High Performance Data Analytics (HPDA) is a multifaceted program introduced in 2013 and is guided by Pacific Northwest National Laboratory. This laboratory helps in focusing on specific areas of research such as graph analytics, streaming analytics, compute intensive analytics, and others. HPDA accelerates big data analytics with the use of high performance computing (HPC). HPCs have been known to contribute enormously to scientific innovation, economic competitiveness, national and regional security, and further improvement of the quality of human life. Demand for HPDA has been backed by the rapid data explosion fueling the stupendous growth of the usage of data analytics systems. Moreover, the proliferation of open source frameworks, commonly identified as ‘Hadoop’ has the ability to successfully manage the powerful HPC systems and process data at higher resolutions. HPDA has been a stepping stone in guiding the performance of these frameworks by hosting them on higher performing hardware like the HPC systems. The number of existing servers is unable to handle the high performance analytics, thus expediting the demand for HPDA. Since the technologies for HPC and enterprise computing have merged, newer opportunities have emerged, driving verticals such as financial services, online retailing, telecommunications, healthcare and others.
Moreover, it has been identified by various organizations that data analytics is critical as both the hardware and the software are prioritized equally to handle the historical (batch) data and real-time streaming data. HPDA has high investment costs for new players, and stringent government rules and regulations regarding data management are the primary concerns for expansion of this market. Other restraining factors for the market are the complexity in programming arising from the massive parallelization and getting sufficient sponsorship for R&D activities. However, HPDA is seeing remarkable growth due to its highly potential drivers such as its wide adaptability and increasing application areas. The development of open source analytic frameworks have aided organizations to tap the vast amounts of data and manipulate the unstructured data in a way that is understandable to the user by enabling quick application on the data set. HPDA not only provides great value to access the large data sets but also enables the analyst to work on it with great speed. Moreover, the advantage of computing real-time or even the value of near-real time computations of live data is driving the latest concept of operations in Activity Based Intelligence (ABI). Therefore, this combination of productivity and achievement has perfectly defined HPDA.
HPDA is an emerging market with consequential segmentation based on component, data type, deployment model, and verticals. Under the component based segment, hardware, software, and services are the three main divisions. Software based component in gaining high traction due to the rigorous deployment of supercomputers and advanced verticals. Furthermore, hardware can be considered either as server or storage systems and services can be further classified into professional and managed services. Based on data type, HPDA can be grouped into unstructured, semi-structured, and structured data. Deployment models include on-premises and on-demand models. Verticals or end-use applications can range from industries such as banking, financial services and insurance, government and defense, manufacturing, media and entertainment, transportation and logistics, healthcare etc. The competitive strategy of most of these sectors is to initiate partnerships, mergers and acquisitions, expansions and healthy collaborations.
The HPDA market is prevalent in all the major continents- North America, Europe, Asia Pacific, Latin America, and Middle East and Africa. However, the market of North America is likely to hold the largest market share, with APAC region having high growth opportunities in the coming years.This is due to the increasing number of manufacturing units in China, India, and other Asia Pacific countries, supporting the market.
The major companies dominating this market are Cisco Systems and SAP SE (Collaborative Products), Red Hat, Inc. and Dell, Inc. (Collaborative Products), Teradata and SAS Institute (Collaborative Products), IBM Corporation, Hewlett-Packard Enterprise, Oracle Corporation, Microsoft Corporation, Intel Corporation, Cray, Inc., Juniper Networks, ATOS SE and others.
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