市场调查报告书
商品编码
1453896
到 2030 年的资料探勘工具市场预测 - 按部署类型(云端和本地)、服务、业务功能、组织规模、最终用户和地理位置进行的全球分析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 |
根据 Stratistics MRC 的数据,2023 年全球资料探勘工具市场规模为 7.536 亿美元,预计到 2030 年将达到 18.174 亿美元,预测期内复合CAGR为 13.4%。资料探勘工具是旨在从大型资料集中提取有意义的模式、见解和知识的软体应用程式。这些工具采用各种技术,包括统计分析和机器学习演算法,并促进资料探索和转换的过程,使组织能够发现有价值的资讯以供决策。它们透过对大量资料进行有效分析和解释来推动策略决策和优化运营,在行销、金融、医疗保健和零售等行业中发挥着至关重要的作用。
增加资料量
资料探勘工具使组织能够从海量资料中提取有价值的见解。透过采用先进的演算法和分析技术,这些工具可以发现手动识别不切实际或不可能的隐藏模式和趋势。此外,不断增长的资料量为企业提供了增强客户体验、优化营运和推动创新的机会,从而推动了这一市场规模的发展。
初始成本高
购买资料探勘软体的授权或订阅会产生前期采购成本。这些成本可能是巨大的,特别是对于企业级解决方案或提供高级分析功能的解决方案。此外,持续的维护成本(包括更新、技术支援和基础设施维护)也会增加资料探勘工具的总拥有成本。对于规模较小的组织或预算紧张的组织来说,这些高昂的成本可能会成为重大的进入障碍,限制他们采用资料探勘工具的能力。
基于云端的解决方案的可用性
基于云端的资料探勘工具使组织无需投资和维护昂贵的本地基础设施。这种可访问性使资料探勘民主化,使各种规模的组织都可以利用高级分析,而无需前期资本投资。此外,基于云端的解决方案的可用性降低了进入壁垒,并加快了价值实现时间,从而更有效地从资料中提取可行的见解,从而推动了该市场的扩张。
缺乏专业知识
缺乏拥有有效操作资料探勘工具所需的技术技能和领域知识的专业人员。这导致需求高而供应有限,从而推高了僱用熟练专业人员的成本。然而,由于该领域相对较新且发展迅速,缺乏具备必要专业知识的个人,这对资料探勘工具的成长和采用造成了重大限制。
Covid-19 影响
COVID-19 大流行对资料探勘工具市场产生了一些负面影响,主要是由于经济中断、优先事项的转变以及企业面临的营运挑战。这导致非必要投资的支出减少,包括资料探勘工具和分析软体。此外,疫情造成的供应链中断和专案实施延迟,导致一些组织延后采用资料探勘工具。
预计云部分在预测期内将是最大的
由于其可扩展性、可访问性和成本效益,云端部分预计将占据最大份额,它利用云端运算基础设施来执行资料分析任务。这些工具具有灵活性等优势,允许用户透过网路连接从任何地方存取和分析资料,而无需大量硬体投资。此外,它们通常与其他云端服务集成,促进无缝资料管理和分析工作流程,从而推动该细分市场的成长。
行销部门预计在预测期内复合CAGR最高
由于行销部门在帮助企业从客户资料中获得可行的见解以优化行销策略和活动方面发挥关键作用,预计在预测期内复合CAGR最高。这些工具利用先进的演算法和技术来针对特定的客户服务来满足客户的需求。此外,透过利用预测分析,行销人员可以优化行销预算、有效分配资源并提高行销活动的整体投资报酬率 (ROI),从而推动该细分市场的扩张。
在推断期内,亚太地区占据了最大的市场份额,原因是该地区经济数位化程度不断提高,导致各种来源产生了大量资料。印度、中国和新加坡等国家正成为资料分析创新中心,吸引国内外企业的投资。此外,熟练人才的可用性和新兴的新创生态系统也有助于亚太地区资料探勘工具市场的扩张。
由于欧洲企业越来越意识到利用资料分析获得竞争优势的重要性,预计欧洲在预测期内将出现最高的CAGR。各行业的公司正在认识到数据驱动决策的价值,因此越来越多地投资于资料探勘工具。此外,欧洲各国政府和研究机构正在积极推动促进资料分析创新的倡议,推动该地区复杂资料探勘演算法和工具的开发。
2024 年2 月,英特尔公司推出了英特尔代工厂,作为专为人工智慧时代设计的更具永续性的系统代工业务,并宣布了扩展的工艺路线图,旨在本十年后半段建立领导地位。
2024 年 1 月,GSMA 和 IBM 宣布开展新的合作,透过推出 GSMA Advance 的 AI 培训计划和 GSMA Foundry 生成式 AI 计划,支援生成式人工智慧 (AI) 在电信行业的采用和技能。
2024年1月,英特尔公司和联华电子公司宣布,将合作开发12奈米半导体製程平台,以满足行动、通讯基础设施和网路等高成长市场的需求。
2023 年 12 月,IBM 宣布与 Software AG(Silver Lake 控股的公司)达成最终协议,购买 StreamSets 和 webMethods、Software AG 的 Super iPaaS(整合平台即服务)企业技术平台。
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.