Collaboration and cooperation are a fact of life in every organization. However, how it's done in practice and how effective it is can vary significantly. What drives these differences and variations? Research shows that organizational culture is an important influence, especially the value placed on two main factors: relationships and
Interview mit Lehrstuhlinhaber für Data Science der Hochschule für angewandte Wissenschaften in Darmstadt, Professor Markus Döhring.
Technologies have driven business progress by providing innovative and effective ways to solve business problems. The financial sector is one of the most accepting of innovation, and the growing pressure from fintechs has encouraged other businesses to act. This has driven rapid incorporation of artificial intelligence (AI) processes and machine
Finite-precision computations can be tricky. You might know, mathematically, that a certain result must be non-negative or must be within a certain interval. However, when you actually compute that result on a computer that uses finite-precision, you might observe that the value is slightly negative or slightly outside of the
Text analytics: Theoretically, a telecoms company, say, could use topic modelling to look at product reviews divided into themes.
This is the decade of action. The United Nations urges this current generation to end extreme poverty, win the race against climate change and conquer injustice and gender inequality. But how do people take action when many are working and learning from home? How can individuals put the Sustainable Development
Seconds are passing us by at this very moment, and there's not much you can do in one second. Well, there is something. Let's say smile, take a deep breath, close your cellphone and say thank you. Within a second you can also make decisions: click the buy button in
A note from Udo Sglavo: The need for randomization in experimental design was introduced by the statistician R. A. Fisher in 1925, in his book Statistical Methods for Research Workers. You would assume that developing a successful treatment for COVID-19, the illness caused by the SARS-CoV-2 virus, will eventually conclude in
When the automatic time-series techniques can't produce adequately forecasts, a tool should be equipped with multiple machine learning techniques.
When working with a probability distribution, it is useful to know how to compute four essential quantities: a random sample, the density function, the cumulative distribution function (CDF), and quantiles. I recently discussed the Poisson-binomial distribution and showed how to generate a random sample. This article shows how to compute
Now that we are many months into the COVID-19 pandemic, I've started going back and reexamining the data for lessons or trends (you might say hindsight is 20/20). This time, I want to explore how COVID-19 has been spreading around the US. I do this by using a graphical idea
September is Suicide Prevention Awareness Month and Recovery Month, which have the important goals of preventing suicide and promoting the idea that recovery from behavioral health conditions is achievable. Amid an unprecedented year of stressors, 2020’s awareness months around behavioral health conditions have become more relevant to far more people. In recognition of the challenges and changes in people’s work lives,
The more information they have to learn from, the better. Naturally, this will not allow you to predict global pandemics or financial collapses.
The Poisson-binomial distribution is a generalization of the binomial distribution. For the binomial distribution, you carry out N independent and identical Bernoulli trials. Each trial has a probability, p, of success. The total number of successes, which can be between 0 and N, is a binomial random variable. The distribution
When you get something new, the hope is that it will be better than the old thing it's replacing. As I often do, I asked my Facebook friends to provide a random picture for my blog - in this case, a picture of one of their new/recent purchases. My friend
The Text Investigation Framework is a flexible solution for addressing text challenges across several domains. It was designed to create a process for turning unstructured text data into a decisioning system.
In the future this kind of data analysis can help to make an even better exoskeleton!
Les institutions gouvernementales que ce soit pour la défense, les transports, les services publics, la sécurité, ou les soins de santé ont un défi et une opportunité à traiter : donner un sens à d'énormes volumes de textes non structurés qui ne font que croître. Plus de 80 % de
A intensidade do choque sobre a economia mundial em decorrência da pandemia do COVID-19 ainda precisa ser determinada. Conforme os negócios desenvolvem, seus próprios entendimentos sobre como eles podem ser afetados, dois elementos constantes em todas as avaliações são incertezas e complexidade. O futuro depende de diversos fatores, incluindo políticas
Digitalization, big data and AI are changing the role of insurance and, therefore, the role of actuaries. A lot of reports – like McKinsey’s Insurance 2030, Deloitte’s “The Exponential Actuary," or the Big Data and Insurance report by the Geneva Association (a leading think tank of insurance CEOs) depict aspects
Learn how SAS and Microsoft aim to meet FinServ’s evolving analytics demands through a new strategic partnership.
Many textbooks and research papers present formulas that involve recurrence relations. Familiar examples include: The factorial function: Set Fact(0)=1 and define Fact(n) = n*Fact(n-1) for n > 0. The Fibonacci numbers: Set Fib(0)=1 and Fib(1)=1 and define Fib(n) = Fib(n-1) + Fib(n-2) for n > 1. The binomial coefficients (combinations
기업이 데이터 기반의 의사결정을 하기 위해서는 AI를 특정 영역이 아닌 분석 라이프사이클 전반으로 확대하고, 이 라이프 사이클은 의사결정 프로세스와 연결돼야 합니다. 개방된 플랫폼에서 분석 시간을 줄이고, 그 결과를 운영시스템에 빠르게 적용해 더 큰 비즈니스 가치를 실현할 수 있어야 합니다. 지난 시리즈에서는 모델링 작업을 위한 피처 자동 생산과 자동 튜닝 정도로
Five years ago, 193 countries joined forces and formed the United Nation’s Sustainable Development Goals. These goals, which are commonly referred to as the Global Goals, serve as a universal promise—an ambitious pledge to build a better future for people and planet by 2030. This year marks the final 10-year
We will combine three separate SAS Viya capabilities to create an application that can manage multiple models, interpret model outputs, and replace the production model if necessary
Innovation is currently an extremely desirable feature for every country. However, a ranking published by the European Commission shows that Poland is struggling to create an environment that supports development. Development and innovation need people with competence in new technologies, such as analytics. Last year’s Modelling for Business conference showed
Mit Hans-Peter Zorn, AI-Influencer und Praktiker, im AI Talk.
What analytics architecture is needed to support an accelerator? I have recently been working with my colleague Jussi Martikka to extract lessons from the City of Helsinki’s AI Experimentation Accelerator work. We used the steps of the accelerator process to define the analytics architecture needed. This was a useful way
A previous article discussed how to solve regression problems in which the parameters are constrained to be a specified constant (such as B1 = 1) or are restricted to obey a linear equation such as B4 = –2*B2. In SAS, you can use the RESTRICT statement in PROC REG to
The practice of business forecasting falls well short of the potential exhibited in academic research and forecasting competitions. Chris Chatfield* noted this in a 1986 editorial in the International Journal of Forecasting, where he called on statisticians to find a better way of communicating the better use of existing methods
