市場調查報告書
商品編碼
1438221
2030 年巨量資料技術市場預測:按解決方案、服務、部署、組織規模、應用程式、最終用戶和地區進行的全球分析Big Data Technology Market Forecasts to 2030 - Global Analysis By Solution, Service, Deployment, Organisation Size, Application, End User and By Geography |
根據Stratistics MRC預測,2023年全球巨量資料技術市場規模將達3,572億美元,預計2030年將達到9,850億美元,預測期內年複合成長率為15.6%。
巨量資料技術是指一組工具、技術和技術,旨在從傳統資料處理系統無法有效處理的大型複雜資料集進行處理、分析和提取有價值的見解。巨量資料允許公司透過分析客戶偏好和行為來創建個人化的客戶體驗。因此,有針對性的行銷宣傳活動變得更加有效,客戶參與也隨之提高。
根據 2022 年發布的《全球巨量資料和分析支出指南》,到 2025 年,巨量資料技術支出將增加 1.6 倍。
數位轉型
隨著公司努力在數位時代保持競爭力和相關性,他們擴大採用巨量資料技術來利用資料的巨大潛力。巨量資料技術使組織能夠捕獲、處理和分析來自不同來源的大量資料,使他們能夠獲得可行的見解。此外,巨量資料將促進資料主導的經營模式的發展,開闢新的收益來源和提高效率的途徑。因此,數位轉型成為拉動市場需求的關鍵因素。
資料安全和隱私問題
收集和分析的資料量龐大且來源多樣,使組織面臨潛在的安全漏洞和未授權存取。巨量資料應用涉及敏感資訊的處理,增加了侵犯隱私的風險,導致法律和聲譽受損。然而,遵守 GDPR 和 CCPA 等資料保護條例會增加挑戰的複雜性。因此,資料安全和隱私問題是阻礙市場擴張的重要因素。
技術進步
運算能力、儲存能力和網路基礎設施的持續創新有助於提高巨量資料解決方案的可擴展性和效率。人工智慧 (AI) 和機器學習 (ML) 演算法的整合增強了資料分析,並實現了更高級的模式識別和預測建模。此外,Apache Hadoop和Apache Spark等先進資料處理框架的發展進一步加速了大型資料集的分析。
缺乏熟練勞動力
巨量資料技術的快速發展超越了擁有必要專業知識的專業人員的能力。擅長處理大型資料集和實施高階分析的資料科學家、分析師和工程師始終供不應求。然而,人手不足正在阻礙巨量資料解決方案在各行業的有效實施和利用。此外,由於競爭和資源限制,小型企業可能難以吸引和留住技術人員。
COVID-19 的影響
COVID-19的疫情對巨量資料技術市場產生了重大影響。隨著遠距工作、電子商務和數位互動的突然激增,組織越來越依賴巨量資料分析來應對不斷變化的環境。對即時資料洞察的需求激增,推動了巨量資料技術的採用,以實現敏捷決策和危機管理。此外,疫情期間的經濟不確定性導致一些公司重新考慮其技術預算,影響了他們投資巨量資料計劃的計畫。
巨量資料分析產業預計在預測期內成為最大的產業
預計巨量資料分析領域將佔最大佔有率。巨量資料分析幫助企業在現代資料驅動的環境中做出明智的決策、最佳化流程並獲得競爭優勢。這個過程涵蓋了多種技術,包括機器學習、預測分析和資料探勘,使公司能夠從資料中獲得可行的見解。隨著公司不斷應對不斷擴大的資料集,對熟練的巨量資料分析解決方案的需求仍然很高。
預計 BFSI 細分市場在預測期內將呈現最高的年複合成長率。
預計 BFSI 領域將在預測期內實現良好成長。 BFSI 的巨量資料分析處理和分析大資料集,以深入了解客戶行為、詐欺偵測和市場趨勢。預測分析在評估信用風險、識別潛在詐欺和最佳化投資組合方面發揮關鍵作用。此外,即時分析可以幫助監控金融交易中的可疑活動並確保監管合規性。隨著 BFSI 產業繼續應對複雜且動態的環境,巨量資料技術的整合變得至關重要。
在估計期間,北美佔據了最大的市場佔有率。該地區成熟的技術基礎設施、廣泛的投資能力和成熟的商業生態系統構成了其優勢。該地區受益於包括資料科學家和工程師在內的熟練勞動力,推動了分析、機器學習和人工智慧的持續發展。此外,該地區的戰略地位和對技術進步的承諾使其成為關鍵參與者,並在全球範圍內塑造巨量資料技術市場的軌跡。
預計亞太地區在預測期內將實現盈利成長。數位化的提高、人口的快速成長以及中產階級的崛起正在豐富資料生成生態系統,並為巨量資料應用提供充足的機會。此外,該地區各國政府正積極推行數位轉型、智慧城市計畫和工業 4.0,推動了對高階分析和資料主導決策的需求。
According to Stratistics MRC, the Global Big Data Technology Market is accounted for $357.2 billion in 2023 and is expected to reach $985 billion by 2030 growing at a CAGR of 15.6% during the forecast period. Big Data Technology refers to a set of tools, techniques, and technologies designed to process, analyze, and extract valuable insights from large and complex datasets that traditional data processing systems cannot handle efficiently. Big Data enables organizations to create personalized experiences for customers by analyzing their preferences and behaviours. This results in more effective targeted marketing campaigns and higher customer engagement.
According to the Worldwide Big Data and Analytics Spending Guide published in 2022, the spending on big data technology will rise by 1.6 times by 2025.
Digital transformation
As organizations strive to stay competitive and relevant in the digital era, they are increasingly embracing big data technologies to harness the immense potential of data. Big Data technologies enable organizations to capture, process, and analyze vast amounts of data from diverse sources, empowering them to derive actionable insights. Moreover, big data facilitates the development of data-driven business models, opening avenues for new revenue streams and improved efficiency. As a result, digital transformation is a significant factor propelling market demand.
Data security and privacy concerns
The massive volume and diverse sources of data collected and analyzed expose organizations to potential security breaches and unauthorized access. As big data applications involve the processing of sensitive information, there is a heightened risk of privacy violations, leading to legal and reputational repercussions. However, compliance with data protection regulations, such as GDPR and CCPA, adds complexity to the challenge. Therefore, data security and privacy concerns pose a critical restraint hampering market expansion.
Technological advancements
Continuous innovation in computing power, storage capabilities, and networking infrastructure contributes to the scalability and efficiency of big data solutions. The integration of artificial intelligence (AI) and machine learning (ML) algorithms enhances data analytics, enabling more sophisticated pattern recognition and predictive modeling. Moreover, the development of advanced data processing frameworks, such as Apache Hadoop and Apache Spark, further accelerates the analysis of large datasets.
Lack of skilled workforce
The rapid evolution of big data technologies has outpaced the availability of professionals with the requisite expertise. The demand for data scientists, analysts, and engineers proficient in handling large datasets and implementing advanced analytics is consistently high. However, a shortage impedes the effective adoption and utilization of big data solutions across industries. Moreover, small and medium-sized enterprises may find it challenging to attract and retain skilled personnel due to competition and resource constraints.
Covid-19 Impact
The COVID-19 pandemic had a significant impact on the big data technology market. With the sudden surge in remote work, e-commerce, and digital interactions, organizations increasingly rely on big data analytics to navigate the evolving landscape. The demand for real-time data insights surged, driving the adoption of big data technologies for agile decision-making and crisis management. Moreover, economic uncertainties during the pandemic led some businesses to reassess their technology budgets, impacting investment plans in big data projects.
The big data analytics segment is expected to be the largest during the forecast period
The big data analytics segment is estimated to hold the largest share. Big Data Analytics empowers businesses to make informed decisions, optimize processes, and gain a competitive edge in a modern data-driven environment. This process encompasses various methodologies, including machine learning, predictive analytics, and data mining, enabling organizations to derive actionable insights from their data. As businesses continue to grapple with ever-expanding datasets, the demand for proficient big data analytics solutions remains high.
The BFSI segment is expected to have the highest CAGR during the forecast period
The BFSI segment is anticipated to have lucrative growth during the forecast period. Big data analytics in BFSI involves processing and analyzing large datasets to derive insights related to customer behavior, fraud detection, and market trends. Predictive analytics plays a crucial role in assessing credit risk, identifying potential fraud, and optimizing investment portfolios. Moreover, real-time analytics aids in monitoring financial transactions for suspicious activities and ensuring regulatory compliance. As the BFSI sector continues to navigate a complex and dynamic landscape, the integration of big data technologies becomes essential.
North America commanded the largest market share during the extrapolated period. The region's well-established technological infrastructure, extensive investment capabilities, and mature business ecosystem contribute to its dominance. The region benefits from a skilled workforce including data scientists and engineers, driving continuous development in analytics, machine learning, and artificial intelligence. Moreover, the region's strategic position and commitment to technological advancements position it as a key player, shaping the trajectory of the big data technology market on a global scale.
Asia Pacific is expected to witness profitable growth over the projection period. Increasing digitization, a burgeoning population, and a rising middle class contribute to a substantial data generation ecosystem, providing ample opportunities for big data applications. Furthermore, governments in the region are actively promoting digital transformation, smart city initiatives, and Industry 4.0, driving the demand for advanced analytics and data-driven decision-making.
Key players in the market
Some of the key players in the Big Data Technology Market include Oracle Corporation, Cisco Systems, Inc., Microsoft Corporation, Hitachi Limited, IBM Corporation, Teradata Corporation, SAP SE, Fujitsu Limited, Dell Technologies, Inc., Amazon Web Services, Google Analytics, Accenture and Informatica.
In January 2024, Fujitsu and Delft University of Technology announced the establishment of the Fujitsu Advanced Computing Lab Delft at Delft University of Technology, an industry-academia collaboration hub dedicated to the development of quantum computing technologies.
In September 2023, Oracle Corporation and Microsoft expand partnership to deliver Oracle Database Services on Oracle Cloud Infrastructure in Microsoft Azure datacenters.
In September 2023, Oracle and Informatica an enterprise cloud data management leader, have advanced their strategic partnership with the creation of an Oracle Cloud Infrastructure (OCI) point of delivery to thousands of joint customers across North America.
In May 2023, Fujitsu Limited and Microsoft Corporation announced a five-year strategic partnership to significantly expand their existing collaboration.
In April 2023, Dell Technologies collaborates with Ericsson to deliver added resilience and interconnectivity to aid communications service providers in their Cloud RAN journey