Thunder?

Apache Spark and Google's Cloud Dataflow service won't kill Hadoop, but they're aimed at the high-value role in big data analysis.

Continue to read on Information Week

Big Data, IOT and Security - OH MY!

While we aren’t exactly “following the yellow brick road” these days, you may be feeling a bit like Dorothy from the “Wizard of Oz” when it comes to these topics. No my friend, you aren’t in Kansas anymore! As seem above from Topsy, these three subjects are extremely popular these days and for the last 30 days seem to follow a similar pattern (coincidence?).

Continue reading this blog from +Carla Gentry

Don’t Judge a Tweet by its 140 Characters: How One App is Using Machine-Learning to Tackle Credibility on Twitter

When you use Twitter, how do you know when you are being presented with something credible instead of something totally bogus? The answer is, unless you spend a lot of time researching each tweet, you probably don’t. However, one thing is for certain, we rely on what we read on Twitter to be true.

Continue to read this blog by +Renette Youssef

What is the future of Data visualization and Dashboard solutions?

This article by Nilesh Jethwa is not about any futuristic "Iron Man style dashboard/data visualization product" where you are combing through holographic cubic chunks from your ultra fast Big Data pipeline.

Interview: Daqing Zhao, Macys.com on Advanced Analytics for Marketing in the Big Data era

KD Nuggets discusses Analytics at Macys.com, comparison of advanced analytics with traditional BI, building data models for scalability, problem of data models becoming quickly obsolete and challenges in customer targeting.

11 Stats that Prove Big Data is a Big Deal

Analytics have transformed the way we think about business. Big decisions were once made using a combination of precedent and instinct. Now, ease of accessibility is making analytics a critical component of any organization’s growth. From measuring productivity of workers to ROI of business initiatives, many companies have come to rely on analytics to track a variety of metrics—particularly big data, which is defined by Webster’s as “an accumulation of data that is too large and complex for processing by traditional database management tools.”

Continue to read at +Thinking Phone Networks

What Retailers Need To Know About Big Data

The “big data” hype rages on, especially for retailers anticipating the holiday shopping season. If you are among those hoping to find a sudden, near-miraculous solution to your data concerns, I have good news and bad news:
The good news is that big data is not a magic cure for sales woes. The bad news is that big data is not a magic cure for sales woes.

Continue to read on +BusinessIntelligence.com

Why You Need to Care About the 'Data Lake'

Have people been telling you to go jump in the lake recently? This may not be a bad thing—if it’s a data lake.

A “data lake,” by definition, is the opposite of silos or the structure of a data warehouse. Instead of taking the time to massage data so that it fits into a warehouse, a data lake just takes all the data in an unstructured form.

Continue to read on +Laserfiche

Big Data Traffic Spikes Drive IaaS Cloud Market

The global infrastructure-as-a-service (IaaS) may grow as much as 42.91 percent annually over the next five years, as growth-oriented companies try to keep their burgeoning technology costs under control, protect themselves from the risk of datacenter disasters, and manage Big Data traffic spikes, according to Infiniti Research.

Continue to read on +Information Management

Data science without statistics is possible, even desirable

Interesting blog post by +Vincent Granville where he starts with a controversial statement: data science barely uses statistical science and techniques. The truth is actually more nuanced, as explained further in the post.

Read it here.

IBM Launches Watson Analytics Cloud Service Beta

IBM wants to bring Watson -- the company's artificial intelligence platform -- to the masses. First known as a supercomputer of sorts, Watson technology is now rolling out in a range of easier-to-consume ways, including a Watson Analytics cloud service.

Continue to read on +Information Management

The Internet of Things (IoT) Will Grow To 40 Billion Devices By 2020: Are You Ready ?

The Internet of Things (IoT) can be defined as a scenario where objects, animals or people are provided with unique identifiers and the ability to transfer data over a network without requiring human to human or human to internet interaction. In the internet of things, a thing can be a person with a heart rate monitor implant, a farm animal with a biochip transponder or an automobile that has built-in sensors to alert the driver when the tire pressure is low.

Continue to read on +Dazeinfo - Startling Insights Of Tech Industry !

5 basic rules of data organization

Here +Vincent Granville  compares the 5 rules published in 1999, with the new 2014 version. Data has changed so much that the opposite rules are now followed. Yet many statisticians and big businesses still stick to the outdated rules.

Continue reading here.

Good Data Can’t Save Bad Marketing

Recently, a Harvard Business Review article suggested that the downfall of Tesco, a U.K. based grocery giant, was in part due to an overreliance on data-driven marketing practices. To be blunt, this idea is just wrong. Research shows that businesses effectively using customer analytics enjoy 10.5% year-over-year increase in annual company revenue, increase customer satisfaction by 8.1% annually – all the while increasing the number of positive social media mentions by 14.6% annually. But beyond these statistics, how do you explain the success of data-driven marketing giants like Amazon, Nordstrom, Dollar Shave Club, and other companies who consistently outperform their competitors through data-driven marketing practices? What’s more, the position taken by the HBR article doesn’t fully articulate the whole situation, as +Chuck Chapek Principal of JAC CRM Consulting notes:

Continue reading on +NewsCred

Transform Your Culture To Realize Big Data’s Full Potential

We are living in the era of big data, and those unable to adopt these approaches will be rapidly left behind. So the question for businesses today isn’t whether or not to use data science, the question is whether businesses can be taught to shift their people, processes, and vision into alignment with driving data science into their value proposition so that it is relevant and competitive.

Continue reading at +Data Informed

HP Boosts Big Data Cloud Amid SaaS Challenges

Hewlett-Packard continues to bolster its Big Data and cloud offerings, but the latest milestones also include a stark reality: HP's SaaS revenues are flat at a time when rival cloud companies enjoy ongoing double-digit growth.

Continue reading on +Information Management

Sisense 2015 predictions for BI, Big Data

Mobile devices, text analytics, Google Glass, and data intelligence will be key to the evolution of business intelligence in 2015 according to Adi Azaria and Eldad Farkash of SiSense.

Read at Sisense 2015 predictions for BI, Big Data

Nine Steps to Unlock Big Data's Hidden Value

No matter where you look, the numbers on big data are staggering. Among estimates of its potential benefits are productivity-led savings: $300 billion a year for the US healthcare industry; €250 billion for the European public sector; a 60 percent potential increase in retailers’ operating margins; and $600 billion in economic surplus for services enabled by personal-location data. However, these are just the early calculations coming in from a few sectors; they could well go higher.

Continue reading the article from +Information Management

Customer Insights, Big Data Analytics Will Sprawl in 2015

Forrester recently published its 2015 Predictions for Asia Pacific. I wanted to highlight some specific trends around customer insights (CI) and big data, two very hot topics for many AP-based organizations.

Continue reading this blog on +Information Management

Hackers with Wall Street Savvy Found to Be Stealing M&A Data

Hackers with Wall Street expertise have stolen merger-and-acquisition information from more than 80 companies for more than a year, according to security consultants who shared their findings with law enforcement.

Read more on +Information Management

8 tips for data analytics success from Data Strategy Symposium

Brands and big data experts share their advice on how you can improve your organisation's use of data to inform business strategy and drive success.

Read more from CMO

Where are big data and analytics heading in 2015?

Big data and analytics in 2015 will be less about collecting everything and anything and more about focusing on the most relevant data for actionable insights. More organisations will also look at how machine generated data can add value to their business, not just data coming from customers or employees, according to analysts.

Continue to read on +CIO

The Surprising Industries Making Use Of Big Data Analytics

Anyone who stays current on tech trends knows that big data is changing the way many business leaders are running their organizations. The specific industries currently incorporating this emerging tool more than any other seem to be healthcare and retail, by a landslide. However, we are seeing more and more niche industries making use of big data and its ever-increasing benefits.

Continue reading on +BusinessIntelligence.com

Hacking the hackers with Big Data

When researchers uncovered cyber attacks on a range of US-based think-tanks earlier this year, they didn’t rely on typical detection techniques. If they had, they might have let the perpetrators slip away, as the attackers weren’t using typical hacker tools that traditional anti-virus protection would detect.

Article here from +Raconteur

6 Tips for Landing a Job in the Big Data Industry

The information explosion is driving demand for qualified individuals in the booming Big Data industry. According to a recent study by the UK-based business analytics company SAS Institute, the number of employees that organizations will need to carry out Big Data tasks is expected to grow by more than 240 percent by 2017. What does that number mean for the U.S.? As more and more companies turn to Big Data analytics platforms such as cloud-based Hadoop to collect, manage and mine mountains of rich data for competitive advantage, the demand for Big Data employees will dramatically outpace supply. According to a 2011 report published by McKinsey & Co., by 2018 the U.S. could “face a shortage of 140,000 to 190,000 people with deep analytical skills, as well as 1.5 million managers and analysts with the know-how to use the analysis of Big Data to make effective decisions.” This huge talent gap represents a tremendous opportunity for those looking to pursue a career in the booming Big Data industry, provided they have the right qualifications. Based on a review of credible online sources that outline the qualifications Big Data employers are looking for in new hires, here are 6 tips for landing a job in the Big Data industry.

Continue reading at +Datafloq

How Big Will The Internet of Things Be?

2014 was the year of Big Data, 2015 will be the year of the Internet of Things. More and more every day items are being connected to the Internet ranging from smart thermostats to smart toothbrushes. In the coming years, the amount of smart devices in our household could grow drastically as Gartner predicts that a typical home could contain more than 500 smart devices by 2022. The falling costs of sensors and the upcoming domotica platforms such as Apple’s Homekit will contribute to this growth. However, this is just the beginning. IDC expects the market for the Internet of Things to grow to $ 3 trillion by 2020, Garnter even predicts a $ 14 trillion market in 2022. So how big will the Internet of Things actually be?

Continue reading at +Datafloq

Data analytics for HR: how to make effective recruitment.

In his book Drive, management author Daniel Pink talks about the disconnect between “what science is telling us and what businesses do”. He refers to employee motivation and how organisations use various incentives, especially monetarist, to motivate people. Conversely, there is a body of research that shows that such ‘extrinsic motivators’ actually have an adverse effect on employee motivation.

Read more of this blog from +PromptCloud

HP Big Data, Cloud Sales Don't Completely Fill Revenue Void

Hewlett-Packard continues to invest in Big Data and cloud computing, but sales apparently haven't grown fast enough to offset weaknesses across HP's services, printing and enterprise businesses. HP CEO Meg Whitman and several other executive team members described the state of HP during the company's Q4 earnings call earlier this week.

Read more at +Information Management

Integrated Big Data Analytics approach to Sustained Economic Value Creation for CSPs

A telecom operator is a ‘natural’ Big Data factory. Huge volume of data is generated each second as part of its business-as-usual processes and what is more – all this data is generated, captured and available in real-time and digital form by default. This is unlike any other industry – healthcare, retail or public sector – where data has to be purposefully captured and then converted to digital form. Increasing connectivity, faster networks, and growth of connected devices and subscribers, all continue to multiply the volume and variety of data.

Read more at +Flytxt

High versus low-level data science

Here I describe a case study: a solution based on high-level data science. By high level, I mean data science not done by statisticians, but by decision makers accessing, digging into, and understanding summary (dashboard) data to quickly make a business decision with immediate financial impact. There is also a section on smart imputation techniques, with patentable, open intellectual property that we created after investigating this problem.

Continue reading well thought out blog by +Vincent Granville

How IT Will Change Healthcare Patient Engagement

As the healthcare industry depends increasingly on software to drive the change to value-based care from transaction-based compensation, the future of global healthcare is increasingly bound to the technology that will deliver.

Read blog from +Information Management

Bringing Silicon Valley to the ICU: My Vision of Data for Good By Rob Seaman

Any parent can relate to the anxiety of being encharged with a newborn completely dependent on you yet unable to communicate its needs. This worry is amplified when your baby is born prematurely and spends its first few weeks of life in the Intensive Care Nursery hooked up to cardiorespiratory monitors.

Here’s the thing about cardiorespiratory monitors. These devices track a newborn’s heart rate, breathing rate and oxygenation so that nurses can attend to health problems like apnea and bradycardia and parents can rest assured that their kid is okay.

Continue reading article at +WibiData

Meet IBM Watson's Potential Rival

+Sentient Technologies , a potential IBM Watson rival focused on artificial intelligence, machine learning and big data, has raised $103.5 million in Series C funding.

Key financial backers include Access Industries, Tata Communications (Hong Kong), Horizons Ventures, and a group of private investors. ""Making sense of massive amounts of data is critical for consumer-facing digital businesses,” said Jörg Mohaupt from Access Industries, in a prepared statement.

Article from +Information Management

Big Data Top Trends in 2015

Big Data has seen a huge leap forward in 2014 regarding how it has been represented and used across companies. The adoption rates have grown and the importance of Big Data as a business function has increased, but what are we going to see in 2015?

Article from +Innovation Enterprise 

Why technology and content are inseparable at Netflix

Neil Hunt is the chief product officer at Netflix, and his job entails a lot more than it might sound like. The end product at Netflix is the video streaming through our iPads or smart televisions, but what we’re watching and we’re seeing it is result of a lot of work.

Article from +gigaom

How Can Big Data Drive Growth Of Business Enterprises?

The world is a huge storehouse of structured and unstructured data that extends well into the range of petabytes and zetabytes. Business enterprises usually have such large repositories of data related to their business processes, customer information, evolving market trends along with data coming in from an enterprise's social media streams. In such a scenario, business enterprises can utilize predictive and big data analytics to make informed decisions to facilitate the creation of multi-dimensional customer services and to enhance their productivity.

Read more on +hostReview

Google demos how to get the most out of analytics

Google has launched a new website to help developers gain more insight into their applications. Google Analytics Demos & Tools aims to give experienced developers the ability to be more productive and improve their business through Google Analytics and advanced measurements.

Article on +SD Times

Industry Watch: Four areas to watch for Big Data innovation

The industry has reached an inflection point in our thinking about data. It’s no longer about slicing and dicing data sets; it’s now about creating insights.

Article from +SD Times