What a Big-Data Business Model Looks Like - R “Ray” Wang. By R “Ray” Wang | 10:00 AM December 6, 2012 The rise of big data is an exciting — if in some cases scary — development for business. Together with the complementary technology forces of social, mobile, the cloud, and unified communications, big data brings countless new opportunities for learning about customers and their wants and needs. It also brings the potential for disruption, and realignment. Organizations that truly embrace big data can create new opportunities for strategic differentiation in this era of engagement.
Those that don’t fully engage, or that misunderstand the opportunities, can lose out. There are a number of new business models emerging in the big data world. Differentiation creates new experiences. Big data offers opportunities for many more service offerings that will improve customer satisfaction and provide contextual relevance. Brokering augments the value of information. Delivery networks enable the monetization of data. Large-scale Data Mining: MapReduce and Beyond. Data are becoming available in unprecedented volumes. This difference in scale is difference in kind, presenting new opportunities.
Map-reduce has drawn a lot of attention recent years for large-scale data processing and mining. In this tutorial, we introduce Map-reduce and its application and research in data mining. In particular, we want to answer the following questions: •What is Map-reduce and why do we need it for data mining? •What mining applications need Map-reduce? •What are the advantages and limitations using Map-Reduce? 1.MapReduce basic includes MapReduce programming model, system architecture, its OpenSource implementation Hadoop and its extensions such as HBase, Pig, Cascading, Hive. 2.MapReduce algorithms cover MapReduce implementation of standard data mining algorithms such as clustering (K-means), classification (k-NN, naive Bayes), graph mining (page rank).
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Rock Report: Big Data & Healthcare. Guest Contributor October 02, 2012 By Dr. Bonnie Feldman I have always been a curious person with wide interests: dentistry, economics, finance, Wall Street, business development, visual display of information, etc. Last summer, I set out to explore a new arena at the intersection of technology, entertainment, psychology and healthcare: mobile social games for health. Ready to step out into Big Data’s Emerald City, I nervously attended the Strategic Research & Innovation Institute conference. At first, it was hard persuading people to be interviewed, but to my surprise, I quickly became a resource, with company executives asking me about competitors and where to find additional data sets. In the course of more than thirty interviews, we found an emerging ecosystem of companies interested in using Big Data to improve healthcare in six ways: Among this sample of companies, three data usage trends emerged: Big Data in Healthcare Hype and Hope.
Www.manovich.net/DOCS/Manovich_trending_paper.pdf. Economics.sas.upenn.edu/~fdiebold/papers/paper112/Diebold_Big_Data.pdf.
BigData Technologies. Ai.arizona.edu/mis510/other/MISQ BI Special Issue Introduction Chen-Chiang-Storey December 2012.pdf. Data visualization.