A hot button issue this election season was the need to determine the eligibility of people for various government programs like the Affordable Care Act (ACA), Medicare and Medicaid, or entry into the United States as a migrant refugee. “Look, we’re facing the worst refugee crisis since the end of
What would happen if we could ask any type of scientific or clinical question about patients, and then go out and find the data to answer our questions? With "real-world data," we can do just that. Real-world data is all medicinal product data that comes from real-life patients. In contrast,
.@philsimon says that data-governance professionals will need to be more agile than ever.
In recent healthcare blogs I’ve looked at the need to drive more value from the UK’s National Health Service (NHS) and how this relies upon the ability to make decisions based on robust, data-driven insights. But what value will these decisions have if they're not founded on a mature data
With the first debate between the two candidates behind us and the culmination of the US presidential election drawing near, who wouldn’t love to predict the winner? I don't have a crystal ball, but I do have the power of unstructured text analytics at my fingertips. With the help of
I recently celebrated my one year anniversary at SAS. I don’t use the word celebrated passively; there was delicious food, time for reflection, and of course selfies. I'm still in awe of this work environment and my awesome team. So what have I learned in this past year? Mayonnaise mixed
Data governance can encompass a wide spectrum of practices, many of which are focused on the development, documentation, approval and deployment of policies associated with data management and utilization. I distinguish the facet of “operational” data governance from the fully encompassed practice to specifically focus on the operational tasks for
Versicherungen stehen massiv unter Druck. Negative Zinsen und ein hoher regulatorischer Druck führen auch nicht gerade zu Euphorie (versicherungswirtschaft-heute.de). Die Branche klagt, all das sei operativ gar nicht zu schaffen. Was tun? Niedrigzinsumfeld ändern? Geht nicht. Regulatorik beeinflussen? Geht nur partiell. Also bleibt nur, an Effizienz und Automatisierung von Prozessen
In many ways financial services is about risk management. Regulatory pressures such as BCBS 239, stress-testing, IFRS9, Solvency II and the Fundamental Review of Trading Book have hugely strengthened that focus. But there are other concerns too. Cost pressures are increasingly important, as is the rise of challengers to the
Gender and race discrimination has been banned in most countries for many years, although gender did have specific exclusions for the insurance industry, where the risk for males and females could be shown to substantially different (e.g. females have a higher life expectancy than males). In the European Union (EU)
It's the age of big data and the internet of things (IoT), but how will that change things for insurance companies? Do insurers still need to consider classic data warehouse concepts based on a relational data model? Or will all relevant data be stored in big data structures and thus
Data monetization, at its simplest, is the process of turning data into bottom-line value for a company -- often through improving efficiency and/or customer experience, and building customer loyalty as a result. This may sound simple, but in practice, it’s anything but. Good data, advanced analytics and real-time decision making
With the Pokémon Go craze sweeping the world, techies and programmers are looking to apply their skills to gain an advantage over the average user. In this blog post, I show how to use some of SAS' geospatial analytics capabilities to capture a Pikachu. Let's say you know of a building that has
Being able to communicate effectively is the most important of all life skills. Communication can make or break our world. It can build up healthy and productive relationships or break them forever. For example, how many times each one of us has experienced quarrels that are just a result of
Auditability and data quality are two of the most important demands on a data warehouse. Why? Because reliable data processes ensure the accuracy of your analytical applications and statistical reports. Using a standard data model enhances auditability and data quality of your data warehouse implementation for business analytics.
The Internet of Things (IoT) is drastically changing our lives, whether this is at home, in the car, at work or even in the street. Gartner has predicted that by 2020, 20.8 billion devices will be connected. Moreover, the potential economic impact of IoT by 2025 is estimated to be
Fellow Roundtable writer David Loshin has commented in the past that: "MDM is popular because it is presented as a cure-all solution to all data problems in the organization." Many people see master data management (MDM) as the silver bullet to all of their business and data woes. But in
It's an exciting time to be in the automotive and transportation industry. The opportunities for business transformation and growth are enormous – and those companies that lead in implementing new ways to drive intelligent customer interactions will capture the greatest share of new revenue streams. For those of us fortunate enough
Insurers are embracing digital to meet the demands of modern consumers. And, of course, there are obvious benefits to them from less costly, more streamlined interactions with their customers. The trouble is that digitisation comes with a major health warning: Unless insurers put suitable measures in place, they're at risk
"Correlation does not imply causation.” Does that bring back memories from your college statistics class? If you cringe when you hear those words, don’t worry. This phrase is still relevant today, but is now more approachable and easier to understand. Here at SAS, we use SAS® Visual Analytics to make
SAS Global Forum 2016のユーザープログラムでの発表論文を、”Machine Learning”というキーワードで検索し、機械学習関連の論文を集めてみました。 SAS Global Forum 2016 Proceedings - Machine Learning 関連のユーザーやパートナーによる講演・論文 Turning Machine Learning Into Actionable Insights 機械学習=意思決定プロセスの自動化 PROC IMSTAT Boosts Knowledge Discovery in Big Databases (KDBD) in a Pharmaceutical Company 日本の塩野義製薬様の機械学習への取り組み Diagnosing Obstructive Sleep Apnea: Using Predictive Analytics Based on Wavelet Analysis in SAS/IML®
Contrary to popular belief, it is okay to: 1.Let yourself feel emotions other than happiness. Happiness is great. I love happiness. But to feel happy 100% of your life is not human. Happiness doesn’t mean denying other feelings like frustration, sadness, disappointment, etc. It takes some confidence and skill to allow yourself to feel
Have you ever used SAS to produce reports for publishing? Have you ever thought of or been told about suppressing data in such reports? Why do we need to suppress (in the sense of withholding, concealing, obscuring or hiding) data in published reports? The reason is simple - in order
.@philsimon on the specific risks to data quality posed by cloud computing.
One of my colleagues often asks me “What’s new in insurance”. For an industry that is risk adverse, change does not come easily. In the past we have discussed innovations concerning telematics, drones, wearables devices and even weather data. However when he asked me last week and I responded that
In my SAS Press book Business Statistics Made Easy in SAS® I place a strong focus on the skill of extrapolating analytics/statistical outcomes to key business implications (similar techniques can be used to link statistics to other key societal outcomes). Unfortunately, business analytics often stops short of defining the impact
In the past, we've always protected our data to create an integrated environment for reporting and analytics. And we tried to protect people from themselves when using and accessing data, which sometimes could have been considered a bottleneck in the process. We instituted guidelines and procedures around: Certification of the data
How many of us have used the phrases… It’s a piece of cake Anyone can do it It’s as easy as ABC I could do it with my eyes shut When it comes to business intelligence it should be “easy peasy” but for many organization it can still be a
¿Cuáles son los retos del sector financiero en Latinoamérica? ¿Cómo detectar y prevenir el fraude en los bancos y empresas de seguros de una vez por todas? ¿Podemos reducir el riesgo de pérdidas relacionadas con estas conductas fraudulentas? ¿Cómo minimizar los daños e impacto en la reputación organizacional? La lucha
A recent survey by Capgemini found that 78% of insurance executive interviewed cited big data analytics as the disruptive force that will have the biggest impact on the insurance industry. That’s the good news. The bad news is that unfortunately traditional data management strategies do not scale to effectively govern
