The increasing scale and availability of digital data provides an extraordinary resource for informing public policy, scientific discovery, business strategy, and even our personal lives. To get the most out of such data, however, users must be able to make sense of it: to pursue questions, uncover patterns of interest, and identify (and potentially correct) errors. In concert with data-management systems and statistical algorithms, analysis requires contextualized human judgments regarding the domain-specific significance of the clusters, trends, and outliers discovered in data.
Excel Cloud Data Analytics is a Microsoft Excel add-in that enables users to execute a variety of data-centric tasks on Windows Azure through a custom Ribbon in Excel. This add-in can be used to connect to data stored in the Windows Azure cloud and can be extended to connect to a variety of other data sources. It also provides a general framework in which the user can create data-analytics methods and run them in Windows Azure. The current code base supports the execution in Windows Azure via built-in access to Daytona, an iterative MapReduce runtime for Windows Azure. Using Excel Cloud Data Analytics, users can upload data to Windows Azure, select and run registered data-analysis algorithms in the cloud through Windows Azure, monitor the execution of the data analysis, and retrieve results for display or further processing.
Interesting article on Predictive Analytics in Marketing…
“Andrew Pole had just started working as a statistician for Target in 2002, when two colleagues from the marketing department stopped by his desk to ask an odd question: “If we wanted to figure out if a customer is pregnant, even if she didn’t want us to know, can you do that? ”
And what would I get for less than a dime per person? Well he emailed me the 617 fields of demographic, behavioral, consumer, and personal information they would supply. And for your viewing pleasure, I’ve republished the entire list of fields below….
In this article I digested a number of MapReduce patterns and algorithms to give a systematic view of the different techniques that can be found in the web or scientific articles. Several practical case studies are also provided. All descriptions and code snippets use the standard Hadoop’s MapReduce model with Mappers, Reduces, Combiners, Partitioners, and sorting. This framework is depicted in the figure below.
Weave (BETA 1.0) is a new web-based visualization platform designed to enable visualization of any available data by anyone for any purpose. Weave is an application development platform supporting multiple levels of user proficiency – novice to advanced – as well as the ability to integrate, disseminate and visualize data at “nested” levels of geography.
Great set of visualizations tools and overview of each. I was particularly interested in the Java app called Timeflow – I’ve been looking for something like that for a while.
Each tool is described using the following headings:
- What it does
- What’s cool
- Skill Level
- Runs on
- Learn more
Chart with overview of all 22 tools: http://www.computerworld.com/s/article/9214755/Image_gallery_22_free_tools_for_data_visualization_and_analysis