Interview: Andrew Duguay, Prevedere on the Hidden Value in Global Data Sets
We discuss the challenges in analyzing global economic datasets, impact of Big Data growth on economics, desired skills in data scientists, and more.
on Jul 31, 2015 in Andrew Duguay, Challenges, Economics, Interview, Prevedere, Trends
Interview: Andrew Duguay, Prevedere on Economic Intelligence from Integrating Public Datasets
We discuss Analytics at Prevedere Software, understanding the impact of external factors on a company’s performance, features of in-memory correlation engine and economic intelligence by Prevedere.
on Jul 30, 2015 in Andrew Duguay, Datasets, Economics, In-Memory Computing, Interview, Performance, Prevedere, Use Cases
Big Data Best-Practice Checklist for Small and Medium Enterprises
As more and more companies getting into the competition, it is important for the SMEs to get Big Data right from the start. Learn, how you can make most of the big data analytics.
on Jul 30, 2015 in Best Practices, Big Data Analytics, Checklist, FICO
Impact of IoT on Big Data Landscape
The Internet of Things (IoT) is the next technological revolution, expected to generate over $300 B by year 2020, according to Gartner. The IoT will also generate unprecedented amounts of data and its impact will be felt across the entire big data universe.
on Jul 29, 2015 in Big Data, Hadoop, IoT, Kaushik Pal
Interview: Brian Kursar, Toyota on Big Data & Advanced Analytics – Cornerstones of Innovation
We discuss the Big Data architecture at Toyota, executives’ perception of Analytics, Toyota Innovation Fair, advice, trends, and more.
on Jul 28, 2015 in Advanced Analytics, Big Data, Brian Kursar, Career, Communication, Innovation, Interview, Toyota
Data Science Degrees – Analyzed and Visualized
We use Silk to create an interactive data site of data science degree programs with visualizations on line. The USA has 181 programs, more than the rest of the world combined. Western Europe follows.
on Jul 28, 2015 in Alex Salkever, Data Science Education, Data Visualization, Ryan Swanstrom, Silk.co, USA
Big Data for Sustainability
With big data about energy usage at the device level, enterprises are reducing consumption, optimizing processes for efficiency, and creating sustainability initiatives that advance them in economic, social, and environmental realms.
on Jul 28, 2015 in Big Data, Energy, Sustainability
Interview: Brian Kursar, Toyota on What You Need to be Truly Data-Driven
We discuss Toyota’s Customer 360 Advanced Analytics and Insights platform, Product Quality Analytics system, Predictive Analytics use cases & performance assessment, and challenges in analyzing data from social media.
on Jul 27, 2015 in
Data for Humanity: A Request for Support
The goal of this initiative is to bring people and institutions together who share the motivation to use Data for Common Good / human well-being. Join many other notable signatories.
on Jul 25, 2015 in Roberto Zicari, Social Good
Interview: Thanigai Vellore, Art.com on Why Big Data vs RDBMS is the Wrong Question
We discuss success factors with polyglot architectures, Big Data challenges, recommendations for using Big Data technologies, trends, advice, and more.
on Jul 24, 2015 in Architecture, Art.com, Big Data, Career, Challenges, Hadoop, Interview, RDBMS, Recommendations
From Big Data to Big Profits: A Lesson from Google’s Nest
Google Nest is a very interesting example of how such a seemingly simple item as thermostat, with the addition to Big Data can transform an industry and lead to significant profits.
on Jul 24, 2015 in Big Data, Google, HVAC, IoT, Nest, Profit, Russell Walker, Thermostat
Interview: Thanigai Vellore, Art.com on Delivering Contextually Relevant Search Experience
We discuss the role of Analytics at Art.com, the polyglot data architecture at Art.com, the use cases for Hadoop, vendor selection, supporting semantic search and experience with Avro.
on Jul 23, 2015 in Architecture, Art.com, Avro, Hadoop, HBase, Interview, Semantic Analysis, Solr, Thanigai Vellore
Sentiment Analysis Symposium Summary and Highlights
Here, find out how leading analysts and researchers are exploring the sentiment analysis and text mining in their areas. Also, explore the opportunities, challenges and use-cases for the sentiment analysis.
on Jul 23, 2015 in Bing Liu, Cognitive Computing, New York City, NY, Sentiment Analysis, Seth Grimes, Steve Gallant
Disruptive Innovation and Competitive Intelligence
Disruptive innovation paradigm enables us to understand the rising competition in businesses. Here, we will show how this can be helpful to Competitive Intelligence and challenges ahead of it.
on Jul 22, 2015 in Big Data, Competitive Intelligence, Crowdsourcing, Debleena Roy
The Perpetual Quest for Digital Trust
Digital Trust is at a deficit – concludes the 2015 Accenture Digital Consumer Survey report “Digital Trust in the IoT Era”
on Jul 22, 2015 in Accenture, Consumer Insights, Information Management, IoT, Security, Survey, Trust
arXiv.org and the 24 Hour Research Cycle
ArXiv.org gives researchers the ability to instantly publish research, free of peer review and the publication cycle. This capability offers both advantages and pitfalls. We should warily eye the 24-7 news cycle as a cautionary tale for how this could go wrong.
on Jul 21, 2015 in arXiv, Data Science, Machine Learning, Research, Zachary Lipton
Analyzing and Visualizing Flows in Rivers and Lakes with MATLAB
ADCPs and VMT have increased the pace of studies that rely on flow data. Find out how these toolkits from MathWorks are revolutionizing the analysis and visualisation processes.
on Jul 20, 2015 in Data Visualization, Data Workflow, MathWorks, MATLAB
Interview: Ali Vanderveld, Groupon on How Data Science is Changing the Global E-commerce Marketplace
We discuss the tools used for data science, competitive landscape, journey from astrophysics to data science, advice, skills sought in data scientists, and more.
on Jul 17, 2015 in Advice, Ali Vanderveld, Career, Competition, Data Science, Ecommerce, Groupon, Interview, Marketplace, Mobile
Stop Hiring Data Scientists Until You’re Ready for Data Science
Getting an unicorn and restraining it into the chains won't be helpful for you or the unicorn. Find out how you can tap into the potential of these new age unicorns.
on Jul 17, 2015 in Data Scientist, Greta Roberts, Hiring, Talent Analytics
OpenImpact – solve social problems with your data skills
Help solve social problems with your data skills - DataLook #openimpact campaign has curated a list of 10 impressive reusable data-driven projects that can help to solve problems in your city.
on Jul 16, 2015 in DataLook, Social Good
Interview: Ali Vanderveld, Groupon on Vital Ingredients of Analytics-powered Sales Force
We discuss the role of Analytics at Groupon, deciding factors for merchant priority, limitations of historical data, optimizing the efforts of sales force, data characteristics and dealing with Data Sparsity.
on Jul 16, 2015 in Ali Vanderveld, Analytics, Challenges, Forecasting, Groupon, Interview, Marketing, Sales, Sparse data
Big Data – yes, that’s what a latest Sensational Rap Music Video is all about
Music video featuring Big Data and Hadoop (and Map-Reduce and NoSQL) might be all you need to light up your day!
on Jul 16, 2015 in Big Data, Data Scientist, Hadoop, MapReduce, Music, NoSQL, Viacom Velocity
Statistics Denial Myth: Repackaging Statistics With Straddling Terms
Data science is nothing but the old wine in new bottle versions of the statistics with different fields. Here, we are busting the myth which states data scientist is new and different than traditional statisticians.
on Jul 16, 2015 in Data Analysis, Data Management, Data Science Skills, Myths, Randy Bartlett, Statistics
Deep Learning Adversarial Examples – Clarifying Misconceptions
Google scientist clarifies misconceptions and myths around Deep Learning Adversarial Examples, including: they do not occur in practice, Deep Learning is more vulnerable to them, they can be easily solved, and human brains make similar mistakes.
on Jul 15, 2015 in Adversarial, Deep Learning, Ian Goodfellow, Myths, Regularization
Interview: Ramkumar Ravichandran, Visa on Customer-focus Mindset for Analytics
We discuss career advice, need for customer-focus, Analytics trends, desired skills in Data Science practitioners, and more.
on Jul 15, 2015 in Analytics, Customer Analytics, Hiring, Interview, IoT, Ramkumar Ravichandran, Trends, Visa
Interview: Ramkumar Ravichandran, Visa on Actionable Insights – Easier Said Than Done
We discuss Analytics at Visa, adapting to the Big Data world, gaps between expectations and delivery from Analytics, delivering Actionable Insights, and tools/technologies used.
on Jul 14, 2015 in A/B Testing, Analytics, Decision Making, Insights, Interview, Ramkumar Ravichandran, Tools, Visa
Can Deep Learning Help you Find the Perfect Girl? – Part 2
Using Deep Learning to find the perfect match, PhD student Harm de Vries describes the process of data collection and analysis. Finally, the results from matching algorithm are compared to human assessment for identifying an individual's dating preferences.
on Jul 13, 2015 in Deep Learning, Love, OkCupid, Online Dating, Predictive Analytics
Can deep learning help find the perfect date?
When a Machine Learning PhD student at University of Montreal starts using Tinder, he soon realises that something is missing in the dating app - the ability to predict to which girls he is attracted. Harm de Vries applies Deep Learning to assist in the pursuit of the perfect match.
on Jul 10, 2015 in Deep Learning, ICML, Love, Machine Learning, Online Dating, Predictive Analytics
Interview: Reiner Kappenberger, HP Security Voltage on Security Checklist for Data Architectures
We discuss securing data-at-rest and data-in-motion, security recommendations for data architectures, trends, advice, and more.
on Jul 10, 2015 in Architecture, HP, HP Security Voltage, Interview, Recommendations, Reiner Kappenberger, Security, Trends
Interview: Reiner Kappenberger, HP Security Voltage on How to Secure Data-in-Motion
We discuss the security concerns in Big Data, challenges in securing Big Data locally and over cloud, and open source solutions – Knox and Ranger.
on Jul 9, 2015 in Challenges, Cloud, HP, HP Security Voltage, Interview, Open Source, Reiner Kappenberger, Security
Lund University Develops an Artificial Neural Network for Matching Heart Transplant Donors with Recipients
Finding the correct donor for the transplant has been challenging and intensively researched usecase in data science. Here, you can find how MathWorks was used to resolve this problem.
on Jul 9, 2015 in Healthcare, Lund University, MATLAB, Neural Networks, Sweden
Data Science Made in Switzerland
Recently there was a data science conference at ZHAW Datalabs, which was attended by people with a wide range of skills, expertise, and levels. Check out the highlights of the events and future plans of the conference.
on Jul 9, 2015 in Data Science, Michael Brodie, Switzerland
Interview: Reiner Kappenberger, HP Security Voltage on Data-Centric Security for Big Data
We discuss HP Security Voltage growth story, HP acquisition, assessing the state of current security standards, and the need for “data-centric” security.
on Jul 8, 2015 in Big Data, Data-Centric, HP, HP Atalla, HP Security Voltage, Interview, NIST, Reiner Kappenberger, Security
Deep Learning and the Triumph of Empiricism
Theoretical guarantees are clearly desirable. And yet many of today's best-performing supervised learning algorithms offer none. What explains the gap between theoretical soundness and empirical success?
on Jul 7, 2015 in Big Data, Data Science, Deep Learning, Mathematics, Statistics, Zachary Lipton
The Definitive Guide to doing Data Science for Social Good
Are you a data scientist, and looking for the opportunity to use your skill for social good? Here, you can find some of the options available for using the data science skills for well-being of society.
on Jul 6, 2015 in Data Science, DataKind, DataLook, Social Good
Data Science and Big Data: Two very Different Beasts
Creating artifact from the ore requires the tools, craftmanship and science. Same is the case of big data and data science, here we present the distinguishing factors between the ore and the artifact.
on Jul 6, 2015 in Big Data, Data Science, Sean McClure
Doubt and Verify: Data Science Power Tools
In the end, there is no truth, no ultimate ground truth, no lie-free utterances, as everything is contextual based on incomplete facts and knowledge. All world models are flawed, but Data Science has 2 power tools.
on Jul 3, 2015 in Bias, Data Science, Michael Brodie
KDnuggets Interview: Amr Awadallah, CTO & Co-founder, Cloudera on the Secret Sauce of Open Source
We discuss the critical success factor for open source projects, entrepreneurial lessons, advice, desired qualities in data scientists and more.
on Jul 2, 2015 in Amr Awadallah, Apache, Cloudera, Data Science Skills, Entrepreneur, Hadoop, Hiring, Interview, Open Source
The missing D in Data Science
Data science is often talked in terms of tools, insights and emerging use cases, but one of its important pillars domain expertise is left out. Find out why you should be concerned about it.
on Jul 1, 2015 in Data Science, Debleena Roy, Domain Knowledge, Sherlock Holmes
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