analytics

1月 182017
 

Improving citizen happiness is an important goal for many, if not all, governments.  But what is happiness really?  Can it be objectively measured?  Can we discover the key factors that best correlate with happiness?  And ultimately, can governments implement policies and programs that maximize happiness? Is maximum happiness nothing more than […]

Can you measure and optimize happiness? was published on SAS Voices.

1月 172017
 

After reading a recent LinkedIn post by Jeff Haden, "Want to Achieve Lifelong Success? An Army Ranger Says You Need This 1 Trait the Most", (spoiler alert: It's adaptability) something occurred to me. One of the reasons I enjoy solving business problems with analytics is that analytics is all about […]

4 adaptability attributes for analytical success was published on SAS Voices.

1月 172017
 

For many years, the Toyota Prius was the hybrid with the best mpg - but in 2017 that's changing! Let's examine the data ... For analyses like this, I have found the fueleconomy.gov website to be a wonderful source of information. In recent years, they've even made all their data […]

The post Prius isn't the highest-mpg hybrid in 2017! appeared first on SAS Learning Post.

1月 132017
 

They say "a picture is worth 1000 words" - and I think it might be more like 2000 when it comes to planning out fun/interesting things to do in  a new city! I'm going to the SAS Global Forum (#SASGF) conference in Orlando this year, and I was wondering where […]

The post What to do in Orlando, during SAS Global Forum! appeared first on SAS Learning Post.

1月 132017
 

A number of posts on SAS Voices have touched upon the theme of modernization. This is certainly a hot topic with our customers as many of them continue to be interested in taking advantage of the evolving software landscape. The thing is, modernization can be hard. I should know, I’ve been […]

Lessons learned from customer modernization projects was published on SAS Voices.

1月 122017
 

analytics resolutionsThe holiday season is over – and you survived. You’ve made a lot of personal resolutions for 2017 - go to the gym, eat less sugar, save more money, visit Grandma more often. These are all great personal resolutions for 2017, but what about your analytics resolutions? If you are having trouble with your analytics resolutions then let us help you out. The recent release of SAS 9.4 M4 will help you make 2017 your best analytics year yet.

Resolution 1: Build more accurate models faster!

Now you will be able to leverage the power of the two most advanced analytics platforms on the market, SAS 9 and SAS Viya from one interface. Using SAS/Connect, users can call powerful SAS Viya analytics from within a process flow in Enterprise Miner. Would you prefer to use the super-fast, autotuned gradient boosting in SAS Viya? No problem! Call SAS Viya analytics directly from Enterprise Miner using the SAS Viya Code node. Then, from the same process flow you can also call open source models, all from one interface, SAS Enterprise Miner. Do you prefer to use SAS Studio on SAS 9? You will also be able to call SAS Viya analytics from SAS Studio as well. With SAS 9 M4, SAS gives you the ability to use both of SAS’ powerful platforms from one interface.

Resolution 2: Score your unstructured models in Hadoop without moving your data!

Got Hadoop? Got a lot of unstructured data? Now SAS Contextual Analysis allows you to score models in Hadoop using the SAS Code Accelerator add-on. Identify new insights with your unstructured text without ever having to move your data. Score it all in Hadoop. Uncover new trends and topics buried in documents, emails, social media and other unstructured text that is stored in Hadoop. You will be able to do it faster because you won’t have to move that data outside of Hadoop. SAS just keeps getting better in 2017.

Resolution 3: Make better forecasts using the weather!

Through SAS/ETS, econometricians and others wanting to incorporate weather data into their models can now do so directly through two new interface engines. SASERAIN enables SAS users to retrieve weather data from the World Weather Online website. And SASENOAA provides access to severe weather data from the National Oceanic and Atmospheric Administration (NOAA) Severe Weather Data Inventory (SWDI) web service. So now you’ll know why there was that big sales spike for rock salt and snow shovels in July! Who says there is no climate change in 2017?

Resolution 4: Estimate causal effects more efficiently!

The new CAUSALTRT procedure in SAS/STAT estimates the average causal effect of a binary treatment variable T on a continuous or discrete outcome Y. Depending on the application, the variable T can represent an intervention (such as smoking cessation – which is a great 2017 resolution - versus control), an exposure to a condition (such as attending private versus public schools), or an existing characteristic of subjects (such as high versus low socioeconomic status). The CAUSALTRT procedure estimates two types of causal effects: the average treatment effect and the average treatment effect for the treated. And best of all, the causal inference methods that the CAUSALTRT procedure implements are designed primarily for use with data from nonrandomized trials or observational studies, where you observe T and Y without assigning subjects randomly to the treatment conditions.

Resolution 5: Design better factory floors!

A factory floor can be a complicated place, with raw materials coming in one side, and finished products going out the other. Options are virtually unlimited for the placement of materials and equipment – and a poorly designed layout can dramatically reduce production capability. Yet experimenting with different layouts would be extremely costly and time consuming. Thankfully, SAS Simulation Studio (a component of SAS/OR) provides a rich – and animated – environment for testing alternatives and coming up with the most appropriate design. And it can handle any kind of discrete-event simulation, integrating with JMP for experimental design and input analysis, and with JMP and SAS for source data and analysis of simulation results. How will your factory floor simulation impact your productivity in 2017?

tags: analytics, SAS 9.4, SAS Viya

Five great analytics resolutions for 2017 was published on SAS Users.

1月 092017
 

I've long been fascinated by both science and the natural world around us, inspired by the amazing Sir David Attenborough with his ever-engaging documentaries and boundless enthusiasm for nature, and also by the late, great Carl Sagan and his ground-breaking documentary series, COSMOS. The relationships between the creatures, plants and […]

Intelligent ecosystems and the intelligence of things was published on SAS Voices.

1月 062017
 

Much of my recent work has been along the theme of modernization. Analytics is not new for many of our customers, but standing still in this market is akin to falling behind. In order to continue to innovative and remain competitive, organizations need to be prepared to embrace new technologies […]

The seven traits of a modern analytical platform was published on SAS Voices.

1月 042017
 

If you do much traveling in the United States, you're bound to hear a few words and expressions that are unique to certain areas. Well y'all get ready, because I'm fixin' to analyze some of those words for ya! I recently found a really neat web application called The Great […]

The post American English: Where to use 'yall' versus 'yinz' appeared first on SAS Learning Post.

1月 042017
 

If you do much traveling in the United States, you're bound to hear a few words and expressions that are unique to certain areas. Well y'all get ready, because I'm fixin' to analyze some of those words for ya! I recently found a really neat web application called The Great […]

The post American English: Where to use 'yall' versus 'yinz' appeared first on SAS Learning Post.