Now that Google has rendered Hadoop passé by putting forth its Cloud Dataflow service, data analysis “experts” will have to work harder
Source: www.businessweek.com
Archives
All posts for the month June, 2014
Roundtable Discussion
Key points
Getting the right people together with the right technology poses a major challenge.Collaboration among those with different skillsets is crucial—alignment around clear goals can incent this collaboration.Executive sponsorship is essential.Because they were born from data, Internet businesses have a built-in advantage when it comes to employing it.Big data and analytics will continue to evolve, but they are here to stay.
Source: www.atkearney.com
The SIGFOX connected world, a fast growing ecosystem connecting the world through the SIGFOX cellular connectivity for the IoT and M2M….
It is impossible to imagine the deployment of billions of connected devices if communication costs remain high, and with such volumes every square inch of silicon counts. The SIGFOX protocol is compatible with the majority of existing transceivers, making it easily accessible for module and device manufacturers.
Welcome to the SIGFOX Connected World.
Source: www.sigfox.com
Failure to take privacy seriously can put you at risk of fines or litigation, but the worse case scenario involves negative publicity equating your company with a lack of concern over personal information (e.g. Target and Neiman Marcus). The Google ECJ case is an opportunity to strengthen relationships between clients and consumers by reconsidering how their data is managed. The winners of the digital age will be those who see privacy as an investment that secures profits and opens up privacy markets across the globe.
Source: blogs.hbr.org
Facebook has built its own networking switch and developed a Linux-based operating systems to run it. The goal is to create networking infrastructure that mimics a server in terms of how its managed and configured.
Source: gigaom.com
See on Scoop.it – Corporate Challenge of Big Data
“eRegulations Insights builds on the success of organizations such as the Sunlight Foundation to free open data, promote public participation and help agencies uncover constructive feedback on specific issues,” said Stephen Sorkin, chief strategy officer, Splunk. “As governments grapple with how best to enhance citizen participation and improve transparency, providing similar access to other open data sets could have a transformative impact on government at all levels. Regulators and citizens alike can empower themselves with data-driven debate, and we hope eRegulations Insights can help show just how powerful a little more transparency can really be.”
See on www.splunk.com
See on Scoop.it – Corporate Challenge of Big Data
Founded just two-and-a-half years ago, Qubole now has more than 30 customers running on Hadoop nodes that it manages, including prominent Web-based outfits like Pintrest and Quora, and a handful of online advertising specialists. Qubole, which maintains dual headquarters in Silicon Valley and Bangalore, runs its clusters on AWS and Google Cloud, and exposes a high-level Web interface for users to query their Hadoop clusters via Hive, Pig, Presto, and MapReduce.
See on www.datanami.com
See on Scoop.it – Corporate Challenge of Big Data
Big data is no longer the sole domain of big companies. As the perception of big data moves from futuristic hype to real-world opportunity, the promise of improved decision making, increased operational efficiency and new revenue streams has more organizations actively engaging in data analysis projects than ever before. That no longer just means more enterprise organizations, either. Midmarket companies are jumping on the big data bandwagon in a big way. In fact, a recent survey by Competitive Topic: Big Data.
See on www.cmswire.com
See on Scoop.it – Corporate Challenge of Big Data
The on-going Big Data media hype stirs up a lot of passionate voices. There are naysayers (“it is nothing new“), doomsayers (“it will disrupt everything”), and soothsayers (e.g., Predictive Analytics experts). The naysayers are most bothersome, in my humble opinion. (Note: I am not talking about skeptics, whom we definitely and desperately need during any period of maximized hype!)
See on dataconomy.com
See on Scoop.it – Corporate Challenge of Big Data
[The] objective (to use deep learning to wrestle the practically-unknowables down to knowables) seems to be the impetus behind a two-year-old US DoD Advanced Research Projects Agency initiative called Deep Exploration and Filtering of Text (DEFT)… DEFT aims to “analyze textual data at a scale beyond what humans could do by themselves….[DEFT is designed to enable] more efficient…processing [of] text information and…[greater] understanding [of] connections in text that might not be readily apparent to humans….[D]efense analysts [would be able] to efficiently investigate…more documents, which would enable discovery of implicitly expressed, actionable information within those documents.”
DARPA’s ability to deliver on this grand promise is still unproven. However, the range of deep-learning ML approaches included under DEFT is truly impressive. A partial list includes separate functional modules to detect anomalies, disfluency, ambiguity, vagueness, causal relations, person-relations, semantic equivalences, entailments and redundancies in textual corpora.
See on www.ibmbigdatahub.com
