市場調查報告書
商品編碼
1453896
到 2030 年的資料探勘工具市場預測 - 各部署類型(雲端和本地)、服務、業務功能、組織規模、最終用戶和地理位置的全球分析Data Mining Tools Market Forecasts to 2030 - Global Analysis By Deployment Type (Cloud and On-Premises), Service, Business Function, Organization Size, End User and By Geography |
根據 Stratistics MRC 的數據,2023 年全球資料探勘工具市場規模為 7.536 億美元,預計到 2030 年將達到 18.174 億美元,預測期內複合CAGR為 13.4%。資料探勘工具是旨在從大型資料集中提取有意義的模式、見解和知識的軟體應用程式。這些工具採用各種技術,包括統計分析和機器學習演算法,並促進資料探索和轉換的過程,使組織能夠發現有價值的資訊以供決策。它們透過對大量資料進行有效分析和解釋來推動策略決策和最佳化營運,在行銷、金融、醫療保健和零售等行業中發揮著至關重要的作用。
增加資料量
資料探勘工具使組織能夠從海量資料中提取有價值的見解。透過採用先進的演算法和分析技術,這些工具可以發現手動識別不切實際或不可能的隱藏模式和趨勢。此外,不斷成長的資料量為企業提供了增強客戶體驗、最佳化營運和推動創新的機會,從而推動了這一市場規模的發展。
初始成本高
購買資料探勘軟體的授權或訂閱會產生前期採購成本。這些成本可能是巨大的,特別是對於企業級解決方案或提供高級分析功能的解決方案。此外,持續的維護成本(包括更新、技術支援和基礎設施維護)也會增加資料探勘工具的總擁有成本。對於規模較小的組織或預算緊張的組織來說,這些高昂的成本可能會成為重大的進入障礙,限制他們採用資料探勘工具的能力。
基於雲端的解決方案的可用性
基於雲端的資料探勘工具使組織無需投資和維護昂貴的本地基礎設施。這種可訪問性使資料探勘民主化,使各種規模的組織都可以利用高級分析,而無需前期資本投資。此外,基於雲端的解決方案的可用性降低了進入壁壘,並加快了價值實現時間,從而更有效地從資料中提取可行的見解,從而推動了該市場的擴張。
缺乏專業知識
缺乏擁有有效操作資料探勘工具所需的技術技能和領域知識的專業人員。這導致需求高而供應有限,從而推高了僱用熟練專業人員的成本。然而,由於該領域相對較新且發展迅速,缺乏具備必要專業知識的個人,這對資料探勘工具的成長和採用造成了重大限制。
Covid-19 影響
COVID-19 大流行對資料探勘工具市場產生了一些負面影響,主要是由於經濟中斷、優先事項的轉變以及企業面臨的營運課題。這導致非必要投資的支出減少,包括資料探勘工具和分析軟體。此外,疫情造成的供應鏈中斷和專案實施延遲,導致一些組織延後採用資料探勘工具。
預計雲部分在預測期內將是最大的
由於其可擴展性、可訪問性和成本效益,雲端部分預計將佔據最大佔有率,它利用雲端運算基礎設施來執行資料分析任務。這些工具具有靈活性等優勢,允許用戶透過網路連接從任何地方存取和分析資料,而無需大量硬體投資。此外,它們通常與其他雲端服務整合,促進無縫資料管理和分析工作流程,從而推動該區隔市場的成長。
行銷部門預計在預測期內複合CAGR最高
由於行銷部門在幫助企業從客戶資料中獲得可行的見解以最佳化行銷策略和活動方面發揮關鍵作用,預計在預測期內複合CAGR最高。這些工具利用先進的演算法和技術來針對特定的客戶服務來滿足客戶的需求。此外,透過利用預測分析,行銷人員可以最佳化行銷預算、有效分配資源並提高行銷活動的整體投資報酬率 (ROI),從而推動該區隔市場的擴張。
在推斷期內,亞太地區佔據了最大的市場佔有率,原因是該地區經濟數位化程度不斷提高,促使各種來源產生了大量資料。印度、中國和新加坡等國家正成為資料分析創新中心,吸引國內外企業的投資。此外,熟練人才的可用性和新興的新創生態系統也有助於亞太地區資料探勘工具市場的擴張。
由於歐洲企業越來越意識到利用資料分析獲得競爭優勢的重要性,預計歐洲在預測期內將出現最高的CAGR。各行業的公司正在認知到數據驅動決策的價值,因此擴大投資於資料探勘工具。此外,歐洲各國政府和研究機構正在積極推動促進資料分析創新的舉措,推動該地區複雜資料探勘演算法和工具的開發。
2024 年2 月,英特爾公司推出了英特爾代工廠,作為專為人工智慧時代設計的更具永續性的系統代工業務,並宣布了擴展的工藝路線圖,旨在本十年後半段建立領導地位。
2024 年 1 月,GSMA 和 IBM 宣布開展新的合作,透過推出 GSMA Advance 的 AI 培訓計劃和 GSMA Foundry 生成式 AI 計劃,支援生成式人工智慧 (AI) 在電信行業的採用和技能。
2024年1月,英特爾公司和聯華電子公司宣布,將合作開發12奈米半導體製程平台,以滿足行動、通訊基礎設施和網路等高成長市場的需求。
2023 年 12 月,IBM 宣布與 Software AG(Silver Lake 控股的公司)達成最終協議,購買 StreamSets 和 webMethods、Software AG 的 Super iPaaS(整合平台即服務)企業技術平台。
According to Stratistics MRC, the Global Data Mining Tools Market is accounted for $753.6 million in 2023 and is expected to reach $1,817.4 million by 2030 growing at a CAGR of 13.4% during the forecast period. Data mining tools are software applications designed to extract meaningful patterns, insights, and knowledge from large datasets. These tools employ various techniques, including statistical analysis and machine learning algorithms, and facilitate the process of data exploration and transformation, enabling organizations to uncover valuable information for decision-making. They play a crucial role in industries such as marketing, finance, healthcare, and retail by enabling efficient analysis and interpretation of vast amounts of data to drive strategic decisions and optimize operations.
Increasing data volume
Data mining tools enable organizations to extract valuable insights from this massive volume of data. By employing advanced algorithms and analytical techniques, these tools can uncover hidden patterns and trends that would be impractical or impossible to identify manually. Furthermore, the increasing data volume presents opportunities for businesses to enhance customer experiences, optimize operations, and drive innovation, which are propelling this market size.
High initial cost
There is upfront acquisition costs associated with purchasing licenses or subscriptions for data mining software. These costs can be substantial, especially for enterprise-grade solutions or those offering advanced analytics capabilities. Moreover, ongoing maintenance costs, including updates, technical support, and infrastructure maintenance, contribute to the total cost of ownership of data mining tools. For smaller organizations or those operating on tight budgets, these high costs can act as a significant barrier to entry, limiting their ability to adopt data mining tools.
Availability of cloud-based solutions
Cloud-based data mining tools eliminate the need for organizations to invest in and maintain expensive on-premises infrastructure. This accessibility democratizes data mining, making it feasible for organizations of all sizes to leverage advanced analytics without an upfront capital investment. In addition, the availability of cloud-based solutions lowers barriers to entry and accelerates time-to-value to extract actionable insights from their data more efficiently, which is boosting this market's expansion.
Lack of expertise
There is a scarcity of professionals who possess the technical skills and domain knowledge required to effectively operate data mining tools. This had led to high demand and limited supply, driving up the cost of hiring skilled professionals. However, due to the relatively new and rapidly evolving nature of the field, there was a shortage of individuals with the requisite expertise, which posed a significant constraint on the growth and adoption of data mining tools.
Covid-19 Impact
The COVID-19 pandemic has had several negative impacts on the data mining tools market, primarily due to economic disruptions, shifts in priorities, and operational challenges faced by businesses. This has led to a reduction in spending on non-essential investments, including data mining tools and analytics software. Additionally, the disruptions to supply chains and delays in project implementations caused by the pandemic have led to delays in the adoption of data mining tools by some organizations.
The cloud segment is expected to be the largest during the forecast period
The cloud segment is estimated to hold the largest share due to its scalability, accessibility, and cost-effectiveness, which leverage cloud computing infrastructure to perform data analysis tasks. These tools offer advantages such as flexibility, allowing users to access and analyze data from anywhere with an internet connection without requiring extensive hardware investments. Moreover, they often integrate with other cloud services, facilitating seamless data management and analysis workflows, thereby driving this segment's growth.
The marketing segment is expected to have the highest CAGR during the forecast period
The marketing segment is anticipated to have highest CAGR during the forecast period due to its pivotal role in helping businesses gain actionable insights from customer data to optimize marketing strategies and campaigns. These tools utilize advanced algorithms and techniques to target specific customer services to meet customer needs. Additionally, by leveraging predictive analytics, marketers can optimize marketing budgets, allocate resources efficiently, and improve the overall return on investment (ROI) of marketing campaigns, which is boosting this segment's expansion.
Asia Pacific commanded the largest market share during the extrapolated period, owing to the increasing digitization of economies across the region, which has led to the generation of vast amounts of data from various sources. Countries like India, China, and Singapore are emerging as hubs for data analytics innovation, attracting investment from both domestic and international players. In addition, the availability of skilled talent and a burgeoning startup ecosystem are contributing to the expansion of the data mining tools market in Asia Pacific.
Europe is expected to witness highest CAGR over the projection period, owing to a growing awareness among European businesses about the importance of leveraging data analytics for competitive advantage. Companies across various industries are recognizing the value of data-driven decision-making and are thus increasingly investing in data mining tools. Furthermore, European governments and research institutions are actively promoting initiatives to foster innovation in data analytics, driving the development of sophisticated data mining algorithms and tools within the region.
Key players in the market
Some of the key players in the Data Mining Tools Market include Microsoft, IBM, Oracle, SAS Institute, Intel, RapidMiner, Teradata, KNIME, SAP SE, Salford Systems, Megaputer, Biomax Informatics, Dataiku, Reltio, SenticNet, Wolfram, Business Insight, MathWorks, Alteryx, H2O.ai and Angoss.
In February 2024, Intel Corp. launched Intel Foundry as a more sustainable systems foundry business designed for the AI era and announced an expanded process roadmap designed to establish leadership into the latter part of this decade.
In January 2024, The GSMA and IBM announced a new collaboration to support the adoption and skills of generative artificial intelligence (AI) in the telecom industry through the launch of GSMA Advance's AI Training program and the GSMA Foundry Generative AI program.
In January 2024, Intel Corp. and United Microelectronics Corporation announced that they will collaborate on the development of a 12-nanometer semiconductor process platform to address high-growth markets such as mobile, communication infrastructure and networking.
In December 2023, IBM announced that it has entered into a definitive agreement with Software AG, a company majority owned by Silver Lake, to purchase StreamSets and webMethods, Software AG's Super iPaaS (integration platform-as-a-service) enterprise technology platforms.