Interview: Debora Donato, StumbleUpon on the Secret Sauce of Impressive Content Curation
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.
on Aug 28, 2014 in 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
We discuss Actionable Analytics start-up, enterprise challenges in Big Data, relationship with cloud computing, metrics vs. insights, Big Data expectations and more.
on Aug 24, 2014 in Advice, Applications, Arpit Gupta, Big Data, Challenges, Cloud Computing, Consumer Insights, Interview, Metrics, Predictions
INFORMS The Business of Big Data 2014: Day 1 Highlights
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.
on Aug 21, 2014 in 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?
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.
on Aug 20, 2014 in 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
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.
on Aug 19, 2014 in 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
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.
on Aug 18, 2014 in 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
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.
on Aug 15, 2014 in 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
We discuss the challenges of gaming analytics, most desired missing data, current trends, career advice, important soft skills in data science and more.
on Aug 15, 2014 in Advice, Blue Shell Games, Challenges, Machine Learning, Missing Values, Pallas Horwitz, Predictive Analytics, Video Games
Recommendations for Big Data Success for the Long Haul
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.
on Aug 15, 2014 in Big Data, Hadoop, Metascale, Proof-of-concept, Skills
IBM Watson’s Next Step: Partnership with Universities
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.
on Aug 15, 2014 in 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
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.
on Aug 14, 2014 in Blue Shell Games, Data Quality, Data Science, Lean Data, Metrics, Optimization, Pallas Horwitz, Video Games
Data is not a fad
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.
on Aug 14, 2014 in Big Data, Burtch Works, Chief Data Officer, Data Science Education, Hiring
Interesting Social Media Datasets
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.
on Aug 13, 2014 in Challenge, Data Visualization, Datasets, Open Data, Social Media Analytics
Talent Analytics Projects: “Fishing” vs Solving Business Problems
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.
on Aug 13, 2014 in Employee Value, HR, Pasha Roberts, Talent Analytics, Workforce Analytics
Interview: Michael Berthold, KNIME Founder, on Research, Creativity, Big Data, and Privacy, Part 2
We discuss interesting research projects, scientific research and creativity, Big Data hype and reality, is privacy still possible, and advice for beginning Data Scientists.
on Aug 12, 2014 in Big Data Hype, Knime, Michael Berthold, Privacy, Research
Top 10 References for applying Big Data and Analytics in Business
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.
on Aug 11, 2014 in 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
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.
on Aug 9, 2014 in Knime, Konstanz University, Michael Berthold, Open Source
Metrics that Matter – The Key to Perfect Dashboards
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.
on Aug 9, 2014 in BRIDGEi2i, Dashboard, Data Visualization, Metrics, Tableau
ASE International Conference on Big Data Science 2014: Day 4 Highlights
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.
on Aug 8, 2014 in Algorithms, Analytics, Community Mining, Conference, Data Analysis, Social Media, Social Network Analysis, Stanford
Six Thinking Hats and the Life of a Data Scientist
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.
on Aug 8, 2014 in 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
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.
on Aug 8, 2014 in Advice, Big Data, Elephant Scale, Hadoop, Hiring, Open Source, Sujee Maniyam, Trends
Big Data Innovation Summit 2014 Toronto: Day 2 Highlights
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.
on Aug 7, 2014 in 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
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).
on Aug 7, 2014 in Big Data, Certification, Elephant Scale, Free, GitHub, Hadoop, Hiring, Open Source, Skills, Sujee Maniyam
Becoming a Data Scientist: MS Program, Bootcamp, or MOOCs?
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.
on Aug 6, 2014 in Bootcamp, Data Science, Data Science Education, Irmak Sirer, Master of Science, MOOC
Big Data Innovation Summit 2014 Toronto: Day 1 Highlights
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.
on Aug 6, 2014 in Analytics, Big Data, Conference, Customer Experience, Gartner, Healthcare, IE Group, Innovation, Toronto-Canada
Interview: Vita Markman, LinkedIn on Discovering Customer Insights through Sentiment Mining
We discuss examples of discovery through sentiment mining, current trends, innovative applications, important soft skills, and more.
on Aug 5, 2014 in Classification, Consumer Insights, Innovation, Interview, LinkedIn, Skills, Trends, Vita Markman
ASE International Conference on Big Data Science 2014: Day 3 Highlights
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.
on Aug 5, 2014 in Analytics, Conference, Cybersecurity, Data Science, Semantic Analysis, Social Media, Stanford, Twitter
BAT: China’s Three Big Data Leaders
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.
on Aug 5, 2014 in Alibaba, Baidu, Big Data, China, Liyang Tang, Search Infrastructure, Social Media Analytics, Tencent
ASE International Conference on Big Data Science 2014: Day 2 Highlights
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.
on Aug 4, 2014 in Big Data Analytics, Cloud Analytics, Conference, Internet of Things, Security, Stanford
Interview: Vita Markman, LinkedIn on Practical Solutions for Sentiment Mining Challenges
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.
on Aug 4, 2014 in Challenges, Classification, LinkedIn, Noise, Sentiment Analysis, Social Media, Text Mining, Vita Markman
Interview: Christophe Toum, Talend on Why Big Data Needs Big Governance
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.
on Aug 2, 2014 in Christophe Toum, Data Governance, Data Management, Data Quality, Hiring, Talend, Trends
ASE International Conference on Big Data Science 2014: Day 1 Highlights
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.
on Aug 1, 2014 in Cloud Foundry, Conference, Cybersecurity, Hadoop, Infrastructure, Predictive Models, Recommendation, Stanford
Interview: Taylor Phillips, Square on Why Finance Needs Machine Learning and Data Science
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.
on Aug 1, 2014 in Data Science, Finance, Fraud Detection, Machine Learning, Real-time, Recommendation, Skills, Square, Taylor Phillips
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