Big Data

https://dzone.com/articles/drill-data-with-apache-drill-part-2
https://dzone.com/articles/big-data-ingestion-flume-kafka-and-nifi
https://dzone.com/storage/assets/5046285-dzone-guidetobigdata-voliv.pdf
https://dzone.com/articles/monitoring-real-time-uber-data-using-apache-apis-p-1
https://dzone.com/articles/deep-learning-and-and-gpu-acceleration-in-hadoop-3
http://www.7wdata.be/data-analysis/mid-year-updates-for-big-data-trends-apache-kafka-spark-flink-drill-and-more/
https://techcrunch.com/2012/07/18/twitter-storm-nodeable-pivot/
https://www.linkedin.com/pulse/big-data-moving-forward-make-fast-bo-yang
https://www.mapr.com/products/apache-drill
http://www.ere.net/2014/10/17/some-quick-thoughts-on-big-data-and-metrics/
http://strataconf.com/stratany2013
https://www.linkedin.com/today/post/article/20130708153702-13561499-the-ethical-profitable-big-data-vendor
http://pro.gigaom.com/2012/03/big-data-beyond-analytics/
http://pro.gigaom.com/2012/04/infrastructure-q1-cloud-and-big-data-woo-the-enterprise/
http://www.fastcompany.com/1843267/pew-internet-big-data
http://gigaom.com/2012/08/06/facebooks-ad-product-guru-to-advise-ny-big-data-startup-sociocast
http://gigaom.com/2012/08/06/leveraging-big-data-to-extract-value-from-social-media/
http://gigaom.com/2012/08/20/making-big-data-analytics-pay/
http://gigaom.com/cloud/big-data-as-a-tool-for-detecting-and-punishing-bullies
http://gigaom.com/cloud/big-data-magic-trick-show-me-a-doorway-ill-tell-you-the-city/
http://gigaom.com/cloud/infochimps-makes-its-big-data-for-developers-platform-real-time
http://gigaom.com/europe/mendeley-injects-some-pace-into-academia-with-fast-big-data
https://docs.google.com/presentation/d/176sjVE_f_bGCkX2cSlxeeTiPaMVcDVsI8vIxn5G9UIU/view#slide=id.p18
http://gigaom.com/cloud/amazons-new-data-warehousing-service-takes-aim-at-old-guard-it-giants/
http://gigaom.com/cloud/for-data-warehousing-startups-amazon-is-both-friend-and-rival/
http://www.fastcompany.com/3003490/amazon-takes-data-management-lions-cloud-computing-service-redshift
http://gigaom.com/cloud/amazon-preps-data-pipeline-service-to-automate-and-orchstrate-big-data-workflows/
http://www.fastcoexist.com/1680949/if-data-is-the-new-oil-we-should-be-wary-of-it
https://dzone.com/articles/creating-wordclouds-from-dataflows-with-apache-nif
https://gigaom.com/2011/07/12/zettaset-raises-3m-for-the-consumerization-of-big-data/ - done reading

http://www.youtube.com/watch?v=viPRny0nq3o
http://www.youtube.com/watch?v=0ZNGOJjuAKg&list=PLGv3QgWrkbRmdhMHXVswl6mHqaY1wDCLR
http://www.youtube.com/watch?v=3twBv2v4Ip0
http://www.youtube.com/watch?v=S9xnYBVqLws
http://www.youtube.com/watch?v=367KWPASWtE
http://www.youtube.com/watch?v=duHxpSTmwW0
http://www.youtube.com/watch?v=yHAf-AR704o
http://www.youtube.com/watch?v=_eWDR3P8Lhw
http://www.youtube.com/watch?v=7FcMhTTG1Cs
http://www.youtube.com/watch?v=DI9JiG-Ow9g
http://www.youtube.com/watch?v=7D1CQ_LOizA
http://www.youtube.com/watch?v=HHv2pkIJjR0
http://www.youtube.com/watch?v=jKBwGlYb13w

GOTO Metrics, a two-year-old company (in 2011), renamed itself as Zettaset, raised 3 million dollars, and re-launched. They raise this money from Draper Fisher Jurvetson and EPIC Ventures to help employees make business decisions on real data as opposed to intuition. It still offers a software toolset that runs on top of a group of servers and unifies the existing databases so someone can mine them for insights. It’s those insights that will end up adding value to technology companies.”It’s not just about the technology anymore; it’s about the data and if you can produce more granular insights from your data. https://gigaom.com/2011/07/12/zettaset-raises-3m-for-the-consumerization-of-big-data/

Zettaset, whose name is an attempt to reflect the growing amount of data available — a zettabyte consists of more than a million petabytes — helps make implementing Hadoop on top of existing databases easier and also offers an user-friendly graphical user interface so people can then play around with the data. They can also export it to more familiar programs such as Excel spreadsheets.

Executives want to know what is being said about their companies or products on Twitter, Facebook, and other social media web sites. They should pay a company who already have connection with these social media companies (already have access to those data hoses) to analyze this data, or they should use SurveyMonkey. Is there a way for the company to push out a message, a survey to these social pages (web sites) or to the individual person? Reputation Defender, and there are other companies that focus on mining and analyzing data that are produced by government agencies on consumer behavior and habits. What about data that come from inside the company (such as product / equipment usage)?

How can we make big data analytics available to smaller companies who might not even have capability to collect intelligence data? Analyze their operations. Offer custom solution (if necessary) to help them collect the data. Have tools that are easy to use so that a BA (Business Analyst) can analyze the data. In effect, they rent the Hadoop guy and a BA from us.

The bigger opportunity isn’t in enabling this shift; it’s in what the shift can do for businesses and society. For example, making data available for the average Joe helped boost Mint.com and is enabling consumer-facing startups such as energy consumption startup OPower to offer amazing insights really quickly. These insights can help change behaviors. https://gigaom.com/2011/07/12/zettaset-raises-3m-for-the-consumerization-of-big-data/

In the government arena, opening up data has the power to make government entities more accountable or even deliver results and insights that government can’t. There are also stories such as this one from the New Yorker, about a doctor in New Jersey that crunched data and then built a pilot program that reduced medical costs for the most-expensive patients in the city by more than 50 percent. It made people healthier too.

Better analytics of bigger data should enable more people to make the leap from intuition to insight — or even see an insight without ever having the intuition that drives them to look for data to back it up. It’s the difference between looking for treasure using a map of pirate sea routes and historical storm data and looking for treasure by trying to think like a pirate.

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