Weekly Big Data Catch-Up

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Big Data News, Events, and Expert Opinion

Excerpts:

With New Tor Connector, Is There Now a Way to Hide from Facebook?

6856181503_8d8e73208b_zFollowing the rise of data breaching and web surfers defending themselves against traffic analysis online, anonymity has because more prevalent than ever. Facebook announced this week that users of the social media can now connect directly to the network via the free anonymity software, Tor. It is first of the Silicon Valley businesses to support the service which claims to protect users by bouncing the communications around a distributed network and prevents people from learning what site they visit. Currently, it is possible to access Facebook through Tor, however the new creation means all data is encrypted and Tor users are not mistaken for hacked accounts. While using a social network completely anonymously could be quite difficult, if used correctly, this set-up could appeal to those who want to hide...
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Mastering Data Management: MDM, SOA, ESB, and Other Three Letter Words

7974661195_21ba006459_zI met with a client last week that was trying to determine what and how to deal with one of the most common and complex problems that organizations both small and large have to deal with – data management.  This oil and gas company had data coming out of its ears – production data, seismic data, HSE data, down-hole sensor data, well log data, financial data… you get the picture.  Each department was its own silo; a vast, sprawling archipelago of data islands completely disconnected from each other. Moving data from one department to another was painful and clunky, much like throwing a bunch of stuff on a boat and hoping whoever receives it finds something useful in the reams and ream of info. I know I just used two...
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The Future of Business Intelligence

The Future of Business IntelligenceOver a year ago, an article written for Dataversity™ on Business Intelligence (BI) stated “at some point in the near future BI analysis will simply be another routine aspect of the job for business professionals looking to maximize the use of what will be viewed as a standard resource.” This prediction was presaged in the context of the increasing assertion of two “diametrically opposed” movements related to Business Intelligence – the prevalence of formal education in this field and the simplification of BI tools that are drastically assisting business users in daily operations. The reality is that the reliance on data is growing exponentially; virtually any application of data requires analytics or BI to extract meaning and subsequent action. What once appeared as two opposing trends that could potentially cancel...
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Modern Business Intelligence Means Intelligence Inside Everything

8470720958_8b42792acc_zBrian Gentile is Sr. Vice President & General Manager of the TIBCO Analytics Product Group within TIBCO Software. Formerly, he was Chairman and Chief Executive Officer of Jaspersoft, which was acquired by TIBCO in April 2014.  Today’s businesses are overrun with data. Yet without the right information, data provides no true business value. Whilst legacy business intelligence (BI) products were created to extract usable intelligence out of mass amounts of data, those BI systems have not kept pace with the modern data centre.  Traditional BI reporting and analytics tools are stand-alone, costly and complex.  However, today’s big data flows through the cloud as well as the network and is largely unstructured.  Data comes in at the speed of the Internet – a speed that is much too fast for old...
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How the Internet of Things Can be Best Explored Using Graph Databases

5280585822_ed883a633a_zEmil Eifrem is CEO of Neo Technology and co-founder of the Neo4j project.  Committed to sustainable open source, he guides Neo along a balanced path between free availability and commercial reliability. Emil is a frequent conference speaker and author on NOSQL databases. In this article, Emil explains how the Internet of Things can be best explored using graph databases.  Morgan Stanley recently predicted there will be 75 billion connected devices in use worldwide by 2020, a number rapidly approaching the estimated 86 billion neurons in the human brain. We know that human intelligence comes not from the sum of neurons in our brains, but from the connections between them and the way they interact with each other. While one could easily take this analogy too far, two points are worth taking away....
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Gridgain’s In-Memory Data Fabric Enters the Apache Software Foundation as Apache Ignite

Gridgain-In-Memory-Data-FabricGridgain announced yesterday that their in-memory data fabric has been accepted into the Apache Software Foundation Incubator programme, under the name Apache Ignite. The Gridgain team hope the move will fuel greater adoption of in-memory computing technologies, and build a greater community around the data fabric. Expanding upon their motives to open-source their signature product, a Gridgain blogpost states: Earlier this year, we took an important step in order to make the transformation to IMC truly accessible by shifting to an open source model through an Apache 2.0 license. Our motivation was simple: remove all barriers to IMC adoption and accelerate the innovation that’s poised to occur through this technology. We wanted to introduce IMC to the mass market in a way that would give developers maximum freedom to experiment...
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Top Tips for Implementing a Big Data Strategy

DubaiAli Rebaie is a Big Data & Analytics industry analyst and consultant of Rebaie Analytics Group. He provides organizations with a vendor-neutral selection of business intelligence & big data technologies and advice on big data and information management strategy and architecture. Ali also appeared in several lists of “Who’s Who in Big Data” and as one of the top big data influencers worldwide. He has led and developed several technology projects in business intelligence and analytics and worked for clients in the Fortune 500. Ali is a member of the internationally renowned Boulder BI Brain Trust (BBBT) in Boulder, USA, a membership-only consortium of leading independent BI and Big Data experts and analysts worldwide. How is big data evolving in the Middle East? Big Data has a long 5000-year history here,...
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LinkedIn’s Veteran Data Science Team Splits Up to Enhance Productivity

6272018820_baab142ab0_zLinkedIn, the social networking company with one of the world’s first pioneering data science teams, has split its crew to be placed under different departments. The data science team which had worked in the product division, had consisted of two branches through the years – the product data science team, responsible for “new data-powered features,” generating new data for analysis, and the decision sciences team, that tracks and monitors product metrics and usage data. VentureBeat reports that the former now comes under engineering while the latter answers to the office of the company’s chief financial officer. Explains the head of LinkedIn’s business operations and analytics team and leader of the former decision sciences team, Laura Dholakia, while speaking to VentureBeat, “It was just really clear that there was just a...
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Which Environment to Choose for Data Science?

scikit-learn-flow-chartSummary: In the past, R seemed like the obvious choice for Data Science projects.  This article highlights some of the issues, such as performance and licensing, and then illustrates why Python with its eco-system of dedicated modules like Scikit-learn, Pandas and others has quickly become the rising star amongst Data Scientists. Data Scientists starting a new project have a cornucopia of options to choose from to develop and implement their models. A popular choice is the R project for Statistical Computing, an open source implementation of the S environment originally developed by the Bell Laboratories. R (and S) is designed as a software environment for working with data, including statistical computations and graphics. R is used in a wide range of use-cases and is supported by a large community to...
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