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From the Founder and CEO, Cloudscale Inc.

Bill McColl

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Top Stories by Bill McColl

Cloud Data Analytics on Ulitzer Cloud analytics is hot. Gartner's top two strategic technologies for the enterprise in 2010 are cloud computing and advanced analytics. In their words "Technologies you can't afford to ignore". Venture capitalist Ann Winblad, in a recent video, points out that the coming era of realtime cloud analytics will have a revolutionary impact on the enterprise, creating a radically new "innovation palette" for businesses of all kinds. Business analytics is, of course, a major established sector of the IT industry, but it's one that's ripe for disruption. Twenty years of SQL/OLAP analytics have created a $25 Billion market, but the impact of SQL/OLAP analytics on the enterprise has been far less impressive than many had hoped. Only a relatively small fraction (5%-10%) of those grappling with information overload from explosively growing enterpr... (more)

Cloud Analytics Checklist

Cloud Data Analytics on Ulitzer In the previous article we looked at how realtime cloud analytics looks set to disrupt the $25B SQL/OLAP sector of the IT industry. What are users looking for from a next-generation post-SQL/OLAP enterprise analytics solution? Let's look at the requirements: Realtime + Historical Data. In addition to analyzing (historical) data held in databases (Oracle, SQLServer, DB2, MySQL) or datastores (Hadoop, Amazon Elastic MapReduce), a next-gen analytics solution needs to be able to analyze, filter and transform live data streams in realtime, with low la... (more)

The Client-plus-Cloud Revolution

Data is growing exponentially everywhere - in business, web, finance, government, science, and in the world of sensors and smart grids. Speaking earlier this week at OSBC, Tim O'Reilly said  "The future will be all about who has most data, and who is able to extract meaning from it and deliver it in real time".  He noted that the IT industry is now in the process of being reinvented around the idea of realtime analysis of "Big Data" in the cloud, as a must-have adjunct to the much more limited kinds of data processing and analytics that can be performed on desktop PCs or mobile d... (more)

Cloud Supercomputing: Navigating The "Big Data" Space

Databases, Data Warehouses, Map Reduce, Hadoop, Realtime Data Warehouses,... What is the right technology for your "big data" analytics challenges? The best fit will depend on your specific requirements on three fronts: Speed (How long can you afford to wait for the results of your big data processing? Is latency of several hours acceptable, or do you need analytics insight at the speed of your business transactions and events, i.e. in seconds?) Scale (How much data are you gathering? How much do you need to process per second, per minute,  or per hour?) Power (How complex do your... (more)

Google Dumps MapReduce

Over the past five years, MapReduce and Hadoop have been widely used for processing big data from the web, both in-house and in the cloud. However, we are now in an era where news, search, marketing, commerce and many other key aspects of the web are becoming much more social, more mobile, and more realtime. In response to these changes, major web companies are realizing that the "big data analytics" that is driving many of their services needs to be radically changed in order to move it into this realtime era. No company sees this more clearly than Google, the company that origi... (more)