This may be controversial coming from someone that has worked with data his entire career, someone that has been involved with software vendors focused on data integration and access for the last 6 years, and someone that is responsible for product marketing for SAS data management capability, but I’ll say
Various research efforts and customer conversations clearly indicate that the data exploration and data preparation stage of the analytic lifecycle is complex and time consuming. Scarce data scientist or data analyst resources are spending the majority of their time on data preparation tasks vs. spending their time on deriving insight
It’s hard to believe, but now that 2011 is almost over it’s time to look ahead. The technology pundits are starting to publish their 2012 predictions, and it’s not surprising to see topics like analytics, cloud, big data, mobile, social networking, virtualization, open source on these lists. Instead of creating
Lately, in consulting with customers about SAS solutions, I’m increasingly seeing discussions revolve around 3 inter-related but distinct segments: Information Management, Analytics, and Campaign Optimization. In the past, these discussions might have happened with 3 different audiences in 3 different meetings, but we are seeing a massive convergence across these
I’ve had many recent opportunities to discuss the role of IT and business based on recent research efforts, focus group conversations, customer visits and advisory board discussions. Some of the feedback is really striking and sadly comical – “They don’t get it, they don’t understand analytics” – I heard the
Big hype about big data has played a significant role in driving awareness about the value of analytics. SAS welcomes the interest in big data, since it highlights our ability to work with huge volumes of complex and diverse data. Since this is such a critical topic, we have formulated
I recently attended Gartner’s IT Symposium, Gartner’s premier IT event. Since I’m not a fantasy city fan – sorry Disney, I mean Orlando, or was I in Las Vegas? - I was heavily motivated to attend the conference sessions. Although one can hardly scratch the surface of the content that
Ask any data warehouse architect what is driving the “big data” craze and he’ll tell you it has to do with the cost of storage and the advancements in distributed computing and most likely will mention Hadoop. Most enterprise data warehouses are constrained by cost and scalability of relational databases.
By now we have all heard how Yahoo uses Hadoop to optimize the user experience by ad and content targeting. We know that Hadoop is well suited for analysis or processing that can be distributed in a parallel fashion on multiple nodes. We know it’s great for managing big data.
Volume, Variety, Velocity – how many times have you heard that lately? The “3 V’s” are commonly used to describe big data by various vendors and analysts. Forrester extends this by introducing “Variability” as a 4th V – this addresses the fact that you need to design for agility due
