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市场调查报告书
商品编码
1309681
DataOps平台全球市场规模、份额、行业趋势分析报告:按部署、按服务模式、按组件、按行业、按地区、2023-2030年预测Global DataOps Platform Market Size, Share & Industry Trends Analysis Report By Deployment, By Service Model (Agile Development, DevOps and Lean Manufacturing), By Component, By Vertical, By Regional Outlook and Forecast, 2023 - 2030 |
到 2030 年,DataOps 平台市场规模预计将达到 146 亿美元,预测期内復合年增长率为 21.2%。
市场增长因素
数据复杂性和数量
组织必须处理来自多个来源的不断增长的数据量,包括结构化和非结构化格式以及实时数据流。 数据的数量、速度和多样性使得传统的数据管理技术难以跟上,经常导致数据处理和分析效率低下、错误和延迟。 借助 DataOps 平台,组织可以有效地集成、处理和分析数据,该平台提供了处理这种复杂性所需的工具和技术。 数据操作平台支持批处理和实时数据流。 这些因素正在推动市场增长。
越来越多地采用云端原生 DataOps
云端原生 DataOps 仍然是 DataOps 平台市场中相对较新的补充,但随着越来越多的公司寻求实现数据运营现代化,它正在迅速超越其他方法。 在云端计算平台上创建和部署数据管道和流程是该策略的基础。 云端原生 DataOps 的主要优势之一是可扩展性。 云端技术可以快速扩展资源,使组织能够管理大量数据,而无需担心基础设施的限制。 预计这将推动各种最终用户对 DataOps 平台的使用并推动市场扩张。
市场限制
需要解决人才短缺带来的挑战
对更多合格专业人员的需求是市场上最大的障碍之一。 DataOps 平台需要数据科学、数据工程、软件开发和运营方面的专家。 然而,具有这些特定技能的专业人员严重短缺,造成了人才缺口。 因此,公司很难找到合格的候选人来设计、实施和维护数据运营平台。 此外,技术的快速发展正在加剧这种人才缺口。 因此,现有团队成员可能需要额外的培训或再培训才能熟悉 DataOps 方法。
组件展望
根据组件,市场分为平台和服务。 平台细分市场在 2022 年以最大的收入份额占据市场主导地位。 该细分市场的增长是由于它用于解决数据生产和处理效率低下以及由错误和不一致引起的数据质量差等问题。 该平台为供应链中的每个人提供了敏捷软件的访问权限,用于在数据的整个生命週期中进行集成和优化的数据整理、治理、管理和配置。
服务模式前景
根据服务模式,市场分为敏捷开发、DevOps 和精益製造。 DevOps 细分市场将在 2022 年获得显着的市场收入份额。 这是因为 DataOps 使用 DevOps 工具将数据洞察转换为生产就绪的输出。 此外,实时监控是这些技术的一项功能,有助于优化数据管道。 此外,DevOps 原则有助于顺利实施用户和业务团队提供的输入。 因此,DevOps 的这些特征预计将在预测期内大幅扩展该领域。
发展前景
根据部署,市场分为云端和本地。 2022 年,云端细分市场将占据市场最大的收入份额。 该细分市场的增长得益于云端部署的采用,它允许客户通过互联网连接从任何地方访问 DataOps 平台,从而提高了灵活性和可访问性。 增加的可访问性使企业能够利用平台功能,而不受物理位置的限制。
云端前景
按云端类型,市场分为公有云端、私有云端和混合云端。 公共云端将在 2022 年占据最大的销售份额并引领市场。 这是因为公共云端是最流行的云端计算实施形式。 在公共云端中,提供商拥有并管理硬件、软件和其他支持基础设施。 使用公共云端,用户只需为服务付费,而不是硬件或软件。 公共云端也不需要维护。 此外,资源可按需提供以满足业务需求,从而实现近乎无限的可扩展性。
行业展望
按行业划分,可分为 BFSI、医疗保健和牙科、零售、製造、政府、IT 和电信、能源和公用事业、媒体和娱乐等。 在2022年的市场中,IT和电信行业将占据较大的收入份额。 这是因为快速、安全地访问数据对于在大规模运营的同时提供卓越且差异化的消费者体验至关重要。 通过部署DevOps数据平台,运营商还可以保护个人客户数据,同时安全高效地为云端迁移等项目提供企业数据。
区域展望
按地区划分,我们对北美、欧洲、亚太地区和拉美地区 (LAMEA) 的市场进行了分析。 北美地区将在 2022 年以最大的收入份额引领市场。 这是由于该地区蓬勃发展的技术行业以及对创新和数字化转型的坚定不移的奉献。 DataOps 平台在北美的广泛采用是由对创新和数字化转型的坚定关注推动的。 北美公司不断寻找新的战略来促进创新并获得竞争优势。
The Global DataOps Platform Market size is expected to reach $14.6 billion by 2030, rising at a market growth of 21.2% CAGR during the forecast period.
Asia Pacific region is the most promising region for DataOps platforms due to several causes, including the exponential expansion of big data, the popularity of cloud computing, and the development of artificial intelligence. Hence, Asia Pacific acquired $892.1 million revenue in the market in 2022. In addition, businesses are looking for automated solutions to manage their data effectively due to the unprecedented growth in data volumes to cut costs, enhance operational efficiency, and improve data quality. In the Asia Pacific region, the DataOps platform business environment is broad and continuously changing. It includes a wide range of technology manufacturers, service providers, and consulting companies that offer enterprises complete end-to-end data management solutions.
The major strategies followed by the market participants are Product Launches as the key developmental strategy in order to keep pace with the changing demands of end users. For instance, In May 2023, IBM announced the launch of the Watsonx Platform, a data platform used for increasing the effect of AI and features IBM Watsonx.ai used for testing and deploying new AI capabilities, IBM Watsonx.data, a data store used for governed data, and IBM Watsonx.governance, an AI-powered workflow enabler. Additionally, In May 2023, Hitachi Vantara announced the launch of Data Reliability Engineering (DRE), a collection of services used for enhancing the uniformity and quality of important business data. It features metadata engineering, data cost optimization, AI-powered automation, and data lineage for providing complete transparency and reliability throughout the data lifecycle.
Based on the Analysis presented in the KBV Cardinal matrix; Microsoft Corporation is the major forerunner in the Market. In October 2022, Microsoft announced the launch of ArcBox for DataOps. ArcBox for DataOps is a data-based service used for the automation of deployment of different business operations. The service features Azure Infrastructure and integrations and three Kubernetes clusters. Companies such as Hitachi Vantara LLC, Accenture PLC, Oracle Corporation are some of the key innovators in the Market.
Market Growth Factors
Rising data complexity and volumes
Organizations have to cope with ever-increasing amounts of data from many sources, in structured and unstructured formats, as well as real-time data streams. The quantity, velocity, and diversity of data frequently make it difficult for traditional data management techniques to keep up, which causes inefficiencies, mistakes, and delays in data processing and analysis. Organizations may integrate, process, and analyze data effectively with the help of DataOps platforms, which provide the required tools and technology to handle this complexity. Platforms for data operations can enable both batch processing and real-time data streaming. These factors are fueling the growth of the market.
The rising adoption of cloud-native DataOps
Despite the fact that cloud-native DataOps is still a relatively new development in the market for DataOps platforms, it is quickly overtaking other approaches as more companies look to modernize their data operations. Creating and deploying data pipelines and processes on cloud computing platforms is the foundation of this strategy. One of the main advantages of cloud-native DataOps is scalability. Cloud technology enables quick resource expansion, so organizations can manage large volumes of data without worrying about infrastructure restrictions. This is anticipated to promote the use of the DataOps platform by different end users, propelling the market expansion.
Market Restraining Factors
Need to address the challenges posed by the talent shortage
The need for more highly competent professionals is one of the most significant obstacles in the market. DataOps platforms necessitate data science, data engineering, software development, and operations experts. However, there is a talent gap due to a severe shortage of professionals with these specific skills. As a result, organizations are having trouble locating qualified candidates to design, implement, and maintain DataOps platforms. In addition, the rapid velocity of technological development is exacerbating this talent gap. As a result, existing team members may require additional or retraining to acclimate to the DataOps methodology.
Component Outlook
Based on component, the market is segmented into platform and services. The platform segment dominated the market with maximum revenue share in 2022. The segment growth is due to its usage to address issues with inefficient data production and processing and poor data quality brought on by mistakes and inconsistencies. It gives everyone in the supply chain access to agile software for data curation, governance, management, and provisioning that is integrated and optimized throughout the full data lifetime.
Service Model Outlook
On the basis of service model, the market is divided into agile development, DevOps and lean manufacturing. The DevOps segment procured a substantial revenue share in the market in 2022. This is because DataOps uses DevOps tools to convert data insights into outputs for production. In addition, real-time monitoring is a feature of these technologies that aid in optimizing the data pipelines. Moreover, the DevOps principles aid in smoothly implementing the inputs supplied by the user and business teams. Thus, such features of the DevOps are anticipated to surge the segment's expansion in the projected period.
Deployment Outlook
By deployment, the market is classified into cloud and on-premise. The cloud segment witnessed the largest revenue share in the market in 2022. The segment's growth results from the adoption of cloud deployment, which allows customers to access the DataOps platform from any location with an internet connection, increasing flexibility and accessibility. Businesses may now take advantage of the platform's capabilities without being constrained by physical location owing to the improved accessibility.
Cloud Type Outlook
Under the cloud type, the market is divided into public cloud, private cloud, and hybrid cloud. The public cloud segment led the market with maximum revenue share in 2022. This is because the most prevalent form of cloud computing deployment is public clouds. The provider owns and manages the hardware, software, and other supporting infrastructure with a public cloud. With the public cloud, users only pay for their services and don't need to buy hardware or software. No maintenance is required with the public cloud. In addition, on-demand resources are available to match business needs, providing nearly infinite scalability.
Vertical Outlook
Based on the vertical, the market is bifurcated into BFSI, healthcare & dental, retail, manufacturing, government, IT & telecommunications, energy & utilities, media & entertainment and others. The IT & telecommunication segment recorded a significant revenue share in the market in 2022. This is because fast and secure access to data is essential to provide exceptional, differentiating consumer experiences while operating at a large scale. In addition, telecom operators can supply enterprise data safely and effectively for projects like cloud migration while safeguarding private customer data by implementing a DevOps data platform.
Regional Outlook
Region-wise, the market is analyzed across North America, Europe, Asia Pacific, and LAMEA. The North America region led the market by generating the maximum revenue share in 2022. This is due to the region's thriving technology sector and unwavering dedication to innovation and digital transformation. The region's unwavering focus on innovation and digital transformation is the primary factor behind the widespread use of DataOps platforms in North America. Businesses in North America are constantly looking for new strategies to encourage innovation and acquire a competitive edge.
The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include Microsoft Corporation, IBM Corporation, Oracle Corporation, Amazon Web Services, Inc. (Amazon.com, Inc.), Informatica, LLC, Teradata Corporation, Wipro Limited, Accenture PLC, SAS Institute, Inc. and Hitachi Vantara LLC (Hitachi Ltd.)
Recent Strategies Deployed in DataOps Platform Market
Partnerships, Collaborations, and Agreements:
May-2023: Wipro partnered with ServiceNow, a software company based in the USA. The partnership aims to provide the joint clients of the two companies with solutions for business transformation. By doing so, the two companies would be able to serve their customers in a better way.
May-2022: Oracle announced a partnership with Informatica, an enterprise cloud data management solutions provider. The partnership integrates Oracle's portfolio with Informatica's portfolio and allows their customers to serve their customers in a better way.
Nov-2021: Amazon Web Services (AWS) teamed up with Goldman Sachs, an investment banking firm to launch Goldman Sachs Financial Cloud for Data. The collaboration allows Amazon Web Services to serve its customers in the financial sector in a better way by providing them with instant analytics in the cloud.
Nov-2021: Amazon Web Services announced a partnership with Accenture, a professional services company. Through this partnership, the two companies aim to provide their joint customers with cloud-based automation solutions through Accenture AWS Business Group (AABG). The partnership allows AWS to serve its customers in a better way by providing them with innovative solutions.
Dec-2020: Amazon Web Services (AWS) entered into a partnership with Alation, a data intelligence solutions provider to integrate their data governance and search solutions with AWS services. The partnership allows the two companies to serve their customers in a better way.
Jun-2020: Microsoft partnered with Hitachi, a Japanese Multinational Corporation, to provide automation solutions for industries in Southeast Asia, Japan, and North America. Through this partnership, Microsoft would be able to serve its customers in a better way by unlocking new opportunities for providing them with solutions.
Product Launches and Product Expansions:
May-2023: IBM announced the launch of the Watsonx Platform. The Watsonx Platform is a data platform used for increasing the effect of AI. The Watsonx Platform features IBM Watsonx.ai used for testing and deploying new AI capabilities, IBM Watsonx.data, a data store used for governed data, and IBM Watsonx.governance, an AI-powered workflow enabler.
May-2023: Hitachi Vantara announced the launch of Data Reliability Engineering (DRE). Data Reliability Engineering (DRE) is a collection of services used for enhancing the uniformity and quality of important business data. Data Reliability Engineering (DRE) features metadata engineering, data cost optimization, AI-powered automation, and data lineage for providing complete transparency and reliability throughout the data lifecycle.
Mar-2023: Teradata introduced Teradata VantageCloud, a cloud-based data analytics platform. The Teradata VantageCloud features Microsoft Azure Machine Learning (Azure ML). The benefits of the product include enhance demand forecast, better risk management, and better patient care.
Mar-2023: Oracle launched Java 20, an upgraded version of Java. Java 20 is used for delivering security, performance, and stability improvements. The new version features Language improvements such as JEP 432 and JEP 433, Incubator features including JEP 429, JEP 436, and JEP 437, and Project Panama preview features including JEP 434 and JEP 438.
Nov-2022: Informatica announced the launch of the Intelligent Data Management Cloud (IDMC) platform. The Intelligent Data Management Cloud (IDMC) platform is used for processing transactions and providing insights for the efficient delivery of services by different governments. The benefits of the Intelligent Data Management Cloud (IDMC) platform include quick reaction for crisis and speedy recovery, Enhanced cybersecurity, and a better digital citizen experience.
Oct-2022: Microsoft announced the launch of ArcBox for DataOps. ArcBox for DataOps is a data-based service used for the automation of deployment of different business operations. The service features Azure Infrastructure and integrations and three Kubernetes clusters.
Mar-2022: Hitachi Vantara announced new capabilities for Lumada DataOps. The new features include Data Catalog used for enhancing business insights and Data Integration used for combining data across a hybrid cloud.
Mar-2021: Informatica unveiled the Spark-based Cloud Data Integration engine, used for boosting performance. The Spark-based Cloud Data Integration engine features NVIDIA infrastructure and RAPIDS data science software. Benefits of the Spark-based Cloud Data Integration engine include cost minimization, enhanced data processing speed, and increased data access throughout the organization.
Dec-2020: Amazon Web Services (AWS) introduced Amazon HealthLake. Amazon HealthLake is a service used for big data analytics in healthcare applications. Amazon HealthLake features interoperability and automated learning for data sorting and identification.
Nov-2019: Accenture announced the launch of myNav. The myNav is a cloud-based platform used for simulating a variety of cloud solutions. The myNav features multiple variable evaluations used for providing correct solutions to organizations.
Sep-2019: IBM added new features to Cloud Pak for Data. The new features include AI-powered global search, Automated metadata generation used for classifying and verifying data, AI-powered risk detection of unstructured data, and enhanced connectivity with InfoSphere Advanced Data Preparation.
Jan-2019: Accenture unveiled SynOps. SynOps is an operating engine used for driving business transformation by enhancing data coordination. The SynOps features Combine human and machine intelligence, Work harmony, diverse data analysis, and Accenture Insights Platform.
Acquisition and Mergers:
Mar-2023: Accenture announced the acquisition of Flutura, an industrial AI company based in Bangalore. The acquisition enhances Accenture's industrial AI services for bettering the performance of refineries and plants.
Jul-2022: IBM took over Databand.ai, a data observability provider headquartered in Israel. This acquisition enables IBM to serve its customers in a better way by providing them with a complete portfolio of services for IT in machine learning and data applications.
Jun-2022: Oracle announced the acquisition of Cerner, a healthcare information systems supplier. The acquisition provides Oracle with Cerner's portfolio of services and extends its reach in the healthcare sector by allowing them to provide automation solutions to their customers in the healthcare sector.
Jun-2021: Hitachi Vantara took over Io-Tahoe, a data management solutions provider based in the UK. The acquisition enhances Lumada DataOps Suite by integrating it with Io-Tahoe's AI-powered data management software for driving business transformation. Furthermore, the acquisitions enhance Hitachi Vantara's ability to serve its customers in a better way by providing them with better solutions for business transformation.
Dec-2020: IBM acquired Instana, an organization performance monitoring platform. This acquisition allows IBM to provide its customers with leading AI-enabled automation powers. Furthermore, this acquisition enhances IBM's Watson AIOps offering.
May-2020: Hitachi Vantara acquired Waterline Data, Inc., a data cataloging solutions provider. The acquisition strengthens Hitachi Vantara's DataOps solution and enables the company to serve its customers in a better way by providing them with solutions for managing their data assets in multiple environments.
Market Segments covered in the Report:
By Deployment
By Service Model
By Component
By Vertical
By Geography
Companies Profiled
Unique Offerings from KBV Research
List of Figures