This page contains links to various resources available throughout our network, for analytics practitioners. It is an attempt to add structure to our content. Time permitting, we will also add tags to all recent or great postings for easier navigation. Currently, these discussions  in sections 2-8 are prior to 2014. For most recent featured discussions,click here.

You might want to bookmark this page, as it will be regularly updated.

1. General Resources

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2. Big Data

• Data Science Has Been Using Rebel Statistics for a Long Time
• Tutorial: How to detect spurious correlations, and how to find the real ones
• Jackknife logistic and linear regression for clustering and predictions
• Practical illustration of Map-Reduce (Hadoop-style), on real data
• A synthetic variance designed for Hadoop and big data
• Fast Combinatorial Feature Selection with New Definition of Predictive Power
• Big data is cheap and easy
• Big datasets available for free
• My thoughts on big data and data science: no, it's not hype
• Facebook missing revenue because of poor data science integration
• A little known component that should be part of most data science algorithms
• 11 Features any database, SQL or NoSQL, should have
• Clustering idea for very large datasets
• Interesting database questions
• When data flows faster than it can be processed
• Correlation and R-Squared for Big Data
• Nasty data corruption getting exponentially worse with the size of your data
• SQL to NoSQL translator
• An extensive glossary of big data terminology
• Building better search tools: problems and solutions
• Marrying computer science, statistics and domain expertize
• 42 big data startups
• Big Data Ecosystem
• From chaos to clusters - statistical modeling without models
• When a data glitch turns great data into worthless gibberish
• New pattern to predict stock prices, multiplies return by factor 5
• Internet Topology - Massive and Amazing Graphs
• Big Data Vendor Revenue and Market Forecast 2012-2017
• What Map Reduce can't do
• Excel for Big Data
• Fast clustering algorithms for massive datasets
• Big Data Analytics Ecosystem
• Source code for our Big Data keyword correlation API
• The 3Vs that define Big Data
• 53.5 billion clicks dataset available for benchmarking and testing
• 5 Big Data Startups That Matter
• The curse of big data
• How to detect a pattern? Problem and solution
• Bit.ly for competitive intelligence
• List of publicly traded analytic companies
• Hidden decision trees revisited

3. Visualization

• Detecting Patterns with the Naked Eye
• 50+ Open Source Tools for Big Data
• 40 maps that explain the world
• Shooting stars
• The 3 Vs of Big Data revisited
• Visualization through videos, using open source tools
• Internet Topology - Massive and Amazing Graphs
• Simple solutions to make videos with R
• 3-D Visualizations with rotating charts, for small and big data
• Great graphic diagrams
• Two more interesting graphs
• A new way to define centrality
• Fast clustering algorithms for massive datasets
• 14 questions about data visualization tools
• The top 20 data visualisation tools
• Another cute graph
• 5 books on data visualization
• Registered meteorites that has impacted on Earth visualized
• Analytics{Benzene} => {big Pharma, Nanotechnologies}
• What your state is the worst at – United States of shame

4. Best and Worst of Data Science

• New batch of 23 great articles and resources
• 175 Analytic and Data Science Web Sites
• 6000 Companies Hiring Data Scientists
• 100 data science, analytics, big data, visualization books
• 300 great articles from top news outlets
• 16 Reasons Data Scientists are Difficult to Manage
• 20 white papers and power point presentations
• 100 Savvy Sites on Statistics and Quantitative Analysis
• The 8 worst predictive modeling techniques
• The top 10 worst graphs
• 4 open source data mining tools (with GUI)
• The top 20 data visualisation tools
• 14 questions about data visualization tools
• 10+ Great Metrics and Strategies for Email Campaign Optimization
• Top analytics websites with trending information
• Who are the wealthiest data scientists?

5. New Analytics Start-up Ideas

• Uniquely identify a human being with two questions
• Selling data
• A new type of weapons-grade secure email
• R in your Browser
• A new, fast Excel for big data
• Automatically averaging and summarizing text
• Typed passwords replaced by biometrics
• Web app to run polls and display results on a map in real time
• Inbox delivery and management system for bulk email
• Pricing optimization for medical procedures
• Checks sent by email
• Anonymous digital currency for bartering
• Detect scams before they go live
• A nice mobile app for amusement parks
• Software that optimize hotel room prices in real time
• Web app to predict your risk of tax audit

6. Rants about Healthcare, Education, etc.

• How to compete against data scientists charging $30/hour
• Why statistical community is disconnected from Big Data and how to fix it
• How to eliminate a trillion dollars in healthcare costs
• Job interview question: what is wrong with this picture?
• Data Science: The End of Statistics?
• Big data misused to justify vaccination
• Big Data start-up to fix healthcare
• 8 reasons not to be insured
• A data scientist's solution to healthcare
• $33,000 to get an outdated Applied Maths degree
• Excel: list of bugs, inaccuracies and use of non-standard formulas
• Why can't Microsoft find analytic talent?
• Statistical evidence of global warming ?
• Official salary of 30,000 University of Washington employees
• Debunking the story about the Russian meteor event
• Boeing's Dreamliner turns into a nightmare due to bad analytics
• High crime rates explained by gasoline lead. Really?
• The graveyard of programming languages
• The End of Theory: The Data Deluge Makes the Scientific Method Obsolete

7. Career Stuff, Training, Salary Surveys

• The journey of a data scientist
• Data science job ads that do not attract candidates, versus those that do
• How to identify the right data scientist for your company
• 17 short tutorials all data scientists should read (and practice)
• Life Cycle of Data Science Projects
• Why Companies can't find analytic talent
• Six categories of data scientists
• Salary history and career path of a data scientist
• 2014 Analytics Salary Guide
• The data science toolkit
• 6000 Companies Hiring Data Scientists
• Data Science programs and training currently available
• Data Science: Connected Fields, Pioneers
• Clustering data scientists
• Salary surveys for data scientists and related job titles
• Difference between data engineers and data scientists
• Data Scientist vs. Statistician
• Marrying computer science, statistics and domain expertize
• Data Scientist Core Skills
• R Tutorial for Beginners: A Quick Start-Up Kit
• The death of the statistician
• Data Science / Big Data Salary Survey by Burtch Works
• Demand for Data Scientists and the Datification of Business
• Data Science Apprenticeship
• Map of data science university programs
• Job titles for data scientists
• How to better compete with other data scientists
• Horizontal vs. Vertical Data Scientists
• Data Scientists vs. Data Engineers
• Extreme Data Science
• 66 job interview questions for data scientists
• Test your analytical intuition
• Are data scientists overpaid?
• Data Science projects billed $300/hour on Kaggle
• The Face of the New University
• Fake data science
• Free courses from top universities
• Time Period for Analytical Positions Recruitment
• Data scientists making $300,000 a year
• Berkeley course on Data Science
• How much does a data scientist make at Facebook?
• Can data scientists replace business analysts?
• Debunking lack of analytic talent
• How maths should be taught in high school
• How do I become a data scientist?
• The amateur data scientist and her projects
• Data Scientist Demographics

8. Miscellaneous

• The best kept secret about linear and logistic regression
• Learn experimental design with our live, real-time ongoing analysis
• From the trenches: real data science project from start to finish
• Machine Learning in Parallel with Support Vector Machines, Generalized Linear Models, and Adaptive Boosting
• One Page R: A Survival Guide to Data Science with R
• Ingredients Of Data Science
• Sometimes outliers are real
• Boosting Algorithms for Better Predictions
• Structuredness coefficient to find patterns and associations
• Correlation and R-Squared for Big Data
• A counter-intuitive finding: twin data points is the norm, not the exception
• How to detect and cope with three types of hidden data, to eliminate opportunity costs
• Attribution Modeling vs Market Mix Modeling
• Top Languages for analytics, data mining, data science
• An indispensable Python : Data sourcing to Data science
• Interesting Data Science Application: Steganography
• Six Predictive Modeling Mistakes
• Linear regression on an usual domain, hyperplane, sphere or simplex
• Wine and alcohol analytics
• SQL: optimizing or eliminating joins?
• Great statistical analysis: forecasting meteorite hits
• Strategy for building a “good” predictive model
  
• Three classes of metrics: centrality, volatility, and bumpiness
• Correlation vs. causation
• Use PRESS, not R squared to judge predictive power of regression
• 27 criteria to choose analytic tools
• Are Lottery Winning Numbers Really Random?
• New, state-of-the-art random number generator
• Identifying the number of clusters: finally a solution
• Invented by a data scientist: the first anti-scam
• The next revolution in analytics: it's not about software
• Data Science Dictionary
• Modern books on multiple programming languages
• Are R, SAS, Excel, Tableau or other packages available as Web apps?
• A Practitioner's Guide to Business Analytics
• Myths about Twitter and Hashtags - real time detection of viral tweets
• Four different ways to solve a data science problem - case study
• Google search: three bugs to fix with better data science
• Online advertising: a solution to optimize ad relevancy
• Ad serving optimization
• Data Scientist Demographics
• Turning visitors into sales: seduction vs. analytics