Big Data – FrontendArts Blog

big data analytics

Big data analytics is the process of examining various legacy data to identify common or discrete patterns, data correlations and other useful information that can be used to make a better decisions. With big data analytics, data scientists and business analyst can analyze huge volumes of data from various database or data systems that conventional analytics and business intelligence solutions cannot produce. Various Consider that your organization could accumulate (if it hasn’t already) billions of rows of data with hundreds of millions of data combinations in multiple data stores and abundant formats. High-performance analytics is necessary to process that much data in order to figure out what’s important and what isn’t.


Historically Business houses collected and stored terabytes of data but never been able to analyze and make meaningful use of the data for decision making preocess in full context. Else they have to wait hours or days to get some metrics ?


With new advances in computing technology, there’s no need to avoid tackling even the most challenging business problems. For simpler and faster processing of only relevant data, you can use high-performance analytics. Using high-performance data mining, predictive analytics, text mining, forecasting and optimization on big data enables you to continuously drive innovation and make the best possible decisions. In addition, organizations are discovering that the unique properties of machine learning are ideally suited to addressing their fast-paced big data needs in new ways. – Amitava Deb


Hadoop for Java Developers

With the revolution in Social media Innovation has changed the outlook of the Business houses in last couple of years. More than 80% of the electronic data worldwide has been created in last 4years. Organizations are collecting data from different disintegrated system for decades, but was never able to use the intelligence collectively a BI for trend analysis, track or critical decision making.

Hadoop logo

Hadoop is written in Java, so developers who already made their hands dirty with Java, can easily pick-up Hadoop than others. Hadoop supports distributed application, was introduced by Dough Cutting & Michael J. Cafarellain in mid of 2006. Hadoop has started gaining momentum in the job market over last couple of years and reasons more than one.

A. Hadoop works on practically any servers and OS. Reason for it to called as “Distributed Processing”. It also called as “Parallel Processing” as it enabled you to work on more than one server simultaneously.

B. MapReduce programs are written in Java, so again its easy for java developer to get speed faster on Hadoop than others.

C. Businesses and Organizations started transitioning into Hadoop in a best possible ways, and are in a constant hunt for java developers skilled in Hadoop.

Hadoop works on two different generation Hadoop 1.0 & Hadoop 2.0 which, is based on YARN (yet another resource negotiator) architecture.

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Learning Hadoop is easier for Java developers, but you need much more than just