Search Results: Visual Analytics (1639)

Alison Bolen 0
Technologies for the future: yes or no

When I started college 25 years ago, we didn’t use email. I moved into the dorms my freshman year with a Brother Word Processor, convinced I would never have a single computing need beyond the necessity to type, save and print text. It’s incredible to consider how wrong I was.

John Farrelly 0
Why we’re creating 150 new jobs in Ireland

In today’s information economy, the ability to engage and develop meaningful digital relationships is fundamental to any business. A growing number of organisations, including small-to-medium sized enterprises, are investing in easy-to-use analytical software and services to extract insights from data about their business. As a result, we're now experiencing the

SAS Events
Maggie Miller 0
Jumpstart your data science career

The data science profession has been called the sexiest job of the 21st century. It’s also landed on the list of the 25 highest-paying jobs with the most openings right now. There’s a wealth of knowledge on the web describing “what is” a data scientist, but there are far fewer

Brooke Fortson 0
Meet your SAS #StrataHadoop Team: Patrick Hall

The epicenter of big data moves to New York City on September 29 at Strata + Hadoop World. It’s a great chance to mix and mingle with people that live and breathe analytics, including a core SAS team of thought leaders, developers and executives. We’d love to be a part

Andrew Pease 0
Enter the data composer

Along with the data scientist hype, analytics and the people who make them work have found themselves in the spotlight. The trend has also put an emphasis on the "science" aspects of analysis, such as a data focus, statistical rigor, controlled experiments and the like. Now, I’m not at all against adding more

Leo Sadovy 0
Big Model: The necessary complement to big data

With all the hype over big data we often overlook the importance of modeling as its necessary counterpart. There are two independent limiting factors when it comes to decision support: the quality of the data, and the quality of the model. Most of the big data hype assumes that the data

Customer Intelligence
Jonathan Moran 0
Getting to the segment of one

As mass marketing becomes less common and effective, we get closer and closer to the ideal of the “segmentation of one,” which involves high degrees of personalization. In that environment, businesses must be able to market to customers at an individual level to remain competitive and relevant. However, without customer analytics technologies --

Analytics | Data Visualization
Leo Sadovy 0
Why build models?

We are all modelers.  Whenever you plan, you are building a model.  Whenever you imagine, you are building a model. When you create, write, paint or speak, you first build in your head a model of what you want to accomplish, and then fill in the details with words, movements

Analytics
Russ Cobb 0
Surfing big waves

I just spent much of the past week watching and trying to ride waves on the North Carolina coast. Small waves, mind you, nothing spectacular and certainly nothing that you would consider edgy or life-altering. Nothing that big wave surfers like Laird Hamilton, Garrett McNamara and others of their substance

Andreas Gödde 0
Big data use cases and the big data wake up call

According to recent studies on big data readiness, the majority of companies (more than 60 percent in the latest study of Crisp Research) are not prepared for the challenges of digital transformation. In fact, 58 percent of decision makers surveyed say they have no strategy in place. The quest for

David Froning 0
5 proven ways to improve field quality performance

Your customers are more demanding than ever before.  Improving field quality and your customer's experience of your product is essential to staying competitive.  However, truly understanding customer experience can be a daunting task.  These recommendations have been refined and proven in dozens of manufacturers as simple ways to rapidly improve field quality performance. 1. Think big; start small.

Andreas Becks 0
Big Data Strategie erfolgreich entwickeln

Das Big Data Lab von SAS - Big Data Strategie 1995 - World Wide Web. Erinnern Sie sich, wie komplex und kompliziert es für ein Unternehmen war, eine eigene Website aufzubauen, Anwendungen zu definieren, diese redaktionell zu betreuen und die nötige Infrastruktur zu betreiben – heute unvorstellbar! Und sogar das Surfen

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