- Kanri Distance Calculator(tm) – patented solution applying power of Big Data to an Individual - Mar 21, 2017.
Kanri combination of patented statistical and process methods provide a powerful ability to evaluate large data, tells users the exact distance from target, and variable contributions for participant. Free trial and 88% KDnuggets discount for the first 100 buyers.
- Analytics 101: Comparing KPIs - Mar 20, 2017.
Different business units in the organisation have different behaviours (e.g. turnover rate) and they can’t be compared with each other. So, how can we tell whether the changes in their behaviour are reasons for concern?
- The Top 5 KPIs to Consider When Measuring Your Campaign - Feb 28, 2017.
When it comes to measuring marketing campaign performance or analysing customers in any business, below top 5 Key Performance Indicators (KPIs) needs to be used to strategically drive the business.
- Marketing Metrics and Analytics Summit, New York, Apr 26-27 – KDnuggets Offer - Feb 2, 2017.
Designed to be at the intersection of marketing, data science, and analytics, this summit will discuss common challenges and pain points, discover new cutting-edge technology tools and solutions, and to connect and network. Use discount code KDN15 to save.
- The Best Metric to Measure Accuracy of Classification Models - Dec 7, 2016.
Measuring accuracy of model for a classification problem (categorical output) is complex and time consuming compared to regression problems (continuous output). Let’s understand key testing metrics with example, for a classification problem.
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- Metrics Gone Wrong – How Companies Are Optimizing The Wrong Way - Apr 20, 2016.
A critique of the over-abundant and misguided pursuit of metric completeness, and how it can result in incorrect "optimization."
- Lift Analysis – A Data Scientist’s Secret Weapon - Mar 22, 2016.
Gain insight into using lift analysis as a metric for doing data science. Understand how to use it for evaluating the performance and quality of a machine learning model.
- Employee Engagement – a Tricky Metric for Predictive Analytics - Feb 22, 2016.
Predictive analytics for workforce has developed significantly in recent times. Here we focus on an important discovery about Employee Engagement metric – why it is tricky.
- Interview: Joseph Babcock, Netflix on Curiosity and Courage – Key for Success in Data Science - Jun 17, 2015.
We discuss discovery vs. personalization, advice, trends, desired skills in data scientists, and more.
- Interview: Sheridan Hitchens, Auction.com on Customer Lifetime Value as the Cornerstone for Marketing Analytics - May 15, 2015.
We discuss Customer Lifetime Value (CLV) metric, maturity level for the CLV metric, different models for calculating it, challenges in designing strategy based on CLV and tackling attribution.
- Interview: Haile Owusu, Mashable on Riding the Wave of Viral Content - Apr 29, 2015.
We discuss Mashable’s milestones, data-driven digital publishing, digital media tracking, viral prediction, and Mashable Velocity.
- Sports Analytics Innovation Summit 2014 San Francisco: Day 2 Highlights - Oct 11, 2014.
Highlights from the presentations by Analytics leaders from San Francisco Giants, New York University and LA Dodgers on day 2 of Sports Analytics Innovation Summit 2014 in San Francisco.
- Interview: Arpit Gupta, CEO, Actionable Analytics on Enterprise Challenges in Big Data and Cloud - Aug 24, 2014.
We discuss Actionable Analytics start-up, enterprise challenges in Big Data, relationship with cloud computing, metrics vs. insights, Big Data expectations and more.
- Interview: Pallas Horwitz, Blue Shell Games on Why Data Science is So Critical for Gaming Studios - Aug 14, 2014.
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.
- Top KDnuggets tweets, Aug 8-10: Forget SQL vs NoSQL. New trend is HTAP: Hybrid Transaction/Analytical Processing - Aug 11, 2014.
Forget SQL vs NoSQL. New trend is HTAP: Hybrid Transaction/Analytical Processing; Metrics that Matter - The Key to Perfect Dashboards; Machine Learning Tutorial: The Max Entropy Text Classifier ; Six Thinking Hats and the Life of a Data Scientist.
- Metrics that Matter – The Key to Perfect Dashboards - Aug 9, 2014.
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.
- Interview: Aparna Pujar, eBay on Evolution of Behavior Analytics for User Engagement - Jul 25, 2014.
We discuss Behavior Analytics vs. Web Analytics, important metrics for user engagement, challenges of behavior insights domain, future of multi-screen analytics, key soft skill and more.
- Interview: Cliff Lyon, Stubhub on Mastering Recommendation & Personalization Analytics Part 2 - Jul 19, 2014.
We discuss current trends, future vision, interesting correlations, privacy concerns, and advice for Data Science practitioners.
- Interview: Cliff Lyon, Stubhub on Mastering the Art of Recommendation and Personalization Analytics - Jul 18, 2014.
We discuss challenges in designing recommendation and personalization systems, how to select the right metrics, and learning regarding presentation of recommendation on different channels.
- Manufacturing Analytics Summit 2014 Chicago: Day 2 Highlights - Jul 17, 2014.
Highlights from the presentations by Analytics leaders from World Fuel Services, Vigilent Corporation, Caterpillar and SunEdison on day 2 of Manufacturing Analytics Summit 2014 in Chicago.
- 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.
- Amazon: Sr. Business Intelligence Engineer, Video Advertising - Feb 18, 2014.
An outstanding BI engineer to design how our data will be stored and used, extract meaning from billions of data points, and automate processes to feed the right data into our machine learning engine.