2014 Jun Opinions, Interviews
All (103) | Courses, Education (4) | Meetings & Reports (10) | News, Features (22) | Opinions, Interviews (31) | Publications (8) | Software (8) | Top Tweets (13) | Webcasts (7)
- Exclusive: Dave Marvit, Innovation Strategy Consultant, Fujitsu on Modern Sentiment Analysis using Ubiquitous Continuous Sensing - Jun 30, 2014.
We discuss traditional sentiment analysis vs. modern sentiment analysis, role of data science in Human Centric Intelligent Society, mainstream adoption of bio sensors and opportunities created by Big Data from ubiquitous continuous sensing.
- The Impact Cycle – how to think of actionable insights - Jun 29, 2014.
The IMPACT Cycle provides a guiding framework for thinking about the steps for being effective analytical consultant, and can be a tool to help you drive effectiveness through your analytical teams.
- New Beginnings in Facial Recognition - Jun 28, 2014.
Developments in neural networks and deep learning are bringing great improvements in facial recognition, which could have exciting (and scary) applications on platforms like Google Glass.
- Do you need a Masters Degree to become a Data Scientist? - Jun 27, 2014.
Leading analytics experts answer the question: "Do you need a Masters Degree to become a Data Scientist?" Read practical tips and interesting commentary.
- Interview: Samaneh Moghaddam, Applied Researcher, eBay on Opinion Mining – Typical Projects and Major Challenges - Jun 27, 2014.
We discuss typical sentiment analysis problems at eBay, underrated challenges, career motivation, important soft skills and more.
- Interview: Ingo Mierswa, RapidMiner CEO on “Predaction” and Key Turning Points - Jun 27, 2014.
RapidMiner CEO Ingo Mierswa talks about "predaction", reasons for RapidMiner popularity, business source model, analytics to investigate fraud, key turning points, and more.
- Data Science Skills and Business Problems - Jun 27, 2014.
Discover what skills a data scientist benefits from learning and how the concept of a data scientist, and what businesses expect of them, has developed over time.
- Interview: Samaneh Moghaddam, Applied Researcher, eBay on Aspect-based Opinion Mining - Jun 26, 2014.
We discuss aspect-based opinion mining, major challenges, cold start items, the need for accurate opinion mining models for cold start items and how factorized LDA can be leveraged.
- Domino – A Platform For Modern Data Analysis - Jun 26, 2014.
Tools that facilitate data science best practices have not yet matured to match their counterparts in the world of software engineering. Domino is a platform built from the ground up to fill in these gaps and accelerate modern analytical workflows.
- What is Text Analytics? - Jun 24, 2014.
Anderson Analytics explains Text Analytics and the difference between First Generation approaches and Next Generation software OdinText.
- Optimizing the Netflix Streaming Experience with Data Science - Jun 19, 2014.
How Netflix uses data science and Big Data analytics to improve the Quality of streaming experience for its members.
- Does Deep Learning Have Deep Flaws? - Jun 19, 2014.
A recent study of neural networks found that for every correctly classified image, one can generate an "adversarial", visually indistinguishable image that will be misclassified. This suggests potential deep flaws in all neural networks, including possibly a human brain.
- Interview: Conal Sathi, Data Scientist, Slice on Creating Value from Mining Shoppers’ e-Receipts - Jun 16, 2014.
We discuss the relevance of "Purchase Graph", Slice platform, analytical insights from mining all activity around a customer's purchase, experimentation strategy, experience of working as a data scientist and more.
- NYU Data Science Program – Things to Know Part 2 - Jun 16, 2014.
NYU Data Science program reviewed from inside, including courses on Machine Learning, Big Data, Deep Learning, top professors, great NYC location, and future plans.
- The Cardinal Sin of Data Mining and Data Science: Overfitting - Jun 14, 2014.
Overfitting leads to public losing trust in research findings, many of which turn out to be false. We examine some famous examples, "the decline effect", Miss America age, and suggest approaches for avoiding overfitting.
- NYU Data Science Program – Things to Know - Jun 13, 2014.
Inside summary of NYU Data Science program launched last year, what it is, and what makes it special.
- The Algorithm that Runs the World Can Now Run More of It - Jun 13, 2014.
The most important algorithm, used for optimizing almost everything, is linear programming. New advances allow linear programming problems to be solved faster using the new commercial parallel simplex solver.
- Top 10 Data Analysis Tools for Business - Jun 13, 2014.
Ten free, easy-to-use, and powerful tools to help you analyze and visualize data, analyze social networks, do optimization, search more efficiently, and solve your data analysis problems.
- Moving from Data-Rich to Decision-Smart: INFORMS Conference The Business of Big Data 2014 - Jun 10, 2014.
We interview the co-chairs of INFORMS Conference The Business of Big Data 2014 (June 22-24, 2014) on Big Data maturity, opportunities assessment, analytics for operations research, conference agenda and more.
- The First Law of Data Science: Do Umbrellas Cause Rain? - Jun 9, 2014.
Michael Brodie on the first law of data science, the role of data curation in Big Data analysis, and Thomas Piketty economic theories.
- Interview: Lloyd Tabb, Chairman & CTO, Looker on Front-line Analytics and Data Democratization - Jun 9, 2014.
We discuss the capabilities of Looker, data democratization across organization, change in the tools being used by analytics-savvy business managers, front-line analytics, competitive landscape and more.
- Don Zereski, VP, Local Search & Discovery, HERE (Nokia) on Location Analytics and Architecture Evolution - Jun 8, 2014.
We discuss trends in location analytics, evolution of HERE's analytics architecture, infrastructure challenges, data governance and more.
- Data Lakes vs Data Warehouses - Jun 7, 2014.
Data Warehouses, traditionally popular for business intelligence tasks, are being replaced by less-structured Data Lakes which allow more flexibility.
- Interview: Santhosh Adayikkoth, CEO, BigInfo Labs on Big Data perception and learning Big Data skills - Jun 7, 2014.
We discuss BigInfo Labs' future plans, Big Data perception at C-level in large firms, most effective ways to learn Big Data skills and more.
- Interview: Santhosh Adayikkoth, CEO, BigInfo Labs on Data Relevance and Intel Partnership - Jun 6, 2014.
We discuss BigInfo Labs, the concept of "Data Relevance" in Big Data, experience of partnership with Intel, and BigInfo Labs' strategy for competitive differentiation.
- Data Science Last Mile - Jun 6, 2014.
This post discusses the Data Science "Last Mile", the final work to take the discovered insights and deliver them a highly usable format or integrate into a specific application.
- Exclusive: Raul Valdes-Perez on OnlyBoth, Scientific Discovery, Advice for Winners - Jun 5, 2014.
Our exclusive interview covers OnlyBoth and Vivisimo startups, Scientific Discovery, legendary Herbert A. Simon, venture capital, Big Data, advice for winners, and more.
- Big Data Strategy: Datafication - Jun 5, 2014.
Datafication of everything enables new ways of creating value and becoming more competitive. Oracle Big Data Strategist Paul Sonderegger explains.
- INFORMS, Uniting Operations Research and Analytics - Jun 4, 2014.
INFORMS is a large professional association which started in operations research and management science. I discuss their evolution to analytics, CAP certification, Big Data and more.
- Lynn Goldstein, Chief Data Officer, NYU on the Need for Data Governance - Jun 3, 2014.
We discuss the role of Data Governance, establishing Big Data accountability, impact of Data Governance on Data Quality, and assessing the education available for Data Governance.
- Interview: Tom Kern, Risk Modeling Manager, Paychex on Risk Analytics and Sales Anticipation Model - Jun 2, 2014.
We discuss the role of Risk Analytics at Paychex, strategic importance of Sales Anticipation Model, optimizing business processes by leveraging Big Data, and advice for companies thinking about Big Data as well as aspiring students.