Nov
2014 Dec Opinions, Interviews, Reports
All (103) | Courses, Education (6) | Meetings (6) | News, Features (24) | Opinions, Interviews, Reports (32) | Publications (4) | Software (10) | Top Tweets (16) | Webcasts (5)
- Interview: Ben Werther, CEO, Platfora on Insightful Analytics for Big Data
- Dec 30, 2014.
We discuss the challenges in implementing end-to-end solutions for Big Data, Platfora use cases, Big Data trends, advice and more.
- Interview: Ben Werther, CEO, Platfora on Why Big Data Needs Self-Service Tools
- Dec 29, 2014.
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.
- Interview: Mac Devine, CTO, IBM Cloud on the Conflux of Cloud, IoT & Big Data
- Dec 26, 2014.
We discuss the implications of Cloud Speed of technological advancement, significant trends in Internet of Things (IoT), future of cloud computing and more.
- Stanford’s AI100: Century-Long Study on Effects of Artificial Intelligence on Human Life
- Dec 26, 2014.
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.
- Interview: Mac Devine, CTO, IBM Cloud on the Fast Approaching Perfect Storm
- Dec 24, 2014.
We discuss why we should anticipate a technology perfect storm soon, Enterprise IT challenges, distinct capabilities of IBM BlueMix and more.
- Hot or Not: Data Science Trends in 2015
- Dec 24, 2014.
CrowdFlower infographic predicts the hot trends for data science in 2015 and which trends will fade away.
- The Big Data of Wearables
- Dec 23, 2014.
Wearables are becoming more common, creating real-time demands on the data-driven systems behind them for applications like forecasting and recommender systems.
- DIY Crawlers vs. Crawlers as Service
- Dec 22, 2014.
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.
- FICO Chief Analytics Officer Sees a Post–Big Data World in 2015
- Dec 21, 2014.
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.
- “Vite fait, bien fait” – Averaging improves both accuracy and speed of time series classification
- Dec 21, 2014.
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.
- 2015 Predictions: What will happen to big data and data science?
- Dec 21, 2014.
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.
- Interview: Brian Hampton, SF 49ers on Competitive Edge through Football Analytics
- Dec 20, 2014.
We discuss the shortcomings of football analytics, how San Francisco 49ers use analytics, future of football analytics, advice and more.
- Interview: Brian Hampton, San Francisco 49ers on Playing Football the Analytics Way
- Dec 19, 2014.
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.
- Interview: Peter Alvaro, UC Berkeley, on Managing Asynchrony and Partial Failure
- Dec 18, 2014.
We discuss the challenges in simultaneously managing asynchrony and partial failure, the problem of composition, research motivation, trends and more.
- Interview: Peter Alvaro, UC Berkeley, on Consistency Challenge in Distributed Systems
- Dec 17, 2014.
We discuss the performance limitations caused by treating datastore as black box, consistency as an application-level property, Dedalus and LDFI approach for testing.
- 8 Things to Check when you analyze Twitter data
- Dec 16, 2014.
A review of biases and issues on large scale studies of human behavior in social media discussed by a recent paper published on Science.
- Analyze And Visualize Chatter from Nigeria Elections 2015
- Dec 16, 2014.
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.
- Open Innovation in the Age of Big Data
- Dec 15, 2014.
Open platforms for data analysis are more important than ever with big data and increasing access to heterogeneous data sources for analysts.
- Our Iceberg is Melting.. Now where is that Data Scientist?
- Dec 15, 2014.
Marketing analytics teams could improve their effectiveness by employing a marketing effectiveness strategy similar to that used by penguins dealing with their iceberg melting.
- KDnuggets Interview: Paul Zikopoulos, IBM on Big Data Opportunities and Challenges
- Dec 14, 2014.
We discuss the value of Big Data for SMBs, how Cognitive will impact Big Data, IBM’s distinction from competition, significant trends and more.
- KDnuggets Interview: Paul Zikopoulos, IBM on Why Big Data needs Polyglots
- Dec 13, 2014.
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.
- 2015 Predictions – What’s Next for Data Scientists?
- Dec 12, 2014.
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.
- IIA 2015 Analytics Predictions
- Dec 11, 2014.
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?
- Interview: Daqing Zhao, Macys.com on Building Effective Data Models for Marketing
- Dec 11, 2014.
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.
- Interview: Daqing Zhao, Macys.com on Advanced Analytics for Marketing in the Big Data era
- Dec 10, 2014.
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.
- Geoff Hinton AMA: Neural Networks, the Brain, and Machine Learning
- Dec 9, 2014.
In a wide-ranging Q&A, Geoff Hinton addresses the future of deep learning, its biological inspirations, and his research philosophy.
- If programming languages were vehicles, what would be R, Python, SAS, and SQL?
- Dec 6, 2014.
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?
- Tableau Top 10 Trends in Business Intelligence for 2015
- Dec 6, 2014.
Tableau Software presents its top 10 trends in business intelligence in 2015, including transformed data governance, improved social intelligence, and organizational analytics.
- Data Scientist: Owning Up to the Title
- Dec 5, 2014.
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.
- Interview: Igor Elbert, Gilt on Boosting Sales through Analytics-curated Shopping
- Dec 4, 2014.
We discuss Analytics at Gilt, unique Analytics challenges of a flash sales portal, consumer behavior across channels, interesting insights, advice and more.
- Sisense 2015 predictions for BI, Big Data
- Dec 3, 2014.
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.
- Geoffrey Hinton talks about Deep Learning, Google and Everything
- Dec 1, 2014.
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.
Netflix’s Polynote is a New Open Source Framework to Build Better Data Science Notebooks