IOT's twin challenges: Compliance and privacy
.@philsimon raises some chilling questions about the IoT and current threats.
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It’s a long, long road … von den Daten zur Entscheidung. Aber mit Analytics-as-a-Service wird die Reise einfacher
In meinem letzten Beitrag habe ich mich mit Colin Gray vom SAS Analytics-on-Demand-Team über die verschiedenen Optionen unterhalten, die Unternehmen zur Verfügung stehen, wenn sie in Analytics einsteigen – eine davon ist Analytics-as-a-Service. Neben dem technischen Aspekt gilt es, auch den strategischen und organisatorischen zu berücksichtigen. Daher soll es hier
Monte Carlo estimates of joint probabilities
Monte Carlo techniques have many applications, but a primary application is to approximate the probability that some event occurs. The idea is to simulate data from the population and count the proportion of times that the event occurs in the simulated data. For continuous univariate distributions, the probability of an
Should data scientists buy into the DevOps philosophy?
DevOps is enjoying a lot of attention at the moment, mostly because of its promise to increase software quality at lower cost. DevOps is a hybrid term linking development and operations. It's a philosophy that focuses on improving efficiencies in how we build and deliver software, solutions and the supporting environments.
A simple framework for getting started with data compliance (Part 2 )
At its core, data compliance is built on simple foundations. Dylan Jones closes this series by explaining the remaining components of the "4F framework."
Analytics - helping your 'dots' tell their story
Does your data just look like a bunch of dots? Would you like to bring those dots to life so they can tell their story? This example shows how to make some voter-registration dots a bit more lifelike, so you can see what they're saying. You can apply the same
2020 vision for utilities: What’s the prescription?
Do you remember the 90s? It seemed like every company and organization had some sort of strategic plan that had “2000” in its title. And they were all going to achieve and exceed these Year 2000 goals … if their systems didn’t crash at 12:00:01 on January 1, 2000! So
Data Scientists im Gesundheitswesen – Chancen im morbiditätsorientierten Risikostrukturausgleich
Seit 2009 sollen der Gesundheitsfonds und der morbiditätsorientierte Risikostrukturausgleich in der deutschen gesetzlichen Krankenversicherung (GKV) für eine ausgewogenere Verteilung der Einnahmen bei den Kassen sorgen. Ziel ist ein sozialer Ausgleich für unterschiedliche Einkommensstruktur und Krankheitslasten bei den Mitgliedern. Über einen sehr interessanten Nebeneffekt, den dieses regulatorische System ungewollt ausgelöst hat,
Compliance – Where does it fit in a data strategy?
To show how they're compliant with regulatory mandates, organizations first need an enterprise data strategy. Joyce Norris-Montanari discusses the issues.
Point/Counterpoint: Should a programming language accept misspelled keywords?
Longtime SAS programmers know that the SAS DATA step and SAS procedures are very tolerant of typographical errors. You can misspell most keywords and SAS will "guess" what you mean. For example, if you mistype "PROC" as "PRC," SAS will run the program but write a warning to the log:
Why quality is the answer to manufacturing challenges
Manufacturers are used to operating in challenging circumstances – whether financial, economic, political or competitive. And it's a good thing since the coming years seem likely to be as uncertain as those following the global economic crash. But manufacturing will have an excellent opportunity to thrive because, like many sectors,
2 Easy Steps to Write a Great Book Outline
Editor's note: This series of blogs addresses the questions we are most frequently asked at SAS Press! It worth spending some time on this. Arguably, this is one of the most important parts of the book. The table of contents and outline provide the blue print of your book –
12 machine learning articles to catch you up on the latest trend
Machine learning is a type of artificial intelligence that uses algorithms to iteratively learn from data and finds hidden insights in data without being explicitly programmed where to look or how to find the answer. Here at SAS, we hear questions every day about machine learning: what it is, how it compares to
Self-Service: Erst mal anfangen, dann klappt’s auch mit der Datenqualität!
Das Konzept von Self-Service Analytics wird oft mit innovativen Geschäftsmodellen oder schneller Reaktion auf Kundenanfragen assoziiert. Darüber hinaus kann Self-Service aber auch Mitarbeiter in die Lage versetzen, operative Vorgänge besser und effektiver zu unterstützen. Mit Carsten Krah, Business Expert Risk, Fraud & Compliance bei SAS, habe ich mich darüber unterhalten,
Data privacy and governance: No easy answers
.@philsimon advises to be wary of those promising obvious and facile solutions to increasingly challenging governance and privacy issues.
DSGVO: Digitalisierungs-Killer oder Wettbewerbsvorteil?
Laut einer Dell-Studie zum Status der Umsetzung der neuen EU-Datenschutzgrundverordnung (DSGVO) haben erst 3 Prozent der befragten Unternehmen einen Umsetzungsplan. Ich hatte in den letzten zwei Wochen auf den SAS Veranstaltungen zur DSGVO unter dem Titel „Abwarten kann teuer werden" die Gelegenheit, mir hierzu von knapp 100 Teilnehmern selbst einen
How to add roads to your SAS maps
Have you been using the SAS/Graph Gmap procedure to plot your data on maps for years, but never knew you could add roads to your maps?!? Follow along in this blog post, and I'll teach you how... But before we get started, here's a picture of a nice aerial view
Managing information policy compliance to prevent fraud
Health care fraud prevention is a sticky topic. David Loshin discusses what's needed to balance prompt claims payments with fraud prevention efforts.
SAS Graphics Accelerator makes charts and graphs consumable for blind users
Some would say that it's impossible for blind users to see charts and graphs. Those same people might have once said it was impossible for the visually impaired to see the particles that comprise an atom, or galaxies that are billions of light years away. Innovation would prove them wrong
Quantile estimates and the difference of medians in SAS
Sometimes SAS programmers ask about how to analyze quantiles with SAS. Common questions include: How can I compute 95% confidence intervals for a median in SAS? How can I test whether the medians of two independent samples are significantly different? How can I repeat the previous analyses with other percentiles,
7 Simple Steps from Proposal to Print: Development of a SAS Press Book
Editor's note: This series of blogs addresses the questions we are most frequently asked at SAS Press! In our last post about how to write a good outline, we discussed the importance of developing an outline for your proposed SAS Press book and gave some tips on how to do
The Other 27 SAS Numeric Missing Values
What?!? You mean a period (.) isn't the only SAS numeric missing value? Well, there are 27 others: .A .B, to .Z and ._ (period underscore). Your first question might be: "Why would you need more than one missing value?" One situation where multiple missing values are useful involves survey data. Suppose
A simple framework for getting started with data compliance (Part 1 )
As you work toward data compliance, Dylan Jones says keep it simple – start with the 4F’s: Function, Flow, Form, Foster. Part 1 looks at the first two.
Lachs mit Eiscreme – und wie sieht Ihr Self-Service aus?
Self-Service Business Intelligence (BI) wartet mit einer ganzen Reihe von Vorteilen auf, einer der wichtigsten ist sicherlich Agilität. Doch gerade diese Agilität kommt manchmal der Governance eines Unternehmens in die Quere. Nicht selten passiert es, dass Anwender angesichts des blinkenden schönen Self-Service-Visualisierungstools die vereinbarten Regeln außer Acht lassen. Hier die
The distribution of colors for plain M&M candies
Many introductory courses in probability and statistics encourage students to collect and analyze real data. A popular experiment in categorical data analysis is to give students a bag of M&M® candies and ask them to estimate the proportion of colors in the population from the sample data. In some classes,
Guest blogger Koen Knapen on Kalman Filtering and Kalman Smoothing
While The BFD normally favors a lighter approach, with a focus on forecasting process (the politics and personalities therein), forecasting news, and forecasting gossip, we sometimes have to get serious. In this guest blogger post from Koen Knapen, Principal Consultant at SAS Belgium, Koen takes us into the netherworlds of
Modern investigations: It’s not like the movies
I’ve always loved watching crime series or films – from Homeland and True Detective to Sherlock Holmes. But after years of building software products and solutions designed to help security and law enforcement agencies solve crimes, I've noticed there are several clichés that need to be conquered by technology. No.
Data wrangling - down the rabbit hole, and back again!
Are your friends passing around clever memes (supposedly) featuring something your favorite actor said, or sharing news articles that you think might be "fake news"? If there's even a hint of data analyst in you, then you probably check the actual data, and confirm or disprove the supposed facts yourself. I
What does the requirement for data privacy mean for data scientists, business analysts and IT?
Corporate compliance with an increasing number of industry regulations intended to protect personally identifiable information (PII) has made data privacy a frequent and public discussion. An inherent challenge to data privacy is, as Tamara Dull explained, “data, in and of itself, has no country, respects no law, and travels freely across borders. In the
Simultaneous confidence intervals for multinomial proportions
A categorical response variable can take on k different values. If you have a random sample from a multinomial response, the sample proportions estimate the proportion of each category in the population. This article describes how to construct simultaneous confidence intervals for the proportions as described in the 1997 paper