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+42% CAGR Growth to Be Achieved by Big Data Analytics & Hadoop Market Through 2023 Including Top Key Player Like Dell, IBM, HP, Greenplum, Fujitsu, Amazon Web Service

The report includes a thorough overview of the competitive landscape and regulatory framework of the Global Big Data Analytics & Hadoop Market.


Houston, TX -- (SBWIRE) -- 08/15/2018 -- Hadoop is a Java-based programming structure that is used for processing and storage of large data sets in a distributed computing environment. It is a distributed processing technology that provides expansive data storage facility and handles thousands of terabytes of data and rapid data transfer among nodes. Hadoop is extensively used in big data analytics, including scientific analytics, business and sales development, and enormous volumes of data processing.

The Big Data Analytics & Hadoop market is expected to grow at +42% of CAGR between 2018 and 2022.

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Among the end users, the banking, finance and insurance sectors are expected to lead the massive error analysis and large data analysis markets during the forecast period (2018-2022). Banking and finance has seen rapid growth due to the increased adoption of information technology solutions for improved financial services. The proliferation of online transactions is increasingly being adopted by technologies such as National Electronic Fund Transfer (NEFT), Real-time Gross Settlement Systems (RTGS), Electronic Clearing Services (ECS)

The amount of data generated by the telecommunications industry is high in speed and volume. In a competitive industry, telcos need to collect information about customer behavior and preferences to differentiate their products and target customers effectively. Applying Hadoop's high-volume data analysis to telecommunications, you can create opportunities for telcos by leveraging the Hadoop framework for large data ecosystems by combining unparalleled marketing capabilities with a combination of real-time insights and customer habits and preferences.

The global Hadoop market is segmented by component, end user and region. Component segments consist of software, hardware, and services. The Hadoop service market is classified as consulting, training and outsourcing services, integration and deployment services, middleware and support services. The Hadoop software market is divided into application software, packaged software, management software, and performance monitoring software. Currently, packaged software is expected to see the highest CAGR by 2022, while application software is the largest monetization area in the global Hadoop software market.

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Top Key Player Studied In this Research are:
Dell, Karmasphere, Talend, DataDirect Networks, Amazon Web Service, HORTONWORKS, Appistry, NetApp, Teradata Corporation, Cloudera, The Hewlett-Packard Company, Greenplum, Datameer, Zettaset, Fujitsu, Pentaho Corporation, DataStax, Platform Computing, HStreaming, MapR Technologies, IBM

Regional Outlook:
Major markets include North America, Europe, Asia Pacific, the Middle East and Africa, and Central and South America. North America and Europe have recently dominated this market and are expected to show a similar trend during the forecast period. Developing countries such as Asia Pacific are expected to grow rapidly during the forecast period due to rapid industrialization and urbanization. Government initiatives such as building a smarter city are likely to open up enough growth opportunities over the next eight years.

Table of Contents
Global Big Data Analytics & Hadoop Market Research Report.
Chapter 1 Big Data Analytics & Hadoop Market Overview
Chapter 2 Global Economic Impact
Chapter 3 Competition by Manufacturer
Chapter 4 Production, Revenue (Value) by Region
Chapter 5 Supply (Production), Consumption, Export, Import by Regions
Chapter 6 Production, Revenue (Value), Price Trend by Type
Chapter 7 Analysis by Application
Chapter 8 Manufacturing Cost Analysis
Chapter 9 Industrial Chain, Sourcing Strategy and Downstream Buyers
Chapter 10 Marketing Strategy Analysis, Distributors/Traders
Chapter 11 Market Effect Factors Analysis
Chapter 12 Market Forecast

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