Yearly Archives: 2016

Rick Wicklin 0
The smooth bootstrap method in SAS

Last week I showed how to use the simple bootstrap to randomly resample from the data to create B bootstrap samples, each containing N observations. The simple bootstrap is equivalent to sampling from the empirical cumulative distribution function (ECDF) of the data. An alternative bootstrap technique is called the smooth

Analytics | Machine Learning
Andreas Gödde 0
Megatrends im Analytics Bereich

Die Fortschritte im Bereich Analytics sind rasant. Während vor wenigen Jahren nur wenige Experten Themen wie Machine Learning, Data Mining oder Cognitive Computing diskutierten, beschäftigen sich jetzt auch Nicht-Mathematiker und Fachbereiche mit diesen Begriffen und versuchen, diese einzuordnen. In meinen Gesprächen mit CIOs, zunehmend auch mit Chief Digital Officers, treffe

Data Visualization
Sanjay Matange 0
Clinical Graphs: A1c Plot

Last week I was visiting San Diego for the SANDS conference.  I always enjoy this conference as I get to interact closely with the users to hear of their pains and innovative solutions to creating Clinical Graphs. In the conference Ed Barber asked about displaying A1c data along with some

David Cosgrave 0
How to Pokemon Go-to-Market

Has there ever been an app that’s captured the world’s imagination as quickly as Pokemon Go? The usage statistics are mind-blowing, and whether or not the world has reached “peak Pokemon Go” yet, this will doubtless be a short-lived fad. But this could be the app that brings augmented reality and

Analytics
Monika Swoboda 0
5 wskazówek jak połączyć analitykę i Customer Journey - istota znajomości klienta i danych (#2 i #3)

W poprzednich wpisach dowiedzieliśmy się czym jest Customer Journey, dlaczego jest tak istotne i od czego zacząć tworzenie mapy ścieżki klienta. W tym wpisie skupimy się natomiast na tym jak istotna jest znajomość danych, którymi operujemy oraz preferencje i potrzeby naszych odbiorców. DOBRA RADA #2: Dbaj o znajomość potrzeb klienta

Data Management
Joyce Norris-Montanari 0
Clean-up woman: Part 1

If your enterprise is working with Hadoop, MongoDB or other nontraditional databases, then you need to evaluate your data strategy. A data strategy must adapt to current data trends based on business requirements. So am I still the clean-up woman? The answer is YES! I still work on the quality of the data.

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