Artificial Intelligence – A Great Way to Improve Data Handling and Processing

Artificial Intelligence

Early machines were dumb and could only function according to a well-defined set of instructions. However, with the increasing power of the computers and processing networks, it is now possible to create and execute algorithms that can improve their functions with each iteration. This phenomenon is termed as artificial intelligence (AI), although it may be better termed as machine intelligence (MI). Defining Artificial Intelligence(AI) Artificial intelligence is difficult to define with complete clarity. A general definition may be presented as

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The 6 Top Hadoop Distributions that You Can Employ for Your Big Data Needs

top Hadoop distributions

Apache Hadoop is an excellent software framework that allows the processing of big data elements. It can use the power of commodity hardware by employing a modular system and process large sets of data. Hadoop is available in different distributions as companies often deliver it as a packaged deal. It uses the Hadoop Distributed File System (HDFS) which allows the use of different platforms and the ability to perform parallel data processing. Here, we discuss the six top Hadoop distributions that

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A Brief Discussion of Hadoop Core Components

Hadoop core components

Apache Hadoop is an excellent open-source big data technology platform that allows the use of computer networks to perform complex processing and come up with results that are always available even when a few nodes are not available for functional processing. There are a few important Hadoop core components that govern the way it can perform through various cloud-based platforms. The core components are often termed as modules and are described below: The Distributed File System The first and the most

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The Merits of Hadoop as a Data Solution

Hadoop Data Solution

Hadoop is an amazing programming framework which is quickly gaining prominence. It is sponsored by the Apache Software Foundation and has the support of the Java programming community. Hadoop as a solution does have its merits because it can simplify big data and allow normal consumers to simplify the concept of volumetric data available on the internet. Here are some important details to understand this framework: The Arrival of Hadoop Hadoop as a solution was formulated by top computer experts

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How Analytics with R became powerful

r

It seems that developers really love to debate about the different ways to do the same things. Seriously, we love it too, but we don’t think we have seen people argue so much in any other industry. There are always people who will think one way of doing something is better than the other but rarely will this result in widespread online arguments and debates the way it does for programmers. Among many such debates, one that has heated up a

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Why MongoDB is so important for big data

MongoDB

MongoDB often confuses people because they don’t understand what its purpose is. MongoDB doesn’t have a singular purpose – it is good in many instances, and yes, it is bad in some situations too, but that is just how every piece of technology is. We have different languages and databases because no one technology can be the best fit for every situation. The main thing which makes MongoDB so great, especially when it comes to big data, is its approach

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What makes Scala & Spark so powerful?

scala

People who work with Python in Spark often hear people discuss Scala and how good it is. If you are wondering whether you should learn Scala, you are probably asking the same question most people asked before they started using Scala: Is it really that better than Python? The answer, you might be surprised to know, is yes – and it is a definite yes. Usually, the experts always have some caveats, some exceptions where the alternative still proves useful

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What are the advantages of BIG DATA Analytics, and how will it impact the future

Big Data Analytics Advantages

Big Data Analytics Advantages : Big Data Analytics Advantages : In the present era, Big data analytics is no longer used only for the purpose of experimenting. Many companies began to achieve a lot more real results with its approach, and  they are expanding their efforts to surround more data and models. It is a term that used to describe the collection, availability, and processing of streaming data in real-time of  huge volumes. The three V’s are nothing but volume,

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Importance of Big Data Analytics

Big Data Analytics

The term itself is not new and there is a very good reason for that. Companies across the globe, both large conglomerates and small start ups are utilizing its potential to gain valuable insight into existing operations for future development and to improve their customer service. Take today’s data for instance. According to a study conducted by scientists at the UC San Diego, by 2024, most businesses across the globe would have processed the digital equivalent of a gigantic number

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Big Data Market size in coming future

big data

Big Data Market size in coming future Big data is here to stay and business owners couldn’t be happier. The term emerged in a bid to describe the large volumes of information that databases comprise of, manage and maintain, but the concept has taken on a life of its own in the modern era. Now it not only refers to the information itself, but also encompasses a number of technologies that can handle the same tasks to solve complex problems.

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