According to a market research report, Global Hadoop market – industry analysis, share, size, growth, trends and forecast, which was once estimated at a value worth USD 1.5 billion in 2012, is now expected to hit $13.95 Billion mark this year, 2017 with a CAGR of 54.9%.
The advent of Hadoop platform stemmed out from the growing urge to manage problems that resulted owing to a lot of data – mostly a concoction of structured and unstructured data – that failed to fit properly in the traditional data storage and management systems, like tables. The play of analytics got intense, more complicated – both computationally and logically – hence the need for Hadoop is more than ever. This is similar to what Google was doing while it was on an endeavor to examine its user behaviors and index web pages, with a view to enhance its own performance algorithms.
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The term Big Data stands for data that is humongous. Large volumes of data are being churned out every day to meet business needs.
Business analytics is the bedrock of an organization. It uses data for proper analysis of business objectives, later on which helps in making better decisions and future profit generation. Also, it aids in determining the actual reasons of failures, re-evaluating risk portfolios, and detecting undergoing fraudulent activities before they swell up to affect business operations.
Continue reading “How to Secure Big data While Harnessing Its Big Power”
Big data is a very powerful term nowadays. It seems to be a large amount of data. Big data means large amount of structured, unstructured, semi-structured data. We get data continuously from various data sources.
Just have a look on how we get data.
Nowadays we are living in a techno era in which we need to use technology so that’s why we are generating data. If you are doing any type of activity like – driving car, having some shakes in CCD, surfing internet, playing games, emails, social media, electronic media, everything plays a crucial role to develop big data. Continue reading “Revising the Basics of Big Data Hadoop”
Of late, Microsoft- the tech mogul, like Google and IBM has deciphered massive potentials in launching quantum computing to eradicate the world’s biggest problems. Researchers at IBM, Intel and others are on an amazing scientific rat race to develop a commercially viable super quantum computer. Though they exist in laboratories, bringing it into the real world is going to be an altogether different endeavor.
Understanding the concept of the quantum computer
The concept of quantum computer is somewhat different and is not based on the use of binary logic. According to its nature, a quantum computer is a simple yes/no/both device – where a programmer doesn’t have to choose between options, he is free to make all the choices in the world and that makes all the difference in the world.
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It’s time to move beyond Artificial Intelligence frameworks. Recently, a joined effort from the Digital giants Microsoft and Facebook has paved the pathway for developers to move beyond traditional AI frameworks. The Open Neural Network Exchange (ONNX) format announced the other day that Facebook and Microsoft are on a lookout to boost AI interoperability and innovation. This piece of information was published in their own blog posts, and from there it got viral.
In Facebook’s blog post, the Social Media behemoth clearly defined its new effort is “toward an open ecosystem where AI developers can easily move between state-of-the-art tools and choose the combination that is best for them.”
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Hadoop is being increasingly used by companies of diverse scope and size and they are realizing that running Hadoop optimally is a tough call. As a matter of fact it is not humanly possible to respond to the changing conditions in real time as these may take place across several nodes in order to fix dips in performance or those that are causing bottlenecks. This performance degradation is exactly what needsto be critically remedied in cases where Hadoop is deployed on large scales where Hadoop is expected to deliver results critical to your business in the proper time. The following three signs signal the health of your Hadoop cluster.
The Out of Capacity Problem
The true test of your Hadoop infrastructure comes to fore when you are able to efficiently run all of your jobs and complete them within adequate time. In this it is not rare to come across instances where you have seemingly run out of capacity as you are unable to run additional application. However monitoring tools indicate that are not making full use of processing capability or other resources. The primary challenge that now lies before you is to sort out the root cause of the problem you have. Most often you will find them to be related to the YARN architecture that is used by Hadoop.YARN is static in nature and after the scheduling of jobs the process of adjusting system and network resources. The solution lies in configuring YARN to deal with worst case scenarios.
Continue reading “Things To Be Aware Of Regarding Hadoop Clusters”
I hope this post will help you to answer some questions related to Apache spark that might be coming into your mind these days related to Spark in Big Data Analytics.
Continue reading “Will Spark Replace Hadoop?”