Interview: Ben Werther, CEO, Platfora on Insightful Analytics for Big Data
We discuss the challenges in implementing end-to-end solutions for Big Data, Platfora use cases, Big Data trends, advice and more.
on Dec 30, 2014 in Advice, Ben Werther, Challenges, Interview, IoT, Platfora, Trends, Use Cases
Interview: Ben Werther, CEO, Platfora on Why Big Data Needs Self-Service Tools
We discuss the importance of self-service model for Big Data tools, Small Data vs. Big Data, unique advantages of Platfora, key enhancements in Platfora 4.0 and more.
on Dec 29, 2014 in Ben Werther, Competition, Data Democratization, Interview, Platfora, Self-service, Survey, Tools, Visualization
Interview: Mac Devine, CTO, IBM Cloud on the Conflux of Cloud, IoT & Big Data
We discuss the implications of Cloud Speed of technological advancement, significant trends in Internet of Things (IoT), future of cloud computing and more.
on Dec 26, 2014 in Advice, Cloud Computing, IBM, Innovation, Interview, IoT, Mac Devine, Trends
Stanford’s AI100: Century-Long Study on Effects of Artificial Intelligence on Human Life
Stanford unveils new 100 year study on the impact of artificial intelligence, particularly on democracy, privacy, the military. Surprisingly, perspectives from outside the AI community are absent from the initial panel.
on Dec 26, 2014 in Artificial Intelligence, Deep Learning, DeepMind, Demis Hassabis, Eric Horvitz, Stanford, Zachary Lipton
Interview: Mac Devine, CTO, IBM Cloud on the Fast Approaching Perfect Storm
We discuss why we should anticipate a technology perfect storm soon, Enterprise IT challenges, distinct capabilities of IBM BlueMix and more.
on Dec 24, 2014 in Big Data, BlueMix, Challenges, Cloud Computing, IBM, Interview, IoT, Mac Devine
Hot or Not: Data Science Trends in 2015
CrowdFlower infographic predicts the hot trends for data science in 2015 and which trends will fade away.
on Dec 24, 2014 in CrowdFlower, Data Democratization, Data Science, Infographic, Predictions for 2015, Social Good, Trends
The Big Data of Wearables
Wearables are becoming more common, creating real-time demands on the data-driven systems behind them for applications like forecasting and recommender systems.
on Dec 23, 2014 in Big Data, Internet of Things, Wearables
DIY Crawlers vs. Crawlers as Service
Crawling structured data from the web has been made easier with the choice between crawlers as a service, like webhose.io, and do-it-yourself, like import.io.
on Dec 22, 2014 in Big Data Services, Crawler, Data Preparation, import.io, Spider, Webhose.io
FICO Chief Analytics Officer Sees a Post–Big Data World in 2015
Predictive analytics and the Big Data that fuels it become deeply and broadly embedded in business and society – no longer a phenomenon but widely accepted as part of the foundation. Here are a few of his predictions for the coming year.
on Dec 21, 2014 in Andrew Jennings, FICO, Predictions for 2015, Security
“Vite fait, bien fait” – Averaging improves both accuracy and speed of time series classification
Time series classification using k-nearest neighbors and dynamic time warping can be improved in many practical applications in both speed and accuracy using averaging.
on Dec 21, 2014 in Classification, Francois Petitjean, ICDM, IEEE, Time Series
2015 Predictions: What will happen to big data and data science?
What’s next in the world of big data? Commonplace terms begin to vanish as businesses put an increased emphasis on the predictive and prescriptive analytics needed to drive value.
on Dec 21, 2014 in Big Data, Chief Data Officer, Data Governance, Data Science, Predictions for 2015, Prescriptive Analytics
Interview: Brian Hampton, SF 49ers on Competitive Edge through Football Analytics
We discuss the shortcomings of football analytics, how San Francisco 49ers use analytics, future of football analytics, advice and more.
on Dec 20, 2014 in Analytics, Brian Hampton, Challenges, Coaching, Competition, Football, Interview, NFL, Sports, Team
Interview: Brian Hampton, San Francisco 49ers on Playing Football the Analytics Way
We discuss the role of analytics in football, the underrated challenges, evolution since the era of draft trade value chart and analytics-supported team selection.
on Dec 19, 2014 in Analytics, Brian Hampton, Challenges, Coaching, Competition, Football, NFL, Sports, Team
Interview: Peter Alvaro, UC Berkeley, on Managing Asynchrony and Partial Failure
We discuss the challenges in simultaneously managing asynchrony and partial failure, the problem of composition, research motivation, trends and more.
on Dec 18, 2014 in Challenges, Cloud, Peter Alvaro, Programming Languages, Recommendations, Trends, UC Berkeley
Interview: Peter Alvaro, UC Berkeley, on Consistency Challenge in Distributed Systems
We discuss the performance limitations caused by treating datastore as black box, consistency as an application-level property, Dedalus and LDFI approach for testing.
on Dec 17, 2014 in Consistency, Data, Databases, Distributed Systems, NoSQL, Peter Alvaro, UC Berkeley
8 Things to Check when you analyze Twitter data
A review of biases and issues on large scale studies of human behavior in social media discussed by a recent paper published on Science.
on Dec 16, 2014 in Data Analysis, Science, Social Media, Twitter
Analyze And Visualize Chatter from Nigeria Elections 2015
A visual listening open data platform helps to see the chatter around upcoming Nigeria 2015 election – facts, ideas, topics, issues, statistics, queries – in a bare minimum of words and beautiful imagery.
on Dec 16, 2014 in Chatter, Elections, Nigeria, Visualization
Open Innovation in the Age of Big Data
Open platforms for data analysis are more important than ever with big data and increasing access to heterogeneous data sources for analysts.
on Dec 15, 2014 in Big Data, Innovation, Knime, Open Analytics
Our Iceberg is Melting.. Now where is that Data Scientist?
Marketing analytics teams could improve their effectiveness by employing a marketing effectiveness strategy similar to that used by penguins dealing with their iceberg melting.
on Dec 15, 2014 in Data Scientist, Debleena Roy, Market Analytics, Marketing
KDnuggets Interview: Paul Zikopoulos, IBM on Big Data Opportunities and Challenges
We discuss the value of Big Data for SMBs, how Cognitive will impact Big Data, IBM’s distinction from competition, significant trends and more.
on Dec 14, 2014 in Big Data, Big Data Hype, Business, Challenges, IBM, Opportunities, Paul Zikopoulos, Trends
KDnuggets Interview: Paul Zikopoulos, IBM on Why Big Data needs Polyglots
We discuss why not to focus on a single technology in Big Data, prevalent myths, what IBM & Twitter partnership means for the world, and current state of data governance.
on Dec 13, 2014 in Big Data, Hadoop, IBM, Interview, MapReduce, NoSQL, Paul Zikopoulos, Social Analytics, Twitter
2015 Predictions – What’s Next for Data Scientists?
What’s next for data scientists in 2015 - new areas they will focus on - cyber threats to fraud detection - and how the expectations for this profession will change.
on Dec 12, 2014 in Data Science Skills, Data Scientist, EXASOL, Predictions for 2015
IIA 2015 Analytics Predictions
Highlights and discussion from IIA 2015 Analytics Predictions webinar, including Storytelling will be the hot new job in analytics; companies double investment in generating NEW and UNIQUE data, and how does one become an expert if entry-level work is automated?
on Dec 11, 2014 in IIA, Predictions for 2015, Privacy, Storytelling, Tom Davenport
Interview: Daqing Zhao, Macys.com on Building Effective Data Models for Marketing
We discuss the challenges in identifying the fair price of ad media, recommendations for building effective models for online marketing, unique challenges of Mobile channel, selection of Big Data tools, and more.
on Dec 11, 2014 in Daqing Zhao, Data Models, Data Science Skills, Hadoop, Interview, Macy's, Marketing, Mobile, Tools
Interview: Daqing Zhao, Macys.com on Advanced Analytics for Marketing in the Big Data era
We discuss Analytics at Macys.com, comparison of advanced analytics with traditional BI, building data models for scalability, problem of data models becoming quickly obsolete and challenges in customer targeting.
on Dec 10, 2014 in Advanced Analytics, Audience targeting, BI, Challenges, Customer Analytics, Daqing Zhao, Data Models, Interview, Macy's
Geoff Hinton AMA: Neural Networks, the Brain, and Machine Learning
In a wide-ranging Q&A, Geoff Hinton addresses the future of deep learning, its biological inspirations, and his research philosophy.
on Dec 9, 2014 in Backpropagation, Deep Learning, Geoff Hinton, Michael Jordan, Neural Networks, Neuroscience, Zachary Lipton
If programming languages were vehicles, what would be R, Python, SAS, and SQL?
We expand on the idea "If programming languages were vehicles" and examine what would be the main languages for data science: R, Python, SAS, and SQL?
on Dec 6, 2014 in Programming Languages, Python, R, SAS, SQL
Tableau Top 10 Trends in Business Intelligence for 2015
Tableau Software presents its top 10 trends in business intelligence in 2015, including transformed data governance, improved social intelligence, and organizational analytics.
on Dec 6, 2014 in Business Intelligence, Cloud Analytics, Data Governance, Data journalism, Mobile, Predictions for 2015, Tableau
Data Scientist: Owning Up to the Title
Regardless of how Data Science or Data Scientist is defined, if you are going to use the word "scientist" in your title, you are going to be held accountable for it.
on Dec 5, 2014 in Career, Data Science Skills, Data Scientist, Salary, Sean McClure
Interview: Igor Elbert, Gilt on Boosting Sales through Analytics-curated Shopping
We discuss Analytics at Gilt, unique Analytics challenges of a flash sales portal, consumer behavior across channels, interesting insights, advice and more.
on Dec 4, 2014 in Advice, Big Data, Consumer Analytics, Curation, Gilt, Insights, Mobile, Personalization, Sales
Sisense 2015 predictions for BI, Big Data
Mobile devices, text analytics, Google Glass, and data intelligence will be key to the evolution of business intelligence in 2015 according to Adi Azaria and Eldad Farkash of SiSense.
on Dec 3, 2014 in BI, Google Glass, Mobile, Predictions, Predictions for 2015, Sisense
Geoffrey Hinton talks about Deep Learning, Google and Everything
A review of Dr. Geoffrey Hinton’s Ask Me Anything on Reddit. He talked about his current research and his thought on some deep learning issues.
on Dec 1, 2014 in Deep Learning, DeepMind, Geoff Hinton, Google, Neural Networks, Reddit, Yann LeCun
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