세계의 고성능 데이터 분석(HPDA) 시장 : 유형별, 컴포넌트별, 업계별, 지역별(2024-2031년)

High Performance Data Analytics (HPDA) Market Valuation - 2024-2031

The need for advanced analytical approaches to provide HPDA solutions is driving the market growth of High Performance Data Analytics (HPDA). According to the analyst from Verified Market Research, The High Performance Data Analytics (HPDA) Market is estimated to reach a valuation of USD 597.06 Billion over the forecast period 2031, by subjugating around USD 113.23 Billion in 2023.

The adoption of an open-source framework for big data analytics is driving market growth. This surge in demand enables the market to grow at a CAGR of 23.1% from 2024 to 2031.

High Performance Data Analytics (HPDA) Market: Definition/ Overview

HPDA refers to big data analytics that uses High-Performance Computing (HPC) techniques. Big data analytics has always relied on high-performance computing (HPC), but as data grows exponentially, new forms of high-performance computing will be required to access previously unimaginable volumes of data. The combination of big data analytics and high-performance computing is called "high-performance data analytics." High-performance data analytics is the process of quickly finding insights from large data sets by running powerful analytical tools in parallel on high-performance computing systems.

Furthermore, high-performance data analytics infrastructure is a rapidly expanding market for government and commercial organizations that need to combine high-performance computing with data-intensive analysis. For complex modeling and simulations, big data analytics techniques like Hadoop and Spark have long required high-performance computing, which they lack.

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Which are the Drivers Encouraging the Adoption of HPDA?

The exponential growth in data volumes across various industries is demanding more sophisticated analytics tools that can effectively handle large datasets while extracting insights from them.

Also, businesses are being encouraged to invest in HPDA technologies to quickly obtain actionable insights due to the growing need for real-time analytics solutions. Thirdly, to extract value from the massive amounts of sensor data being generated by IoT devices, strong analytics capabilities are needed.

Furthermore, the development of artificial intelligence and machine learning technologies is encouraging the use of HPDA by opening up new avenues for predictive modeling and more advanced data analysis. All of these factors together drive HPDA adoption across industries, offering businesses increased agility, efficiency, and competitiveness.

What are the Challenges in High Performance Data Analytics (HPDA) Market?

High Performance Data Analytics (HPDA) holds great promise, but its adoption faces several obstacles. The complexity and diversity of data sources, formats, and structures present a significant challenge to the efficient integration and analysis of heterogeneous datasets. The scalability of HPDA solutions is also a problem because handling large-scale analytics tasks requires robust infrastructure and computational resources, thereby affecting market growth.

Furthermore, adoption is further hampered by the lack of qualified data scientists and analysts who use HPDA technologies to extract insightful data. Smaller businesses also face difficulties in affording the expenses involved in implementing and maintaining HPDA software and infrastructure. They also need to invest in workforce development programs to bridge the skills gap and give more people access to advanced analytics capabilities, limiting its market adoption.

Category-Wise Acumens

How Does HPDA Help in the Growth of the Manufacturing Sector?

According to VMR analysis, the manufacturing segment is estimated to dominate the market during the forecast period. Modern manufacturing processes create massive amounts of data from a wide range of sources, including IoT devices, sensors, and operating systems. This data is complicated and multidimensional, ranging from machine performance measurements to supply chain logistics. HPDA delivers the computational capacity and analytical capabilities required to process and evaluate this data in real-time, allowing firms to optimize production processes, improve quality control, and decrease downtime. The capacity to properly handle and extract value from huge datasets has made HPDA important in the manufacturing sector.

Furthermore, the manufacturing sector faces ongoing pressure to enhance operational efficiency and cut costs while maintaining product quality. HPDA offers predictive maintenance, which anticipates equipment faults before they occur, reducing unplanned downtime and increasing machine lifespan. Furthermore, HPDA enables advanced simulation and modeling methodologies, enabling enterprises to optimize manufacturing processes and supply chain management, resulting in considerable cost reductions and efficiency gains. The economic benefits provided by HPDA have fueled its acceptance and domination in the manufacturing sector.

How does HPDA Help in the Structured Segment of the Market?

The structure segment is estimated to dominate the market during the forecast period. Structured data, due to its organization, provides for more efficient storage, access, and analysis. This is especially crucial in high-performance data analytics, where processing speed and efficiency have a substantial impact on results. Structured data's predictability allows for optimal algorithms and database architectures that can swiftly query and analyze data, making it perfect for applications that require real-time analytics or handle large amounts of data.

Many of the world's data are stored in relational databases, which are designed to accommodate structured data types. Structured data's popularity in HPDA can be attributed in part to its compatibility with current systems on which many firms rely for vital operations. This compatibility assures that firms may use their existing database and analytics investments to do high-performance analytics without requiring major overhauls or migrations to new platforms.

Furthermore, structured data serves as a solid foundation for predictive modeling, trend analysis, and decision-making processes in industries where accuracy is critical, such as financial services, healthcare, and logistics. The ability to use statistical models and machine learning algorithms consistently and properly is a huge benefit, which drives the demand for structured data in high-stakes analytics applications.

High Performance Data Analytics (HPDA) Market

Report Methodology

Country/Region-wise Acumens

Which Region has the Most Potential for Growth of the HPDA Market?

The Asia-Pacific region is estimated to grow at the highest CAGR during the forecast period. There has been a significant increase in data generation due to the fast digitization of all industries in the APAC area. The abundance of available data provides a significant opportunity for HPDA solutions to derive insightful information and drive business growth.

The demand for HPDA solutions is also being further accelerated by the growing adoption of big data and cloud computing in countries such as China, India, Japan, and South Korea, as businesses seek to leverage these capabilities to gain a competitive edge. The APAC region's growing tech-savvy business presence, coupled with increased investments in IT infrastructure and digital transformation initiatives, provides a favorable environment for the adoption of HPDA solutions.

Additionally, government initiatives that promote data analytics, such as Industry 4.0 initiatives and smart city projects, are further driving demand from public sector organizations and spurring innovation in the private sector, thus promoting growth in the HPDA market.

Which Region Dominates in High Performance Data Analytics (HPDA) Market?

North America is estimated to dominate the High Performance Data Analytics (HPDA) Market during the forecast period. One of the drivers for this is that it has a strong technological base and a well-established network of IT vendors. This makes it possible for advanced analytics solutions to be widely adopted by various industries. North America is also home to numerous prominent players in the HPDA market, including startups, significant technology companies, and research institutes, which stimulates competition and innovation in the field.

The region's well-developed regulatory framework and strong emphasis on data privacy and security compliance further aid the adoption of HPDA solutions, particularly in highly regulated industries like government, healthcare, and finance. Also, North America's early adoption of big data and cloud computing technologies has made it easier for businesses looking to leverage data analytics to scale and deploy their systems smoothly.

Furthermore, companies in North America prioritize talent acquisition and development to drive innovation and gain a competitive edge. This availability of a skilled workforce with a focus on analytics, machine learning, and data science further accelerates the adoption of HPDA solutions in the region.

Competitive Landscape

The competitive landscape in the High Performance Data Analytics (HPDA) Market is dynamic and evolving, driven by changing customer preferences, technological advancements, and market dynamics. Providers continue to innovate and differentiate their offerings to stay competitive and capture market share in this rapidly growing market.

Some of the prominent players operating in the High Performance Data Analytics (HPDA) Market include:

Jestec, Japan Honeywell, USA Toshiba, Japan Staff Technologies, Poland Sharp Vision software, USA Qualcomm Technologies, the USA Panasonic, Japan NEC, Japan Hitachi.

Latest Developments:

In March 2022, Panasas, which offers high-performance storage, announced that its PanFS software lineup will now include more data insight and mobility tools. They provide Panasas storage with data management and analytics tools.

In January 2022, AWS added five new features to its database and analytics portfolios. Customers find it simpler to run high-performance database and analytics workloads at scale thanks to these new features for Amazon Document DB, Amazon OpenSearch Service, and Amazon Athena.

TABLE OF CONTENTS

1 INTRODUCTION OF GLOBAL HIGH PERFORMANCE DATA ANALYTICS (HPDA) MARKET

• 1.1 Overview of the Market
• 1.2 Scope of Report
• 1.3 Assumptions

2 EXECUTIVE SUMMARY

3 RESEARCH METHODOLOGY OF VERIFIED MARKET RESEARCH

• 3.1 Data Mining
• 3.2 Validation
• 3.3 Primary Interviews
• 3.4 List of Data Sources

4 GLOBAL HIGH PERFORMANCE DATA ANALYTICS (HPDA) MARKET OUTLOOK

• 4.1 Overview
• 4.2 Market Dynamics
  • 4.2.1 Drivers
  • 4.2.2 Restraints
  • 4.2.3 Opportunities
• 4.3 Porters Five Force Model
• 4.4 Value Chain Analysis

5 GLOBAL HIGH PERFORMANCE DATA ANALYTICS (HPDA) MARKET, BY TYPE

• 5.1 Overview
• 5.2 Structured
• 5.3 Unstructured
• 5.4 Semi-structured

6 GLOBAL HIGH PERFORMANCE DATA ANALYTICS (HPDA) MARKET, BY COMPONENT

• 6.1 Overview
• 6.2 Software
• 6.3 Hardware
• 6.4 Services

7 GLOBAL HIGH PERFORMANCE DATA ANALYTICS (HPDA) MARKET, BY VERTICAL

• 7.1 Overview
• 7.2 Healthcare
• 7.3 Government and Defense
• 7.4 IT and Telecom
• 7.5 Banking, Financial Services, and Insurance (BFSI)
• 7.6 Transportation and Logistics
• 7.7 Retail and Consumer Goods
• 7.8 Others

8 GLOBAL HIGH PERFORMANCE DATA ANALYTICS (HPDA) MARKET, BY GEOGRAPHY

• 8.1 Overview
• 8.2 North America
  • 8.2.1 U.S.
  • 8.2.2 Canada
  • 8.2.3 Mexico
• 8.3 Europe
  • 8.3.1 Germany
  • 8.3.2 U.K.
  • 8.3.3 France
  • 8.3.4 Rest of Europe
• 8.4 Asia Pacific
  • 8.4.1 China
  • 8.4.2 Japan
  • 8.4.3 India
  • 8.4.4 Rest of Asia Pacific
• 8.5 Rest of the World
  • 8.5.1 Latin America
  • 8.5.2 Middle East and Africa

9 GLOBAL HIGH PERFORMANCE DATA ANALYTICS (HPDA) MARKET COMPETITIVE LANDSCAPE

• 9.1 Overview
• 9.2 Company Market Ranking
• 9.3 Key Development Strategies

10 COMPANY PROFILES

• 10.1 Jestec
  • 10.1.1 Overview
  • 10.1.2 Financial Performance
  • 10.1.3 Product Outlook
  • 10.1.4 Key Developments
• 10.2 Japan Honeywell
  • 10.2.1 Overview
  • 10.2.2 Financial Performance
  • 10.2.3 Product Outlook
  • 10.2.4 Key Developments
• 10.3 USA Toshiba
  • 10.3.1 Overview
  • 10.3.2 Financial Performance
  • 10.3.3 Product Outlook
  • 10.3.4 Key Developments
• 10.4 Japan Staff Technologies
  • 10.4.1 Overview
  • 10.4.2 Financial Performance
  • 10.4.3 Product Outlook
  • 10.4.4 Key Developments
• 10.5 Poland Sharp Vision software
  • 10.5.1 Overview
  • 10.5.2 Financial Performance
  • 10.5.3 Product Outlook
  • 10.5.4 Key Developments
• 10.6 USA Qualcomm Technologies
  • 10.6.1 Overview
  • 10.6.2 Financial Performance
  • 10.6.3 Product Outlook
  • 10.6.4 Key Developments
• 10.7 the USA Panasonic
  • 10.7.1 Overview
  • 10.7.2 Financial Performance
  • 10.7.3 Product Outlook
  • 10.7.4 Key Developments
• 10.8 Japan NEC
  • 10.8.1 Overview
  • 10.8.2 Financial Performance
  • 10.8.3 Product Outlook
  • 10.8.4 Key Developments
• 10.9 Japan Hitachi
  • 10.9.1 Overview
  • 10.9.2 Financial Performance
  • 10.9.3 Product Outlook
  • 10.9.4 Key Developments

11 KEY DEVELOPMENTS

• 11.1 Product Launches/Developments
• 11.2 Mergers and Acquisitions
• 11.3 Business Expansions
• 11.4 Partnerships and Collaborations

12 Appendix

• 12.1 Related Research