2014 Aug Opinions, Interviews, Reports

• Interview: Debora Donato, StumbleUpon on the Secret Sauce of Impressive Content Curation - Aug 28, 2014.
  We discuss the role of data science at StumbleUpon, the shift from search to discovery, metrics for user engagement, the art of collaborative filtering, how native ads improve user experience, major trends, advice and more.

  Advertising, Advice, Customer Engagement, Data Curation, Debora Donato, Interview, Recommendations, StumbleUpon, Trends, User Experience

• Interview: Arpit Gupta, CEO, Actionable Analytics on Enterprise Challenges in Big Data and Cloud - Aug 24, 2014.
  We discuss Actionable Analytics start-up, enterprise challenges in Big Data, relationship with cloud computing, metrics vs. insights, Big Data expectations and more.

  Advice, Applications, Arpit Gupta, Big Data, Challenges, Cloud Computing, Consumer Insights, Interview, Metrics, Predictions

• INFORMS The Business of Big Data 2014: Day 1 Highlights - Aug 21, 2014.
  Highlights from the presentations by Big Data technology practitioners from Teradata, Booz Allen Hamilton, Databricks and ProbabilityManagement.org during INFORMS The Business of Big Data in San Jose.

  Analytics, BDaaS, Big Data, Conference, Hadoop, INFORMS, Probability, San Jose-CA, Trends

• Interview: Saikat Mukherjee, ShareThis on Why Marketers can no longer Ignore Social TV? - Aug 20, 2014.
  We discuss the role of Analytics at ShareThis, the emergence of Social TV, better user behavior insights through Social TV, major challenges with Social TV analytics, interesting insights, future trends, recommendation and more.

  Challenges, Consumer Insights, Marketing, Prediction, Recommendations, Saikat Mukherjee, ShareThis, Social Media, Social TV

• Interview: Pedro Domingos: the Master Algorithm, new type of Deep Learning, great advice for young researchers - Aug 19, 2014.
  Top researcher Pedro Domingos on useful maxims for Data Mining, Machine Learning as the Master Algorithm, new type of Deep Learning called sum-product networks, Big Data and startups, and great advice to young researchers.

  Advice, Deep Learning, KDD-2014, Machine Learning, Pedro Domingos, Startups

• Interview: John Funge, CTO, Knack on Why Gaming is the Next Big Thing for Hiring - Aug 18, 2014.
  We discuss the gamification of hiring, founding story of Knack, applications of Predictive Human Analytics, challenges, Big Data tools and technology used, key qualities sought in data scientists, career advice and more.

  Advice, Analytics, Big Data, Gamification, Gaming, Hiring, John Funge, Knack, Skills, Startup, Tools

• Interview: Pedro Domingos, Winner of KDD 2014 Data Mining/Data Science Innovation Award - Aug 15, 2014.
  We discuss the differences between Machine Learning, Data Mining, and Statistics; the importance of cost-sensitive classification; social network mining and identifying influencers; mining data streams, and more.

  Cost Sensitive, Machine Learning, Pedro Domingos, SIGKDD, Social Network Analysis, Stream Mining

• Interview: Pallas Horwitz, Blue Shell Games on Why Gaming Analytics is Not a Piece of Cake - Aug 15, 2014.
  We discuss the challenges of gaming analytics, most desired missing data, current trends, career advice, important soft skills in data science and more.

  Advice, Blue Shell Games, Challenges, Machine Learning, Missing Values, Pallas Horwitz, Predictive Analytics, Video Games

• Recommendations for Big Data Success for the Long Haul - Aug 15, 2014.
  Overcome common big data challenges by identifying the right POC (proof-of-concept) use case for Hadoop and leveraging its success to build executive and stakeholder buy-in.

  Big Data, Hadoop, Metascale, Proof-of-concept, Skills

• IBM Watson’s Next Step: Partnership with Universities - Aug 15, 2014.
  Students from ten top tech universities now have access to Watson. For students at New York University interested in Watson, Capstone Project Course would be their first choice.

  Data Science Education, IBM, Machine Learning, NYU, Ran Bi, Watson

• Interview: Pallas Horwitz, Blue Shell Games on Why Data Science is So Critical for Gaming Studios - Aug 14, 2014.
  We discuss the role of data science at Blue Shell Games, the importance of "Lean Data", key metrics for online games, cross-product projects and optimizing meeting the data needs across an organization.

  Blue Shell Games, Data Quality, Data Science, Lean Data, Metrics, Optimization, Pallas Horwitz, Video Games

• Data is not a fad - Aug 14, 2014.
  Learn why Big Data drives the need for companies to adopt data leadership and why Chief Data Officers are likely to join the C-suite in large organizations.

  Big Data, Burtch Works, Chief Data Officer, Data Science Education, Hiring

• Interesting Social Media Datasets - Aug 13, 2014.
  Learn about some of the many interesting social media datasets available to you, some of which are quite new, and the different features and challenges they offer you for your next big data science project.

  Challenge, Data Visualization, Datasets, Open Data, Social Media Analytics

• Talent Analytics Projects: “Fishing” vs Solving Business Problems - Aug 13, 2014.
  We examine a vague "look for something interesting in the HR data” vs a narrowly focused “business win” effort and show why the second approach is preferable, and what needs to be added to HR data for success.

  Employee Value, HR, Pasha Roberts, Talent Analytics, Workforce Analytics

• Interview: Michael Berthold, KNIME Founder, on Research, Creativity, Big Data, and Privacy, Part 2 - Aug 12, 2014.
  We discuss interesting research projects, scientific research and creativity, Big Data hype and reality, is privacy still possible, and advice for beginning Data Scientists.

  Big Data Hype, Knime, Michael Berthold, Privacy, Research

• Top 10 References for applying Big Data and Analytics in Business - Aug 11, 2014.
  See how businesses leverage data analytics for great gain to help others understand the business value of data science projects and provide examples to inspire your own data-driven projects.

  Alex Jones, Applications, Business Analytics, Business Strategy, Business Value, Data Analytics

• Interview: Michael Berthold, President and Founder of KNIME, on Data Mining, Startups, and Visual Workflow - Aug 9, 2014.
  We discuss KNIME key features and how it compares to competition, KNIME business model, Pharma, planned development, and transition from an academic project to a company.

  Knime, Konstanz University, Michael Berthold, Open Source

• Metrics that Matter – The Key to Perfect Dashboards - Aug 9, 2014.
  Create the perfect data visualization dashboards by learning what metrics matter most to your users and displaying them prominently within the design of the dashboard.

  BRIDGEi2i, Dashboard, Data Visualization, Metrics, Tableau

• ASE International Conference on Big Data Science 2014: Day 4 Highlights - Aug 8, 2014.
  Highlights from the presentations by Data Science leaders from UC Berkeley, Clark Atlanta Univ, Florida Institute of Technology, Rober Bosh LLC and HP on day 4 of ASE Conference on Big Data Science 2014, Stanford.

  Algorithms, Analytics, Community Mining, Conference, Data Analysis, Social Media, Social Network Analysis, Stanford

• Six Thinking Hats and the Life of a Data Scientist - Aug 8, 2014.
  Learn about the different "hats" (mindsets) a data scientist should adopt to reach maximum effectiveness in the variety of situations encountered in this emerging field.

  Data Science Skills, Data Scientist, Debleena Roy, Edward De Bono, Hats

• Interview: Sujee Maniyam, Elephant Scale on Why Open Source is So Important for Big Data - Aug 8, 2014.
  We discuss the importance of contributing to Open Source, Big Data skills for business managers, Big Data predictions, key qualities sought in data engineers, career advice and more.

  Advice, Big Data, Elephant Scale, Hadoop, Hiring, Open Source, Sujee Maniyam, Trends

• Big Data Innovation Summit 2014 Toronto: Day 2 Highlights - Aug 7, 2014.
  Highlights from the presentations by Big Data leaders from Aviva, Canadian Imperial Bank, Royal College of Physicians and Surgeons of Canada, and University Health Network on day 2 of Big Data Innovation Summit 2014.

  Analytics, Big Data, Conference, Graph Analytics, Healthcare, IE Group, Innovation, Toronto-Canada

• Interview: Sujee Maniyam, Elephant Scale on the Best Free Online Resources to Learn Hadoop - Aug 7, 2014.
  We discuss the startup - Elephant Scale, DIY Hadoop learning, best free online resources for learning Hadoop, getting a good job in Big Data, and the experience of authoring a book - Hadoop Illuminated (available for free).

  Big Data, Certification, Elephant Scale, Free, GitHub, Hadoop, Hiring, Open Source, Skills, Sujee Maniyam

• Becoming a Data Scientist: MS Program, Bootcamp, or MOOCs? - Aug 6, 2014.
  Learn about the different ways to become a data science including a master's degree, bootcamps, or self-learning with MOOCs and their advantages and disadvantages.

  Bootcamp, Data Science, Data Science Education, Irmak Sirer, Master of Science, MOOC

• Big Data Innovation Summit 2014 Toronto: Day 1 Highlights - Aug 6, 2014.
  Highlights from the presentations by Big Data leaders from TD Bank, Public Health Ontario and First Nations Education Steering Committee on day 1 of Big Data Innovation Summit 2014 in Toronto, Canada.

  Analytics, Big Data, Conference, Customer Experience, Gartner, Healthcare, IE Group, Innovation, Toronto-Canada

• Interview: Vita Markman, LinkedIn on Discovering Customer Insights through Sentiment Mining - Aug 5, 2014.
  We discuss examples of discovery through sentiment mining, current trends, innovative applications, important soft skills, and more.

  Classification, Consumer Insights, Innovation, Interview, LinkedIn, Skills, Trends, Vita Markman

• ASE International Conference on Big Data Science 2014: Day 3 Highlights - Aug 5, 2014.
  Highlights from the presentations by Data Science leaders from UC Davis, UT Dallas, Northrop Grumman Corp and NIST on day 3 of ASE Conference on Big Data Science 2014 held in Stanford University.

  Analytics, Conference, Cybersecurity, Data Science, Semantic Analysis, Social Media, Stanford, Twitter

• BAT: China’s Three Big Data Leaders - Aug 5, 2014.
  We examine the “three big mountains” in Chinese Internet and Big Data industry: Baidu, Alibaba, and Tencent (together called BAT), and look into their different strategy and focus.

  Alibaba, Baidu, Big Data, China, Liyang Tang, Search Infrastructure, Social Media Analytics, Tencent

• ASE International Conference on Big Data Science 2014: Day 2 Highlights - Aug 4, 2014.
  Highlights from the presentations by Data Science leaders from USC, YarcData and Revolution Analytics on day 2 of ASE Conference on Big Data Science 2014 held in Stanford University.

  Big Data Analytics, Cloud Analytics, Conference, Internet of Things, Security, Stanford

• Interview: Vita Markman, LinkedIn on Practical Solutions for Sentiment Mining Challenges - Aug 4, 2014.
  We discuss sentiment data models, significance of linguistic features, handling the noise in social conversations, industry challenges, important use cases and the appropriateness of over-simplified binary classification.

  Challenges, Classification, LinkedIn, Noise, Sentiment Analysis, Social Media, Text Mining, Vita Markman

• Interview: Christophe Toum, Talend on Why Big Data Needs Big Governance - Aug 2, 2014.
  We discuss the priority order of data governance for Big Data initiatives, impact of increasing shift towards Hadoop and NoSQL, data quality, current trends, talent crunch, advice and more.

  Christophe Toum, Data Governance, Data Management, Data Quality, Hiring, Talend, Trends

• ASE International Conference on Big Data Science 2014: Day 1 Highlights - Aug 1, 2014.
  Highlights from the presentations by Data Science leaders from Pivotal, IBM Research, George Washington University, IARPA at ASE Conference on Big Data Science 2014 held in Stanford University.

  Cloud Foundry, Conference, Cybersecurity, Hadoop, Infrastructure, Predictive Models, Recommendation, Stanford

• Interview: Taylor Phillips, Square on Why Finance Needs Machine Learning and Data Science - Aug 1, 2014.
  We discuss the role of data science at Square, common machine learning use cases, transition to real-time architecture, major challenges, expectations from data science, key qualities for data scientists, and more.

  Data Science, Finance, Fraud Detection, Machine Learning, Real-time, Recommendation, Skills, Square, Taylor Phillips