The high performance data analytics market has been valued at USD 48.28 billion in 2020 and is expected to reach USD 187.57 billion in 2026 registering a CAGR of 25.4% during the forecast period (2021 - 2026).
- A major driver for the growth of the high data performance analytics market is the increasing ability of the powerful high performance computing (HPC) systems to process data at higher resolutions and proliferation of open source frameworks (Hadoop) for big data analytics.
- Furthermore, a large number of businesses are beginning to rely on large scale data analytics for greater insights into their customers’ behavior and their business requirements is also expected to aid the market growth.
- Analytics and AI require immensely powerful processes across compute, networking and storage. As a result, more companies are increasingly using HPC solutions for AI-enabled innovation and productivity. For instance, ZEFF, Inc.’s AI database is a great example of what AI and HPC can achieve together. With HPC, ZEFF has been able to solve tens of millions of image problems for people in a day or less instead of what previously took weeks or months to accomplish. However, investment costs and government regulations may hamper the market.
Key Market Trends
Energy and Utilities Sector to Grow Rapidly
- The energy and utility industry is also amongst the other sectors undergoing a large-scale transformation due to the advent of advanced technologies. One of the major technological drivers which impacted this industry is the emergence of Big Data and analytics.
- Further, the scarcity of fossil fuel is giving rise to alternate sources of energy such as solar, wave, and wind turbines, wherein consumption is increasing at a high pace. Thus, it has become imperative to use advanced tools that use high-performance data analytical tools to understand the behavior or adaption of these sources of energy. For instance, the French energy services company like Edelia, launched a complex energy consumption monitoring and management solution which monitors energy usage in near real-time, enables consumers to control consumption and reduce their carbon footprint.
- Energy and utility organizations apply smart technology to their landscape, including sensors, cloud computing technologies, wireless, power planning, and network communication. These produce large data sets, which gets collected over a period of time. Hence the need for quality information is also likely to aid the market growth. For example, a utility company, using smart meters and power, can gather around three petabytes of data every 15 minutes for a year for about one million households.
North America Expected to Continue to Dominate the Market
- The North America region dominates the market in terms of demand, owing to the presence of major players. The high investment rate, the presence of active collaboration among different enterprises, growing applications of HPDA in areas such as healthcare, academic research, media, and entertainment are amongst few factors driving the regional market growth.
- Further, there are substantial R&D activities in the area of HPC accentuating this regional market. The U.S. is expected to dominate the NorthAmerica region due to strong demand from software and IT sector over the forecast period.
- According to a survey by NewVantage Partners, the success rate of various big data initiatives as of 2019, was 59.5% of the companies reported which have seen measurable results from big data initiatives to decrease expenses.
The competitive landscape of the global high-performance data analytics market is moderately fragmented owing to the presence of many players in the market. The key vendors are continuously innovating in the technology due to the vast array of prospects the market projects. The companies are undergoing mergers and acquisitions, spending vast sums of money on R&D activities, etc.
- February 2019 - Owing to the spectacular rise in the use of Python in high-performance computing applications Intel has extended its services targeting its new applications. With the latest releases of Intel Distribution for Python, included in Intel Parallel Studio XE 2019, the numerical and scientific computing capabilities of high-performance Python now extends to machine learning and data analytics.
- November 2018 - Hewlett Packard Enterprise, collaborated with High-Performance Computing Center Stuttgart (HLRS) to build the fastest supercomputer for industrial production. The new supercomputer, called Hawk, is based on HPEs next-generation high-performance computing (HPC) platform running the new AMD EPYC processor code-named Rome.
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1.1 Study Assumptions
1.2 Scope of the Study
2 RESEARCH METHODOLOGY
3 EXECUTIVE SUMMARY
4 MARKET DYNAMICS
4.1 Market Overview
4.2 Market Drivers
4.2.1 Growing Number of IT & Database Industry Across the Globe
4.2.2 Growing Data Volumes
4.2.3 Advancements in High Performance Computing Activities
4.3 Market Restraints
4.3.1 High Investment Cost
4.3.2 Stringent Government Regulations
4.4 Industry Value Chain Analysis
4.5 Industry Attractiveness - Porter's Five Force Analysis
4.5.1 Bargaining Power of Suppliers
4.5.2 Bargaining Power of Buyers/Consumers
4.5.3 Threat of New Entrants
4.5.4 Threat of Substitute Products
4.5.5 Intensity of Competitive Rivalry
4.6 Technology Snapshot
4.6.1 Grid Computing
4.6.2 In-Database Analytics
4.6.3 In-Memory Analytics
5 MARKET SEGMENTATION
5.1 By Component
5.2 By Deployment
5.3 By Organization Size
5.3.1 Small and Medium Enterprises
5.3.2 Large Enterprises
5.4 By End-user Industry
5.4.2 Government & Defense
5.4.3 Energy & Utilities
5.4.4 Retail & E-commerce
5.4.5 Other End-user Industry
5.5.1 North America
126.96.36.199 United States
188.8.131.52 United Kingdom
184.108.40.206 Rest of Europe
220.127.116.11 Rest of Asia-Pacific
5.5.4 Latin America
18.104.22.168 Rest of Latin America
5.5.5 Middle East & Africa
22.214.171.124 United Arab Emirates
126.96.36.199 Saudi Arabia
188.8.131.52 Rest of Middle-East & Africa
6 COMPETITIVE LANDSCAPE
6.1 Company Profiles
6.1.1 SAS Institute, Inc.
6.1.2 Hewlett Packard Enterprise Development LP
6.1.3 Oracle Corporation
6.1.4 ATOS SE
6.1.5 Juniper Networks, Inc.
6.1.6 Dell Inc.
6.1.7 IBM Corporation (Red Hat, Inc.)
6.1.8 Cisco Systems, Inc.
6.1.9 Intel Corporation
6.1.10 Cray Inc.
7 INVESTMENT ANALYSIS
8 MARKET OPPORTUNITIES AND FUTURE TRENDS
Secondary Research Information is collected from a number of publicly available as well as paid databases. Public sources involve publications by different associations and governments, annual reports and statements of companies, white papers and research publications by recognized industry experts and renowned academia etc. Paid data sources include third party authentic industry databases.
Once data collection is done through secondary research, primary interviews are conducted with different stakeholders across the value chain like manufacturers, distributors, ingredient/input suppliers, end customers and other key opinion leaders of the industry. Primary research is used both to validate the data points obtained from secondary research and to fill in the data gaps after secondary research.
The market engineering phase involves analyzing the data collected, market breakdown and forecasting. Macroeconomic indicators and bottom-up and top-down approaches are used to arrive at a complete set of data points that give way to valuable qualitative and quantitative insights. Each data point is verified by the process of data triangulation to validate the numbers and arrive at close estimates.
The market engineered data is verified and validated by a number of experts, both in-house and external.
REPORT WRITING/ PRESENTATION
After the data is curated by the mentioned highly sophisticated process, the analysts begin to write the report. Garnering insights from data and forecasts, insights are drawn to visualize the entire ecosystem in a single report.