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TwIn part one of this series, Clark Twiddy, Chief Administrative Officer of Twiddy & Company, shared some best practices from the first of three phases of Twiddy’s journey to becoming a data-driven SMB. This post focuses on phases two and three of their journey. (Read the whole series here.) Phase
Todd Wright says Hadoop can be difficult – but data management can help.
최근 양귀비 불법 재배와 연예인 마약 사건이 잇달아 발생하면서 국내에서는 멀게 느껴졌던 마약 범죄에 대한 관심이 높아지고 있습니다. 실제 관세청은 올해 상반기 마약 밀수가 전년 대비 2.6배 증가했으며, 밀수된 마약의 종류까지 다양해졌다고 발표했는데요. 국가는 이처럼 급증하는 마약 밀수를 차단하기 위해 조사 인력과 장비를 확충하고, 검색 기법을 적극 개발하겠다고 밝혔습니다. 이미
Datasets are rarely ready for analysis, and one of the most prevalent problems is missing data. This post is the first in a short series focusing on how to think about missingness, how JMP13 can help us determine the scope of missing data in a given table, and how to
St. Louis Union Station welcomed its first passenger train on Sept. 2, 1894 at 1:45 pm and became one of the largest and busiest passenger rail terminals in the world. Back in those days, the North American railroads widely used a system called Timetable and Train Order Operation to establish
El ecosistema actual de marketing es más complejo que nunca, por lo tanto es imposible gestionarlo sirviéndose únicamente de la intuición. Los clientes son más exigentes y siempre están cambiando entre un creciente número de canales, la competencia sigue aumentando, los presupuestos se desploman y las decisiones tienen que tomarse
In the digital world where billions of customers are making trillions of visits on a multi-channel marketing environment, big data has drawn researchers’ attention all over the world. Customers leave behind a huge trail of data volumes in digital channels. It is becoming an extremely difficult task finding the right
In May, the New York Times published an article “The Little Known Statistician Who Taught Us to Measure Teachers” which profiled the life of Dr. Bill Sanders. The author reflected on Dr. Sanders’ life and work improving education for all students. For those of us in education, Dr. Sanders’ work
SAS power users (and actually, power users of any application) like to customize their environment for maximum productivity. Long-time SAS users remember the KEYS window in SAS display manager, which allows you to assign SAS commands to "hot keys" in your SAS session. These users will invest many hours to
My previous blog post focused on a graph, showing the % of women earning STEM degrees in various fields. While that graph was was designed to answer a very specific question, let's now look at the data from a broader perspective. Let's look at the total number of STEM degrees
An important problem in machine learning is the "classification problem." In this supervised learning problem, you build a statistical model that predicts a set of categorical outcomes (responses) based on a set of input features (explanatory variables). You do this by training the model on data for which the outcomes
Phil Simon chimes in on the immediacy of enterprise data.
For the past several years, efforts have been under way to recruit more women into the STEM (science, technology, engineering, and math) fields. I recently saw an interesting graph showing the percentage of bachelor's degrees conferred to women in the US, and I wondered if I could tweak that graph
I started my training in machine learning at the University of Tennessee in the late 1980s. Of course, we didn’t call it machine learning then, and we didn’t call ourselves data scientists yet either. We used terms like statistics, analytics, data mining and data modeling. Regardless of what you call
Artificial intelligence promises to transform society on the scale of the industrial, technical, and digital revolutions before it. Machines that can sense, reason and act will accelerate solutions to large-scale problems in myriad of fields, including science, finance, medicine and education, augmenting human capability and helping us to go further,