Yearly Archives: 2016

Rick Wicklin 0
The empty-space distance plot

How far away is the nearest hospital? How far is the nearest restaurant? The nearest gas station? These are commonly asked questions whose answers depend on the location of the person asking the question. Recently I showed an algorithm that enables you to find the distance between a set of

Analytics | Students & Educators
Georgia Mariani 0
ESSA – accountability, indicators and analytics to drive informed decision making

Last December, The Every Student Succeeds Act (ESSA) was signed into law to ensure opportunity for all students in the United States. As part of this federal legislation, states now have the flexibility to design their own accountability systems following certain parameters outlined in ESSA. These accountability systems include academic and non-academic indicators. By

Analytics
Elizabeth Bautista 0
La orden perfecta

La volatilidad de demanda y expansión de portafolio de productos, así como la persistente presión de alinear los costos de la cadena de suministro con la demanda del mercado, son solo algunos de los retos que enfrentan las organizaciones de industrias como manufactura, alimentos y bebidas, farmacéuticas o automotriz. La

Data Management
Jim Harris 0
How do you define data governance?

Data governance has been the topic of many of the recent posts here on the Data Roundtable. And rightfully so, since data governance plays such an integral role in the success of many enterprise information initiatives – such as data quality, master data management and analytics. These posts can help you prepare for discussing

Data Management | Machine Learning
Charlie Chase 0
Machine learning changes the way we forecast in retail and CPG

Machine learning is taking a significant role in many big data initiatives today. Large retailers and consumer packaged goods (CPG) companies are using machine learning combined with predictive analytics to help them enhance consumer engagement and create more accurate demand forecasts as they expand into new sales channels like the

Analytics | Data Visualization
Christine Komander 0
Data Scientist – Data Artist – Data Journalist – wie bitte, wer?

Nachdem der Data Scientist mittlerweile bei allen Digitalisierungsthemen und der damit einhergehenden Analytik in aller Munde ist, geistern nun auch etliche andere Rollendefinitionen durch die Positionierungen der verschiedenen Anbieter. Ein paar dieser neuen Bezeichnungen würde ich gerne aufgreifen und erklären, zusätzlich ein paar Denkanstöße mitgeben.

Data for Good | Data Management
Dan Stevens 0
A playbook for analyzing real world intelligence in a health care setting

Real world data collected in a functioning health care setting instead of a controlled clinical environment can provide opportunities for new and deeper insights across life science and health care organizations. However, managing, analyzing and extracting actionable information from the varied available sources can present unique challenges. The sheer size of these

Fraud & Security Intelligence
Michael Rabin 0
„Fraudsters love digital“

Wer glaubt, die Digitalisierung hätte dem Thema Versicherungsbetrug den Garaus gemacht, der irrt – gewaltig. Nach wie vor ist einer von zehn gemeldeten Schäden und Ansprüchen erfunden oder manipuliert. Der Schaden: mindestens 4 Milliarden Euro allein in Deutschland – und das nur bei Sachversicherungen, also ohne Lebens- oder Krankenversicherungen. Den

Rick Wicklin 0
Visualize a weighted regression

What is weighted regression? How does it differ from ordinary (unweighted) regression? This article describes how to compute and score weighted regression models. Visualize a weighted regression Technically, an "unweighted" regression should be called an "equally weighted " regression since each ordinary least squares (OLS) regression weights each observation equally.

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