Engineering’s Dirty Little Secret… Data Shows That Women Experience 6.5x Less Stable Wages Than Male Counterparts

America is the “land of the free and home of the brave”! Equal rights for all, no? Isn’t that the message that media puts out? Aren’t these the messages we’ve all been told about the good old US of A?

Continue reading here by +Lillian Pierson

The Big Data Challenge Isn't The Needle In The Haystack -- It's The Haystack

A lot of the buzz around big data, analytics and insights has been focused on finding the proverbial needle in the haystack. You figure out what you want to know, and you analyze the data available to you to find the answer.

Continue reading here on +Forbes

Under the Hood of Revenue-Based A/B Tests Parts 1 and 2

It’s been quite a while since marketers first adopted A/B testing for their website optimization, making it an integral part of their best-practices toolbox. In most A/B tests, marketers aim to optimize the CTR of some element on the page – a rather short-term and easy to measure goal. However, the ultimate goal is, of course, to increase revenue.

Read part 1 here on +Dynamic Yield

Read Part 2 here on +Dynamic Yield

Dear John: Your flight is delayed — Personalizing the travel experience with big data

This past summer a major airline was briefly the butt of press and social media jokes and criticisms when it mistakenly sent a response to an unsatisfied customer’s complaint that started with the generic salutation “Dear CUSTOMER NAME:”. The letter continued with a canned apology which contained references to a SPECIFIC INCIDENT, and concluded with a promise that the airline truly appreciated CUSTOMER NAME’s loyalty and business.

Continue reading here on +VentureBeat

How C-Level Executives Really Feel About Big Data

As big data begins to inform decision-making at every level of the organization, C-level executives have entered a dynamic environment that explores how data analytics translate into business value. Some executives appear more confident than others in the capabilities of big data, prompting us to ask: Who’s big on big data?

Continue to read here on +BusinessIntelligence.com

Why 2015 Will Be a Banner Year for Information Governance

For many years information governance failed to achieve many of its goals primarily because document classification, which is the necessary first step in nearly all IG initiatives, has proven difficult to achieve on an enterprise scale. No more. 2015 marks the beginning of a whole new era.

Continue reading here on +Beyond Recognition

5 Reasons Your CEO Prefers Data On A Dashboard

The days of CEOs waiting hours for the delivery of a paper report are long gone. Now, many forward-thinking executives are making use of visual dashboards to gain insight into their company, rather than relying on CIOs or IT professionals to do it for them.

Read here on +BusinessIntelligence.com

Big Data Projects: How to Choose NoSQL Databases

So, you've succumbed to the buzz and now you're looking around trying to make heads or tails of the mass amounts of information out there hyped up as "big data." Or perhaps you’re even ready to start your own internal project to get your existing applications on the bandwagon. In either case, terrific! Your decision is a good one.

Continue to read here on +Information Management

Data Science Handbook - free first three chapters

The Data Science Handbook -- it's a collection of honest interviews with 25 premier data scientists, discussing career success, life philosophies and unconventional truths.

They are giving out the first 3 chapters for free to everyone (get it at the link below), featuring interviews with:
DJ Patil - former LinkedIn Data Science team lead and co-creator of the term 'data scientist'
Clare Corthell - creator of The Open Source Data Science Masters, and current data scientist
Michelangelo D'Agostino - former data scientist on the Obama 2012 campaign, and current data scientist at Civis Analytics

Get your copy here.

Understanding Data Science as a Service

Big data is here to stay. Organizations have more data than ever before, and in a world overloaded with information, it’s hard to imagine working with a data set that isn't “big” anymore.

Read more here on +Data Informed

10 Social Data Resolutions to Be a Better Marketer This Year

As a social media practitioner and marketer, you are no doubt swamped with various types of data on a daily basis. Even for seasoned marketers or advanced practitioners in this field, it can get overwhelming. Most of the time, there’s an abundance of data, but you might have a lack in resources or capabilities that will allow you to make meaningful sense of your data-gathering efforts.

Continue reading here on +Infinit Datum

Inside the Apache Software Foundation’s Flink

The Apache Software Foundation has announced Apache Flink as a Top-Level Project (TLP).

Flink is an open-source Big Data system that fuses processing and analysis of both batch and streaming data. The data-processing engine, which offers APIs in Java and Scala as well as specialized APIs for graph processing, is presented as an alternative to Hadoop’s MapReduce component with its own runtime. Yet the system still provides access to Hadoop’s distributed file system and YARN resource manager.

Continue reading here on +SD Times

Social Data: Why Marketers Should Proceed With Caution

“The world has witnessed two revolutions in the way consumer data has been solicited and collected,” wrote Amazon’s Andreas Weigend in 2009. “Today, the online world has shifted to a model of collaboration and explicit data creation.”

Continue reading here at +BusinessIntelligence.com

Big Data Underwriting for Payday Loans

ZestFinance traces its origins to a phone call Douglas Merrill received one winter day from his sister-in-law, Victoria, who needed new snow tires to drive to work and was short of cash. When Mr. Merrill asked what she would have done had she not been able to reach him, she replied that she would have taken out a “payday loan.”

Continue reading here on +The New York Times

Big data initiatives not quite delivering yet, survey shows

Capgemini survey of 225 companies shows disappointing results for big data efforts so far; but there is movement to the cloud.

Big data is seen as the ticket to competitiveness for today and the years ahead in an intensely competitive global economy. The ability to capture data on transactions, customer preferences, and product adoption, and then be able to predict where things are going, will help organizations lead the way within their industry groups.

Continue reading here on +ZDNet

Capturing the Business Value of Big Data in Real Time

Harnessing the power of big data analytics to create value is now considered a crucial component of any sound business development program. In fact, IDC estimates that worldwide spending on big data-related software, hardware, and services will grow to $125 billion in 2015.

Continue reading here on +Data Informed

Get Ready for BI Change

To compete in today's global economy, businesses and governments need agility and the ability to adapt quickly to change. And what about internal adoption to roll out enterprise-grade Business Intelligence (BI)applications?

BI change is ongoing; often, many things change concurrently.

Continue reading here on +Information Management

Three Ways Big Data Is Helping To Build Better Cars

Not long ago, a friend jokingly asked me “What happened to all the “lemons”? He didn’t mean the kind found in the fruit aisle. He was talking about the kinds of cars made in the 1970s that were so poorly built that they needed repairs practically as soon as they rolled off the assembly line.

Continue reading here on +Forbes

5 areas for making cognitive computing robust

Voice activation, visualisation, and context awareness need to be further implemented so interaction feels more natural to humans, IBM says.

Continue reading here on +CIO

What you missed in Big Data: mining value from unstructured data

The enterprise analytics crowd kicked off the new year with a string of major developments aimed at addressing the explosion in use cases for unstructured data over the past 12 months. FoundationDB Inc. set the train in motion on Monday after revealing plans to expand its namesake key-value store with a new component for exposing information as objects.

Continue reading here on +Silicon ANGLE

The Basics of Oracle Statistics

Databases uses statistics about data to determine the best way to query tables. Should the database seek or scan? How many rows will be returned from tables that are being joined? Oracle is no exception, but the way Oracle treats statistics is different from SQL Server.

Continue reading here by +Jeremiah Peschka

Top 14 Big Data Books of 2014

2014 has been a huge year in big data- and big data publishing. Viktor Mayer-Schoenberger and Kenneth Cukier re-published and added an extra chapter to their bestselling “Big Data”; Nate Silver graced the publishing world with his presence once more with the Best American Infographics of 2014. We’ve compiled a list of the most insightful, beautiful, thought-provoking and challenging books on big data this year. Whether you’re a casual data enthusiast or a hardcore statistician, you’re sure to find a book among our selections to add to your Christmas Wishlist.

Read the list here on +Dataconomy

5 Data Fails in 2014

When it comes to data breaches, leaks and blunders, 2014 had more than its fair share. Many major brands took data-related hits that became PR nightmares, scrambling marketing departments into damage control mode as they tried to repair tarnished images.

In the spirit of learning from past mistakes so as not to repeat them, here’s a look at some of last year’s standout data fails and what advertisers/marketers can do to avoid them.

Continue reading here on +Datafloq

How Cloud Technology Influenced Data Management

While it is common to think of cloud computing as a recent technological development, the origins of cloud technology can be traced back over six decades.

This blog entry explains about how cloud technology and data management collide.

The 12+ Unmissable Big Data Stories of the Past Year

2014 was an eventful year for those of us watching for the impact that big data is having on society.

While 2013 brought an explosion of awareness around big data, 2014 showed the market for big data services beginning to mature. We also saw how “datafication” is starting to impact the lives of more and more people around the world.

Continue reading here from +Bernard Marr

Research Leaders on Data Mining, Data Science, and Big Data key trends, top papers

+KD Nuggets  asked global research leaders in Data Science and Big Data what are the most interesting research papers/advances of 2014 and what are the key trends they see in 2015. Here are their answers.

Free Ebook - Data Driven Creating a Data Culture

Succeeding with data isn't just a matter of putting Hadoop in your machine room, or hiring some physicists with crazy math skills. It requires you to develop a data culture that involves people throughout the organization. In this O’Reilly report, DJ Patil and Hilary Mason outline the steps you need to take if your company is to be truly data-driven—including the questions you should ask and the methods you should adopt.

Get it here.

Data Acceleration: Turning Technology Into Solutions

In this article, the author outlines four fundamental combinations of components to create solutions that enable data movement, processing and interactivity at high speed.

Read the article here on +Information Management

Best Data Vizualization and Dashboard Management Practices in Self Service BI Programs

This article goes through and makes some recommendations on best practices in best practices in Self Service BI Programs.  He comes up with a few good suggestions.

Read here from +Isaac Sacolick

Measuring the Smart City

The 6 dimensions identified that make it possible to coordinate a SC are the following: Smart Environment, Smart Mobility, Smart Governance, Smart Economy, Smart People and Smart Living

Measuring the management model requires systems to control efficacy and efficiency. This makes it relevant to distinguish between resources, activities and impact.

Continue reading here on +Smart Cities

NASA’s 10 rules for developing safety-critical code

NASA’s been writing mission-critical software for space exploration for decades, and now the organization is turning those guidelines into a coding standard for the software development industry.

Continue reading here on +SD Times

Personal Healthcare Data: Patients Will Take Control

Eric Topol, M.D., chief academic officer of Scripps Health in San Diego, is many things. He is a practicing cardiologist, a geneticist, a researcher, and a bestselling author. Health Data Management spoke to Topol about his latest book and the future of medicine.

Read about it here on +Information Management

SLIDESHOW: 10 Internet of Things (IoT) Trends & Considerations

The Internet of Things (IoT) certainly earns plenty of headlines. Now, it’s time for a reality check. Here’s a look at key IoT definitions, market forecasts, potential standards and challenges facing CIOs, chief data officers (CDOs) and those who hope to make business sense of data from all types of devices.

Look at the slideshow here on +Information Management

Data Science And Statistics: Colleges Must Evolve

Inquidia recently completed our seventh season of college recruiting, interviewing 30 candidates from three top universities, ultimately hiring two Spring 2015 grads. The newbies include a natural sciences major and a joint econ/computer science student.

Continue reading here on +Information Management 

Why Once-Successful Companies Fail

How can one explain why seemingly successful companies, such as Borders, Blockbuster, Circuit City, Wang Labs and Digital Equipment, go bankrupt or fall from a successful leadership position? I find it fascinating that almost half of the roughly 25 companies that passed the rigorous tests to be listed in the once-famous book by Tom Peters and Robert Waterman, In Search of Excellence, today either no longer exist, are in bankruptcy, or have performed poorly.

Continue reading this blog on +Information Management

Hadoop Isn't for Everyone

f you think you can do big data in-house, get ready for a lot of disappointment. If the data you want to analyze is in the terabytes in size, comes from multiple sources -- streams in from customers, devices or sensors -- and the insights you need are more complex than basic trending, you are probably looking for a data scientist or two. You probably have an open job requisition for an Hadoop expert as well and have hit the limit on what your capital budget will let you buy to house all this data and insights. Thus you are likely taking a hard look at some cloud-based options to fill your short term needs.

Continue reading this blog on +Information Management

Next Shift: From Big Data to Deep Data

It’s no secret that today’s consumer looks and acts differently than the consumer of fifteen years ago. While in the past, consumers may have been satisfied with standardized services and solutions that matched those of their neighbors, friends or acquaintances, people now expect products and services that best fit theirindividual needs and interests.

Continue reading here on +Information Management

5 Ways Big Data Will Be Bigger in 2015

Big Data. It’s a buzzword uttered by both industry experts and business professionals; a marketing term and industry description bandied about by techies and creative types alike. Everyone acknowledges how important it is and its unlimited potential in affecting how decisions are made in various areas of our lives.

Continue reading here on +Infinit Datum

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

11 Clever Methods of Overfitting and how to avoid them

Overfitting is the bane of Data Science in the age of Big Data. John Langford reviews "clever" methods of overfitting, including traditional, parameter tweak, brittle measures, bad statistics, human-loop overfitting, and gives suggestions and directions for avoiding overfitting.

Continue reading here on KD Nuggets

Big Data Paves Way for Hyper Smart Transportation Era

Big data and virtualization will dominate the coming “hyper smart” transportation era, according to a new report from ABI Research.

Continue reading here on +Information Management

Taking Big Data to the street in 2014

This was the last year in which Big Data was an off-the-street term. As the year ended, Hortonworks was preparing to go public, with Cloudera preparing for the same outcome. Big Data will officially transition into being a big business this year.

Continue reading here on +SD Times .

A blended approach to managing data

Making the case for version control, testing environments and continuous integration when it comes to software development these days is a no brainer. But when it comes to the data behind your important applications, life-cycle management and data flow automation are still new ideas struggling to find their place in the market.

Continue reading here on +SD Times

Three Big Data New Year's resolutions organisations should make

The New Year has started and 2015 promises to be a big year for Big Data and everything that is linked with Big Data. The Internet of Things is expected to take of dramatically this year, Big Data Security Analytics will become common language in the Boardroom and the available data in the world will grow with another 8 Zettabyte this year. 2015 will therefore be an exciting year when talking Big Data and organizations should be ready for the data revolution we are already facing. Therefore, here are three Big Data New Year's resolutions organizations should make in order to stay ahead of the pack and be ready for a data-driven economy.

Continue reading here on +Datafloq

Get started with Hadoop and Spark in 10 minutes

With the big 3 Hadoop vendors – Cloudera, Hortonworks and MapR - each providing their own Hadoop sandbox virtual machines (VMs), trying out Hadoop today has become extremely easy. For a developer, it is extremely useful to download and get started with one of these VMs and try out Hadoop to practice data science right away.

Continue reading this blog by Maloy Manna on Data Science Central

How Facebook uses Hadoop and Hive

Facebook is one of Hadoop and big data’s biggest champions, and it claims to operate the largest single Hadoop Distributed Filesystem (HDFS) cluster anywhere, with more than 100 petabytes of disk space in a single system as of July 2012.Facebook runs the world’s largest Hadoop cluster. Just one of several Hadoop clusters operated by the company spans more than 4,000 machines, Facebook deployed Facebook Messages,its first ever user-facing application built on the Apache Hadoop platform.Apache HBase is a database-like layer built on Hadoop designed to support billions of messages per day.

Continue reading here from +Ashwani Agarwal

Big Data Analytics For Smart Mobility In The 21st Century

There’s nothing more irritating than being stuck in the middle of a traffic jam. When you have places to go and things to do, traffic jams can cause you to be delayed to the point of being late by several hours. But have you ever wondered exactly what the cause of traffic jams is? Mathematicians have uncovered three main theories to explain it. Traffic jams are caused by factors such as saturation, weather, and roadwork. So, what are the countermeasures? Bigger, wider roads, bus lanes, reversible lanes? Maybe we should reach out to Technology to help us out.

Continue reading this post from Errol S. van Engelen here

SLIDESHOW: 10 Big Data Experts to Know

Which executives, entrepreneurs and experts are shaping the Big Data market? +Information Management  tracks the names and personalities you need to know. Here’s their latest update.

3 Ways Santa Claus Uses Big Data This Holiday Season

The holiday season operation is a big deal for Santa Claus. Getting the wide range of presents to kids all over the world is a complex operation that needs to be carried out within just a few days. Of course, nothing can go wrong, as that would significantly depress kids and their parents. Fortunately he can turn to Big Data to drive his different operations, which range from personalization of presents, inventory management and of course elf resources.

Continue to read here on the Smart Data Collective

Why You Cannot Do Big Data Without SQL

It was quite interesting to gloss over a recent article from Business Insider, which remarked on the comeback of SQL (Structured Query Language) as a core programming language despite its decline in recent years. In many ways, I can't say I'm surprised. Since the late 1970s, SQL has served as the primary language for sorting of data in a logical fashion.

Continue reading here on +First Class Analytics

The 2 Types Of Data Scientists Everyone Should Know About

It depends entirely on how broadly you categorize them. In reality, of course – there are as many “types” of data scientist as there are people working in data science. I’ve worked with a lot, and have yet to meet two who are identical.

Continue reading this blog by Bernard Marr on Data Science Central.

Questions About Pivoting Data in SQL Server You Were Too Shy to Ask

Of all the basic SQL operations, the pivot seems to cause the most problems. We can tell from the way that old articles on Simple-Talk on the topic continue to be read. It turns out that there are several questions that come to mind while learning about pivoting, but which are seldom asked on forums. Once more, Robert Sheldon attempts to answer these unspoken questions here.

Archiving Hierarchical, Deleted Transactions Using XML

When you delete a business transaction from the database, there are times when you might want to keep a record of the data for posterity. This can become somewhat complicated if the transaction you need to delete is in a table that is the parent of a deeply nested hierarchy of dependent tables based on the foreign key relationships. In this article, Dwain Camps looks at a tidy means of doing just that here.

Where Big Data, Software Defined Still Struggle

Instead of predicting what will happen in the technology industry for the rest of this year, +Satyam Vaghani is taking a different approach -- pointing out what won't happen. As he look's into his crystal ball, here are his UNpredictions for the rest of 2015 as well as some tips for success:

Read here on +Information Management

Leave Some Room for the 'Nice to Have' Data

One of the themes that pops up in All Analytics community discussions on a pretty regular basis is the issue of how much data an enterprise analytics team should collect and store, and how long the team should retain it.

Continue reading here on +UBM AllAnalytics

Big Data Knows When You're Going to Quit Your Job Before You Do

Good bosses have an uncanny ability to sense when employees are unhappy and work with them to fix problems in the office before it’s too late. At VMware in Silicon Valley, they let the machines figure it out.

Continue reading here on +Information Management

Understanding Dimensionality Reduction- Principal Component Analysis And Singular Value Decomposition

Interesting blog from +Manu Jeevan Prakash about principal component analysis (PCA) and singluar value decomposition (SVD).

I like this tutorial on how to calculate SVC here from MIT and if you want to understand Eigenvalues there the wikipedia page is a good as source of information.

Subscribe to Data Informed Experts Share their Big Data Resolutions for the New Year

+Data Informed asked several experts about their big data resolutions for 2015. Their experts covered a wide range of areas, from emerging trends to aligning data with business goals to the terminology they resolve to use.

Read them here on +Data Informed

SLIDESHOW - 10 Business Analytics Predictions for 2015

Where is the business analytics industry heading in 2015? The International Institute of Analytics offers up these 10 potential trends to watch.

Go here to see the slideshow on +Information Management

I particularly dislike #9 which says Analytics, machine learning and cognitive computing will increasingly take over the jobs of knowledge workers.

Statisticians have a biased view on data science

Most statisticians are great professionals, working on various data-intensive projects, and they don't care about their job title. You can say the same about data scientists. However, there is a small cluster of statisticians - Andrew Gelman seems to be their leader and their only influencer - who have been challenging data scientists, even publicly insulting them recently, as their demise seems imminent.

Read about it here from +Vincent Granville in his blog on Data Science Cental

Data Science vs. Analytics?

Interesting post from +Dashboard Insight where Piyanka Jain, CEO of  +Aryng  writes on the difference between data science and data analytics from their standpoint.

I have to agree sometimes it can be a little hard to distinguish between the two and often the difference is down to semantics or a personal difference in definition.

T-SQL COALESCE Example

SQL Server T-SQL coalesce simplifies the use of a case statement to find the first non-null value of your expression.

Excellent short blog from Derek Wilson on +SQLServerCentral

Microsoft Previews Power BI Dashboards

An update will enable personalized dashboards and deliver insights from popular third-party SaaS applications.

Power BI, Microsoft's cloud-based, self-service business intelligence toolset, is gaining new features that are aimed at helping users get an at-a-glance view of more of their data—and from more sources.

Continue reading here on +eWEEK.com