Crazy Data Science Tutorial: Classification and Clustering

This blog post from Randal Scott King on Classification and sub-dividing them.

A useful place to start.

Dilbert's 20 funniest cartoons on Big Data

This post from +Big Data Made Simple is a good source of Big Data laughs.

Top 10 categories for Big Data sources and mining technologies

This article is on +ZDNet and looks at the types of data and suggests tools to use to look at  it.

A good starting point.

Visual Document Classification: Changing the Dynamics of Information Governance

This article is on +Forbes is by +Ben Kerschberg discusses a new way of classifying documents.

It looks interesting and any method that makes it easy to classify documents gets my vote :-)

A Spark for Analytics

This article on +Information Management looks at Spark and that it is a good basis for Analytics.

Could be a good predictor as to how things are going to go.

5 controversies and debates around Big Data

This article is on +Big Data Made Simple and summarises 5 of the big controversies or debates around Big Data.

How to build and lead a winning Data Team

This e-book is available from +Data Informed

9 Questions to Determine If a BI Solution Is Truly Self-Service

This article by Evan Castle was shared by +Elana Roth Katzor  and looks at how to determine if a BI solution is really self-service.

American Exceptionalism in Data Management

This article by +Henrik Liliendahl Sørensen discusses some of the data differences for American data.

I have to admit to finding it a little odd having to translate temperatures to Fahrenheit when talking to US based friends.

From the field to the cloud, SAP champions big data as new MVP in sports

This article from +ZDNet looks at how big data is just as useful for fans as it is for customers.

A nice use for big data.

Big Data's Effect on Organ Transplant Wait Lists

This article on the +Mashable website looks at a positive effect from Big Data.

I think it would be a better solution to get more people to agree to organ donation or change the presumption to agree to it.

Google et al slammed by justice chief over 'right to be forgotten'

This article by +Naked Security explores the recent right to be forgotten and opposition to it.

To be honest I'm not sure it is very effective when you can use an IP proxy to pretend to not be in Europe in order to see things.

Sturgeon’s Law, Big Data and the New Literacy

This is an interesting blog on the +Information Management website looking at big data.

I have to say I think it is big literacy.

New Tools Help Neuroscientists Analyze Big Data

This article from +Neuroscience News looks at a new way to process big data for Neuroscience.

For Big-Data Scientists, ‘Janitor Work’ Is Key Hurdle to Insights

This article from the +The New York Times points out how much time is spent collecting and preparing data.

I have to agree - it takes forever (it feels) to cleans and format the data so that it can provide useful insights.  However the skill in doing this is key to getting the best insights from it.

Big data is an opportunity to win more customers

This article from +Washington Post discusses how big data is a new way to win more customers.

Comparison of statistical software

A comparison between R, MATLAB, SAS, STATA and SPSS.

15 ways to prevent data security breaches

This article from +Big Data Made Simple reminds us all some steps to take to make our data safe.

What Makes a Good Chief Data Officer?

What Makes a Good Chief Data Officer?

Interesting thoughts from +BigDataStartups.

How The European Union Is Helping Its Citizens Cope With Big Data

This article on the +CloudTweaks website by Daniel Price discusses the project.

An interesting way for them to make our lives easier I guess.

Google whips up a Chrome app to let data scientists work together

This article on +VentureBeat discusses the announcement in the Google Research blog about a new service some of its employees worked on called CoLaboratory. By downloading the app for the Chrome browser, you instantly get the IPython open-source software for interactive computing, as well as multiple Python libraries.

Interesting.

Lost in Data Translation? Forrester's Data Taxonomy to the Rescue

This article on +Information Management discusses that Forrester just created a Data Taxonomy - a collection of 55 components, organized by four categories (data, data processes, data interactions, data interaction channels), with up to four levels of subcategories and about 100 attributes and aliases describing the components. Obviously for a price.

Prototype real-time dashboard using Big Data - London

This is a prototype dashboard by some folks at +UCL and covers some UK cities - this link is to the one for London.

Pretty neat.

Three Personal Finance Tips From Big Data

In this interesting article from Simon Moore on +Forbes he puts a new spin on three common personal finance money saving tips.

The Internet of Things: What's Possible vs. What's Practical?

This article by Don DeLoach on Data Informed discusses how IoT is transforming over time from just being possible to being practical.  So the future is looking more exciting.

How big data challenges corporate culture

In this article on +TechRepublic It discusses how big data and the Internet of Things (IoT) can help businesses get a "360 degree" view of their customers, but not without a conscious effort to fight old patterns of corporate resistance

Where HP Vertica fits in the Big Data continuum

This article on +SiliconANGLE as part of coverage of this year’s HP Vertica event discusses the move of resources from data management to HADOOP and other similar areas.

Interesting perspective.

Ontologies versus Data Models

This article on +Information Management by Malcolm Chisholm and is a fascinating look at the benefits and features of both.

Whilst I can see that Ontologies are a better fit for non-relational database data, most organisations will only focus on having a data model and not an ontology.

3 Ways to Become a Data Scientist

This article is written by +Linda Burtch and is on the SmartData Collective website.

An interesting perspective.

Most influential research papers every data scientist should read

This list has been pulled together on the +Big Data Made Simple site.

I actually quite enjoyed reading the last one on the list - top 10 algorithms for Data Mining.

Google's latest big-data tool, Mesa, aims for speed

In this article from +PC World they discuss how Google has found a way to stretch a data warehouse across multiple data centres, using an architecture its engineers developed that could pave the way for much larger, more reliable and more responsive cloud-based analysis systems.

It all sounds very impressive and exciting however I'm not sure who needs what this delivers.

The 9 Best Languages For Crunching Data

This article on +Fast Co.Labs lists the 9 best languages for crunching data.

Makes me glad for the time I spend learning R as it's the first on in their list.

Confusion Surfaces About the Data Lake

This article on +Information Management discusses how data lakes lack semantic consistency and governed metadata so business users are finding it hard to utilise them properly.

The Partnership Between Gamification And Data

This article discusses the partnership between gamification (Gamification borrows the characteristics of games and applies them to non-game contexts) and data.

An example of this would be any test that you can compete against a threshold so you can measure improvement and reward accordingly.

Energy Industry Big Spender for Big Data

This article on +Information Management discusses a new study from ABI Research which says that the Energy Industry is a big spender on big data.

Getting Organizations Ready for Big Data

In this article on +Information Management Fern Halper and Krish Krishnan discuss the assessment needed to get an organisation ready for big data.

The assessment link near the bottom of the article doesn't work - to do the Big Data Maturity Model go to this link.  It consists of approximately 50 questions across five categories.

Data-Driven Illusions

This blog post from Jim Harris on +Information Management discusses not being too data driven which can be the result of the focusing illusion oversimplifying a complex challenge

Integrating and governing big data

This white paper is sponsored by +IBM Big Data & Analytics.

In it they describe best practices for integration and use IBM's InfoSphere product to explain some of the things we should be doing with our big data.

If you can ignore the marketing it is actually an informative white paper with some insights useful for everyone.

Hadoop vs. Data Warehouse: Comparing Apples to Oranges?

In this article on +Data Informed Dan Graham from +Teradata talks about the differences between Hadoop, a Data Warehouse and a Data Mart.

He is quite right - Hadoop is not going to replace a data warehouse - it can be used for specific big data projects but cost will never make it cheap enough to replace a data warehouse.

7 Big Data Solutions Try To Reshape Healthcare

This article from +InformationWeek by +Paul Cerrato looks at 7 Healthcare Providers who are already using Big Data.

To Achieve Big Data's Potential, Get it Into the Boardroom

This article from Bill Schmarzo on +Entrepreneur points out that the business needs to direct the usage of big data at the right area of the business to get the best and biggest benefit.

Add to that this article from Stephanie Overby on CIO.COM on The CIO and CMO Perspective on Big Data and you can see that big data needs board level attention.

Dissecting data quality by understanding disparate sources

This article by +Experian Data Quality discusses a few of the potential problems with data quality when data comes from many sources.

I have to agree that you need to get back to the true source of the data but also make sure that it is kept up to date.  If you can't keep it up to date then only use recent data.

Hadoop Is Not a Data Integration Solution

In this report from +Gartner, Inc. it explains how as use of the Hadoop stack continues to grow, organisations are asking if it is a suitable solution for data integration. Today, the answer is no. Not only are many key data integration capabilities immature or missing from the stack, but many have not been addressed in current projects.

Big Data; Using Google Searches To Predict Stock Market Falls

This article by Tim Worstall on +Forbes he includes links to papers and reports that point to the assertion that people search for information on business and financial news/information just before the stock market falls.

An interesting viewpoint which I think would need a bit more analysis in order to turn that around to be able to predict it.

Data Supply Chain: Putting Information into Circulation

This article on the +Information Management by Narendra Mulani from +Accenture explains some steps on how to set up a data supply chain.

I agree that this is something that all smart organisations should be setting up before we have even more data silos.

10 things you shouldn't expect big data to do

This article by Mary Shacklett on +Tech Republic is worth a read just to reset some expectations when doing a Big Data project.

What does Big Data mean for banks?

This article by Michael Flynn on +Bank Systems & Technology discusses why banks are struggling with Big Data.

The SQL of Membership: Equivalence Classes & Cliques

In this excellent article by Joe Celko on how to try and use SQL to do set theory.

I agree with him - it is clunky and awkward and far easier to do with a graph database.

What's new in Oracle 12.1.0.2

Details in this article by +Jeremiah Peschka.

I like the increased focus on data warehousing and the increased use of caching (although that needs to be done carefully).

The need for UPDATE locks in SQL SERVER

+Klaus Aschenbrenner explains why on his website.

I agree with him completely.

The law of series: why 4 plane crashing in 6 months is a coincidence

In this interesting blog entry by +Vincent Granville discusses some statistical ways to look at the recent plane crashes.  Password is 5150 

Well worth time to review.

Impact of Big Data on Social Media Marketing

This article from +Online Social Media talks about the volume of data and that much of it is only 2 years old.

I can see that marketing will become more cost effective from recent data and that social media can make it more worthwhile.

Big Data in Science

This blog entry on +PromptCloud looks at how Big Data is used in Science and the possible problems that can be encountered.

Huge Trello List of Great Data Science Resources

This blog entry by +Kai Xin Thia on Data Science Central points to a huge list of resources collected over many years.

A great resource and a great place to start from.  Thank you so much for doing and publishing this.

Hiring With Science: Big Data Brings Better Recruits

This article in +Forbes by +Emma Byrne looks at how Big Data can help you pay real market salaries, and increase your diversity.

How Drones And Big Data Are Creating Winds Of Change For Hurricane Forecasts

This article in +Forbes looks at how Drones and Big Data are creating winds of change for Hurricane Forecasts.

A fascinating use of Big Data for sure.

Pivotal and Hortonworks collaborate on Ambari for enterprise HADOOP

In +ZDNet this article by +Natalie Gagliordi she notes that Pivotal has said it will dedicate engineers to contribute installation, configuration and management capabilities to Ambari.

5 ways to get the most out of BI and Big Data

This article by David Gee and Matthias Feltz looks at how CIOs must play an active role in creating and governing a competency centre.

Kindle e-book on Big Data

This link contains links to Amazon to get a free e-book on Big Data.

It's a very high level document but you might find it useful to point a colleague to.

Hottest 50 Big Data start-ups of 2014

This article lists them.  You do need to sign up for the newsletter to see the list except for the top 3.

Data Scientist Core Skills

This blog post from  Mitchell A Sanders on Data Science Central goes through the core skills a Data Scientist needs to have.

Looking through his list as always I can see my weakest area is the Capture section as I know I am not so good at programming.

Teradata has acquired Revelytix and Hadapt

It appears that there is some consolidation in the big data market following the news that Teradata has acquired Revelytix and Hadapt.