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市場調査レポート
商品コード
1624502
高性能データ分析(HPDA)市場:タイプ別、コンポーネント別、業界別、地域別、2024年~2031年High Performance Data Analytics Market By Type, By Component, By Vertical, And Region for 2024-2031 |
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高性能データ分析(HPDA)市場:タイプ別、コンポーネント別、業界別、地域別、2024年~2031年 |
出版日: 2024年11月28日
発行: Verified Market Research
ページ情報: 英文 202 Pages
納期: 2~3営業日
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HPDAソリューションを提供するための高度な分析アプローチのニーズが、高性能データ分析(HPDA)市場の成長を促進しています。Verified Market Researchのアナリストによると、高性能データ分析(HPDA)市場は、2023年の約1,132億3,000万米ドルを下回り、予測期間2031年には5,970億6,000万米ドルの評価額に達すると予測されています。
ビッグデータ分析のためのオープンソースフレームワークの採用が市場成長を促進しています。この需要の急増により、市場は2024年から2031年にかけてCAGR 23.1%で成長します。
高性能データ分析(HPDA)市場:定義/概要
HPDAとは、高性能コンピューティング(HPC)技術を利用したビッグデータ分析のことです。ビッグデータ解析は常にハイパフォーマンス・コンピューティング(HPC)に依存してきたが、データが指数関数的に増大するにつれて、これまで想像もつかなかったような大量のデータにアクセスするために、新しい形態のハイパフォーマンス・コンピューティングが必要になります。ビッグデータ・アナリティクスとハイパフォーマンス・コンピューティングの組み合わせは、"ハイパフォーマンス・データ・アナリティクス "と呼ばれています。ハイパフォーマンス・データ・アナリティクスとは、ハイパフォーマンス・コンピューティング・システム上で強力な分析ツールを並列実行することにより、大規模なデータセットから洞察を迅速に見出すプロセスのことです。
さらに、高性能データ分析インフラは、高性能コンピューティングとデータ集約的な分析を組み合わせる必要がある政府機関や民間企業にとって、急速に拡大する市場です。複雑なモデリングやシミュレーションを行うには、HadoopやSparkのようなビッグデータ分析技術が必要ですが、これにはハイパフォーマンス・コンピューティングが不足しています。
さまざまな業界でデータ量が急激に増加しているため、大規模なデータセットを効果的に処理しながら、そこから洞察を引き出すことができる、より高度な分析ツールが求められています。
また、リアルタイム分析ソリューションに対するニーズの高まりから、実用的な洞察を迅速に得るためにHPDAテクノロジーに投資することが企業に推奨されています。第三に、IoT機器から生成される大量のセンサーデータから価値を引き出すには、強力な分析能力が必要です。
さらに、人工知能や機械学習技術の開発は、予測モデリングやより高度なデータ分析に新たな道を開くことで、HPDAの利用を促進しています。これらすべての要因が相まって、各業界でHPDAの導入が促進され、企業の俊敏性、効率性、競合力が向上しています。
高性能データ分析(HPDA)は大きな可能性を秘めているが、その採用にはいくつかの障害があります。データソース、フォーマット、構造の複雑さと多様性は、異種データセットの効率的な統合と分析にとって大きな課題となっています。また、大規模な分析タスクを処理するには堅牢なインフラと計算リソースが必要なため、HPDAソリューションのスケーラビリティも問題であり、市場の成長に影響を及ぼしています。
さらに、HPDAテクノロジーを使って洞察に満ちたデータを抽出する有能なデータサイエンティストやアナリストが不足していることも、採用の妨げになっています。中小企業は、HPDAソフトウェアやインフラの導入・維持にかかる費用を捻出することも困難です。また、スキルギャップを埋め、より多くの人が高度なアナリティクス機能を利用できるようにするためには、人材開発プログラムに投資する必要があり、市場の普及を制限しています。
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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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.
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.
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.
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
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.
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.
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.
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