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The reactions to a big data breach often resemble the five stages of grief, so a little empathy is needed.

APT Trends report Q2 2017

Since 2014, Kaspersky Labrsquo;s Global Research and Analysis Team (GReAT) has been providing threat intelligence reports to a wide-range of customers worldwide, leading to the delivery of a full and dedicated private reporting service. Prior to the new service offering, GReAT published research online for the general public in an effort to help combat the ever-increasing threat from nation-state and other advanced actors.
Big data and analytics initiatives can be game-changing, giving you insights to help blow past the competition, generate new revenue sources, and better serve customers.To read this article in full or to leave a comment, please click here(Insider Story)
A new report has said emerging technologies offer improved capabilities for collecting, collating, and analysing big data, but warns against getting carried away with the hype and potential benefits of using 'big data' to fight crime or terrorism.
Roshan Kumar is senior product manager at Redis Labs.Real-time streaming data ingest is a common requirement for many big data use cases.
In fields like IoT, e-commerce, security, communications, entertainment, finance, and retail, where so much depends on timely and accurate data-driven decision making, real-time data collection and analysis are in fact core to the business.However, collecting, storing and processing streaming data in large volumes and at high velocity presents architectural challenges.

An important first step in delivering real-time data analysis is ensuring that adequate network, compute, storage, and memory resources are available to capture fast data streams.

But a companyrsquo;s software stack must match the performance of its physical infrastructure. Otherwise, businesses will face a massive backlog of data, or worse, missing or incomplete data.To read this article in full or to leave a comment, please click here
An algorithm is using government data to tell those from low socioeconomic backgrounds their likelihood of completing university, but privacy experts say it could be utilised for early intervention instead of discouragement.
Convenience alone makes containers ideal for development.

After all, as this CIO article points out, “a container consists of an entire runtime environment: an application, plus all its dependencies, libraries and other binaries, and configuration files needed to run it, bundled into one package.

By containerizing the application platform and its dependencies, differences in OS distributions and underlying infrastructure are abstracted away.”However, when properly utilized, containers have value that extends well beyond application development to support production workloads.

A modern hyperconverged environment can empower organizations to run next-gen apps that process big data and need highly efficient, high performance computing capabilities.To read this article in full or to leave a comment, please click here
As defined by the World Economic Forum (WEF), “Blockchain technology allows parties to transfer assets to each other in a secure way without intermediaries.
It enables transparency, immutable records, and autonomous execution of business rules.”Investments in the blockchain are on the rise.

Banks, private businesses, and even governments are investing in the technology.

The WEF predicts that smart contracts alone on the blockchain could equal 10 percent of the global GDP by 2027.

As with any new technology, itrsquo;s important to note the value of the data that comes with it.

And arguably the most valuable data involved with blockchain technology is that of virtual currency use.To read this article in full or to leave a comment, please click here
Dating from 1991, Python is a relatively new programming language.

From the start, Python was considered a gap-filler, a way to write scripts that “automate the boring stuffrdquo; (as one popular book on learning Python put it) or to rapidly prototype applications that will be implemented in one or more other languages.However, over the past few years, Python has emerged as a first-class citizen in modern software development, infrastructure management, and data analysis.
It  is no longer a back-room utility language, but a major force in web application development and systems management and a key driver behind the explosion in big data analytics and machine intelligence.To read this article in full or to leave a comment, please click here
Software Defined Visualization (SDVis) has become a mainstream idea: visualization on processors (CPUs) has enormous advantages in flexibility, cost, and performance for large visualizations. While that sounds like a great marketing pitch for Intel, the facts actually check out on this for a number of reasons, including trends in memory and algorithms.These advantages are overwhelming for truly big data (referred to as “exascalerdquo; data).  In the paper “An Image-based Approach to Extreme Scalenbsp;In Situ Visualization and Analysis,” the data movement challenge is quantified as being 1,000,000,000X as much data for extreme scale simulation data (where CPUs win) vs. that of image processing (where GPUs have dominated).To read this article in full or to leave a comment, please click here
But the next big thing will be machine learning and AI for simulations and design.
JAKARTA, Indonesia: The explosive growth of the Internet of Things (IoT), the role of satellite connectivity and the evolution of 4G, 5G and LTE technologies will be some of the key talking points discussed by leading industry names at this yearrsquo;s Communic Indonesia.In 2016, the number of internet users in Indonesia hit 100 million, with 93% accessing the web via their mobile phones.

As the Government aims to have broadband reach 71% of the total... Source: RealWire