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Data Infrastructure
Data Infrastructure
The market for Big Data Infrastructure is forecast to reach $4.2 billion by 2026, growing at a CAGR of 32.3% from 2021 to 2026 due to rapid increase in consumer and machine data developments.

The market for Big Data Infrastructure is forecast to reach $4.2 billion by 2026, growing at a CAGR of 32.3% from 2021 to 2026 due to rapid increase in consumer and machine data developments. Big Data is referred as the collection of data sets so large and complex that it is not possible to process it in traditional way. The market will be driven by the growth of the structured and unstructured data. Big Data infrastructure is the cornerstone of the enterprises to sort, store, process and analyze the large data sets. An enterprise generates data in large volume with high velocity and veracity which cannot be stored and processed traditionally and this raises the demand for emerging data intensive analytical technology.

Big Data Infrastructure Market Segment Analysis - By Type

Big Data Infrastructure is the main component of the organization to sort, store, process and analyze the large data sets. Presently the global Big Data adoption trend focuses on application and not in the infrastructure. An enterprises generate the data in terabytes and petabytes which cannot be stored and processed traditionally which raise the demand for up gradation of IT infrastructure. Once there is proper hardware and analytical tool in place you can move up the stack and focus on your database and application. An updated Big Data infrastructure can provide you access, speed and availability of data to make quick decision and corrective approach. The Big Data Infrastructure consists various adoption process such as cluster design, server architecture, network architecture, storage architecture and information Infrastructure architecture. Most enterprises are using the Network attached storage (NAS) and Storage area network (SAN) for implementing Big Data to use the existing infrastructure even though Direct attached storage (DAS) is recommended. The storage segment is expected to dominate the Big Data Infrastructure Market in the forecast period. The storage used for big data needs a huge data handling capacity. The growth of this segment is also due to arrival of a new trend known as object storage. This architecture considers data as object and block and the stores them within the sectors. These factors drive the growth of the big data infrastructure market in the forecast period. 

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Big Data Infrastructure Market Segment Analysis - By End Use Industry

Among all end use industries, automotive is the leading segment due to growing adoption of high tech vehicles. Huge amounts of constantly changing data that is difficult to handle but is of enormous value on the analysis of which we can provide new and improved user experience, is “big data.” In the automotive industry, this data can improve driver safety and experience, and in short provide better and safer vehicle services. Further the increase of electronics and usage of different services, generates the data in large amount which is known as Big Data and these data cannot be stored or analyzed by traditional way so the Big Data Infrastructure provides the ability to handle and process such data.

Big Data Infrastructure Market Segment Analysis - By Geography

North America will dominate the Big Data Infrastructure Market during the forecast period with 41% in 2020. The U.S. is the main region for big data infrastructure due to the presence of players such as HP, Dell, Cisco, and IBM. Big data has a high potential in the U.S due to increasingly extensive data collection practices. In Asia Pacific, the technological developments in the IT sector and growing business operations will benefit the market in the forecast period. Many organisations in Asia Pacific are depending on digital systems to reach their goals.

Big Data Infrastructure Market Drivers

Rising Usage of Hadoop for Bid Data Processing

One of the current trend in the Big Data Infrastructure Market is, the usage of Hadoop for processing, storing and analyzing has been increased compared to other tool such as NoSQL and massive parallel processing. Components such as Hadoop distributed file system, Map Reduce, and Spark are making it preferable. Also there has been an alternative to Hadoop which is making a foot print in the current market named “IBM Info sphere Big Insights” as it has capabilities such as high availability, performance, ease to use and can eliminate the single point of failure events in the Hadoop. Big Data infrastructure is also witnessing growing usage of cloud storage for storage of data which allows improved implementation with Hadoop.

Rising Amount of Data Generated by Organizations

One of the current trends in the Big Data Infrastructure Market is it is widely popular and in demand due to the rising storage capacity in terms of Terabyte and Petabyte of Big Data generated by the organizations. It is widely used because it can handle large amount of data and keep scaling to keep up growth and can provide input and output data to analytical tools for analysis. Big Data challenges include storage of data, capturing data and analyzing data. These can be done by few analytical tools such as Apache Hadoop, NoSQL, JAQL, Hive and others. Out of these tools Apache Hadoop is widely used and is in trend due to its storage capacity, Hadoop file storage system which can split data and can distribute across many nodes thus providing high availability. All these aspects are making Big Data Infrastructure market face higher adoption and we can expect the growth of this market, as more and more organization are looking forward for alternative tool or cloud storage to store its generated data to analyze it and make corrective approach to generate revenue. 

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Big Data Infrastructure Market Challenges

Concerns Regarding Data Privacy

The biggest challenge with Big Data is the sensitive issue of data privacy and Infrastructure, which most organizations are facing. With the implementation of GDPR regulations, consumer data privacy issues have been put to the forefront. Privacy concerns are cropping up as companies feed more and more consumer and vendor data into advanced, AI-fuelled algorithms to create new bits of sensitive information, unbeknownst to affected consumers and employees. This is especially prevalent in the BFSI sector, where consumer data collection has been at the forefront in terms of big data challenges. These data privacy concerns will hinder the adoption of Big Data Infrastructure solutions.

Big Data Infrastructure Market Landscape

Product launches, acquisitions, and R&D activities are key strategies adopted by players in the Big Data Infrastructure Market. Accenture, Amazon Web Service, Dell, HP, IBM, Oracle, Cisco Cloudera, Concurrent, Dataguise and others are considered to be the key players of the Big Data Infrastructure Market.

Acquisitions/Technology Launches/Partnerships

In December 2020, NuWave Solutions Acquired BigBear, a Leading Provider of Big Data Analytics Solutions to the National Infrastructure Community.

In May 2020 Accenture acquired Byte Prophecy, an automated insights and big data analytics company from India. The acquisition will help Accenture to meet what it sees as growing demand for enterprise-scale AI and digital analytics solutions across the region. As part of the deal, nearly 50 data science and data engineer experts will join Accenture Applied Intelligence, the global IT consulting firm’s team and service for artificial intelligence, data, analytics and automation.

Key Takeaways

Growth of cloud based big data analytics will enhance the growth of the big data analytics software.

Growth of structured and unstructured data will provide many opportunities for big data platform.

Use of big data solutions in the financial services sector and analysis of conversations in social networking websites will propel the growth of the Big Data Infrastructure Market.

Large volume of data generated by enterprises will enhance the demand for big data infrastructure in the forecast period.

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