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KDnuggets Home » News » 2013 » Jul » Webcasts » Upcoming July Webcasts on Analytics, Big Data, Data Science 13:n17 )

Upcoming July Webcasts on Analytics, Big Data, Data Science


Coming soon: Discovery analytics, Analytically Speaking, Survival Analysis, Data Discovery, Enterprise Informatics, When Hadoop Is Not Enough, Data Mining: Failure to Launch, and SciDB-Py.



Upcoming webcasts in July 2013 – see the full list on KDnuggets page on
Webcasts & Webinars on Analytics, Big Data, Data Mining, and Data Science.

When Event
Jul 17
10 AM PT
1 PM ET
How Companies Use Discovery Analytics to Outsmart Competitors, by Richard Hackathorn of Bolder Technology and Tasso Argyros of Teradata.
Jul 17
10 AM PT
1 PM ET
Analytically Speaking, on predictive analytics, data mining, customer relationship management, Web analytics, fraud detection, credit risk management. By JMP and Bart Baesens.
Jul 17
8 AM PT
11 AM ET
Using Survival Analysis for Marketing Attribution, by Andrie de Vries, Revolution Analytics.
Jul 17
1 PM PT
4 PM ET
Get Smart: The Present and Future of Data Discovery, Hot Technologies of 2013 with Bloor, Fitzgerald & Neutrino BI.
Jul 18
8 AM PT
11 AM ET
Enterprise Informatics: Unlock the full transformative power of your data, by Gary Kennedy, Founder and CEO, Remedy Informatics and FierceBigData.
Jul 18
11:30 AM PT
14:30 PM ET
When Hadoop Is Not Enough, by Think Big Analytics.
Jul 18
1 pm PT
4 pm ET
Data Mining: Failure to Launch, by The Modeling Agency.
Jul 25
10 AM PT
1 PM ET
SciDB-Py: Big Analytics for Python Users without Big Hassles, by Bryan Lewis, Chief Data Scientist, Paradigm4; Peter Wang, President, Continuum Analytics; and Jake Vanderplas, Postdoc, U. of Washington.
Jul 29
11 AM PT
2 PM ET
Staying Ahead of the Social Conversation in an Always On World, by Jamie de Guerre, VP of Products, Topsy and Data Informed.
Jul 30
9 AM PT
noon ET
Analytics Competitor Secrets Revealed: How they Recruit, Hire and Retain their Analytics Dream Teams, by Talent Analytics.
Jul 30
10 AM PT
1 PM ET
5 Key Things to Know About Selecting a Big Data Solution, by MapR and Datameer.


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