According to Stratistics MRC, the “Global High-Performance Data Analytics Market” is accounted for $22.76 billion in 2016 and is expected to reach $127.38 billion by 2023 growing at a CAGR of 27.8 % during the forecast period. Factors such as increasing number of IT & database industry across the globe, growing data explosion in businesses and production of open source frameworks (Hadoop) for big data analytics are fueling the market growth. However, huge investment prices, strict government rules and regulations are hampering the growth of the market. One of the major opportunities in the market is Uncontrollable amount of data volume across various sectors.
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High performance data analytics refers to the use of high performance computing to inspect large data sets for patterns and insights. Via high performance data analytics it is probable to rapidly inspect large data sets and draw conclusions about the information they contain. It provides benefits such as aEUR error detection, graph modeling and visualization, streaming analytics, investigative data analysis and architecture analysis. There is an increasing demand for HPDA among business organizations as it aids in making a better verdict in less time to gain competitive advantages.
Opportunity: Gradual shift of high performance computing (HPC) systems to high performance data analytics (HDPA) enabled systems has actually stirred the big computing system manufacturers to quick onward their product development, custody pace with the demand for data intensive computing applications. With Internet of Things (IoT) networks suspended to see faster growth, need for advanced computing systems has pushed service providers to improve their existing IT infrastructure. This has resulted in new installations being chosen for high performance data analytics (HPDA) systems over high performance computing systems, enhanced for analytics applications. In assorted developing and urbanized economies, HPC technologies show advantageous to furthering scientific improvement, bolstering economic competitiveness, boosting national security world over.
Driver: Proliferation of open source frameworks (Hadoop) for big data analytics
Hadoop is the present option for software vendors because of its inborn excellence of handling large capacious unstructured amount of data with simplicity. The software leverages on its deployment vis-à-vis the traditional database software as it offers scalability. Scalability allows additional servers to be accommodated in the near future, if the need arises. Furthermore, Hadoop is resilient to failure as it ensures the duplication of data to other nodes in clusters. Hence in the case of manmade or natural calamities, the data backup ensures operational stability. The HPDA market, which is governed by advanced analytics on high-performance computers, deploys Hadoop as its first choice as it helps data scientists to lever capacious data in real time, thus improving performance in the storage hierarchy.
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On the basis of data type, Semi-Structured segment is expected to grow at the significant rate during the forecast period. Semi-structured data is cross among the structured and unstructured data. On one hand, the data lacks the severe data model structure; on the other hand, it is characterized by tags and other markers to discriminate the semantic elements within the data. Semi-structured data does not have the firm structure of a relational database but does have some directorial properties that allow it to be analyzed easily. These data can be establish in documents, e-mails, tweets, and other social media, and is of deep relevance to the enterprises. Most of the data in the internet era is semi-structured and needs to be tailored as per organizational requirements.
By geography, Asia Pacific is projected to have considerable market growth during the forecast period. Among new enlargement opportunities and initiatives taken by vastly contributing countries like India, China, and others to support the emerging technologies like IoT have provided tremendous opportunities to HPDA solution vendors in this region. The other countries of APAC comprise Hong Kong, Indonesia, Singapore, Korea, and Malaysia. The countries are looking onward to embracing the new technologies and adopting HPDA in their mainframe IT infrastructure. For instance, supercomputers are assertively deployed by local community in Singapore with several universities like Institute of HPC, A*Star Computational Resource Centre, and others. Hence, the deployment of HPDA technology looks very bright in the region.
Some of the key players in High Performance Data Analytics Market include Red Hat, Inc, IBM Corporation, Oracle Corporation, Intel Corporation, Juniper Networks, Inc., Cray Inc., Microsoft Corporation, Hewlett-Packard Enterprise, Teradata Corporation, SAP SE, Cisco Systems, ATOS SE, Dell Inc. and SAS Institute.
Red Hat, Inc: July 2017: Red Hat, Inc. has acquired the assets and technology of Permabit Technology Corporation, a provider of software for data deduplication, compression and thin provisioning. With the addition of Permabit’s data deduplication and compression capabilities to the world’s leading enterprise Linux platform, Red Hat Enterprise Linux, Red Hat will be able to better enable enterprise digital transformation through more efficient storage options. With Permabit’s technology, it will also enhance capabilities across Red Hat’s hybrid cloud and storage technologies, including Red Hat OpenStack Platform, Red Hat OpenShift Container Platform and Red Hat Storage.
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SAP SE: Nov 2017: SAP SE has launched new data solution, SAP student activity hub, to provide real-time insight into student behavior and success. The aim of SAP Student Activity Hub is to measurably improve student success, with the long-term goal being to make higher education more affordable, accessible and relevant to students and society. SAP is bringing the power of the SAP HANA platform, SAP Analytics solutions and next-gen innovation to give institutions unprecedented insight into student activity.
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