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市場調查報告書
商品編碼
1309681
DataOps平台全球市場規模、份額、行業趨勢分析報告:按部署、按服務模式、按組件、按行業、按地區、2023-2030年預測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 平台市場規模預計將達到 146 億美元,預測期內復合年增長率為 21.2%。
市場增長因素
數據複雜性和數量
組織必須處理來自多個來源的不斷增長的數據量,包括結構化和非結構化格式以及實時數據流。 數據的數量、速度和多樣性使得傳統的數據管理技術難以跟上,經常導致數據處理和分析效率低下、錯誤和延遲。 借助 DataOps 平台,組織可以有效地集成、處理和分析數據,該平台提供了處理這種複雜性所需的工具和技術。 數據操作平台支持批處理和實時數據流。 這些因素正在推動市場增長。
越來越多地採用雲端原生 DataOps
雲端原生 DataOps 仍然是 DataOps 平台市場中相對較新的補充,但隨著越來越多的公司尋求實現數據運營現代化,它正在迅速超越其他方法。 在雲端計算平台上創建和部署數據管道和流程是該策略的基礎。 雲端原生 DataOps 的主要優勢之一是可擴展性。 雲端技術可以快速擴展資源,使組織能夠管理大量數據,而無需擔心基礎設施的限制。 預計這將推動各種最終用戶對 DataOps 平台的使用並推動市場擴張。
市場限制
需要解決人才短缺帶來的挑戰
對更多合格專業人員的需求是市場上最大的障礙之一。 DataOps 平台需要數據科學、數據工程、軟件開發和運營方面的專家。 然而,具有這些特定技能的專業人員嚴重短缺,造成了人才缺口。 因此,公司很難找到合格的候選人來設計、實施和維護數據運營平台。 此外,技術的快速發展正在加劇這種人才缺口。 因此,現有團隊成員可能需要額外的培訓或再培訓才能熟悉 DataOps 方法。
組件展望
根據組件,市場分為平台和服務。 平台細分市場在 2022 年以最大的收入份額佔據市場主導地位。 該細分市場的增長是由於它用於解決數據生產和處理效率低下以及由錯誤和不一致引起的數據質量差等問題。 該平台為供應鏈中的每個人提供了敏捷軟件的訪問權限,用於在數據的整個生命週期中進行集成和優化的數據整理、治理、管理和配置。
服務模式前景
根據服務模式,市場分為敏捷開發、DevOps 和精益製造。 DevOps 細分市場將在 2022 年獲得顯著的市場收入份額。 這是因為 DataOps 使用 DevOps 工具將數據洞察轉換為生產就緒的輸出。 此外,實時監控是這些技術的一項功能,有助於優化數據管道。 此外,DevOps 原則有助於順利實施用戶和業務團隊提供的輸入。 因此,DevOps 的這些特徵預計將在預測期內大幅擴展該領域。
發展前景
根據部署,市場分為雲端和本地。 2022 年,雲端細分市場將佔據市場最大的收入份額。 該細分市場的增長得益於雲端部署的採用,它允許客戶通過互聯網連接從任何地方訪問 DataOps 平台,從而提高了靈活性和可訪問性。 增加的可訪問性使企業能夠利用平台功能,而不受物理位置的限制。
雲端前景
按雲端類型,市場分為公有雲端、私有雲端和混合雲端。 公共雲端將在 2022 年佔據最大的銷售份額並引領市場。 這是因為公共雲端是最流行的雲端計算實施形式。 在公共雲端中,提供商擁有並管理硬件、軟件和其他支持基礎設施。 使用公共雲端,用戶只需為服務付費,而不是硬件或軟件。 公共雲端也不需要維護。 此外,資源可按需提供以滿足業務需求,從而實現近乎無限的可擴展性。
行業展望
按行業劃分,可分為 BFSI、醫療保健和牙科、零售、製造、政府、IT 和電信、能源和公用事業、媒體和娛樂等。 在2022年的市場中,IT和電信行業將佔據較大的收入份額。 這是因為快速、安全地訪問數據對於在大規模運營的同時提供卓越且差異化的消費者體驗至關重要。 通過部署DevOps數據平台,運營商還可以保護個人客戶數據,同時安全高效地為雲端遷移等項目提供企業數據。
區域展望
按地區劃分,我們對北美、歐洲、亞太地區和拉美地區 (LAMEA) 的市場進行了分析。 北美地區將在 2022 年以最大的收入份額引領市場。 這是由於該地區蓬勃發展的技術行業以及對創新和數字化轉型的堅定不移的奉獻。 DataOps 平台在北美的廣泛採用是由對創新和數字化轉型的堅定關注推動的。 北美公司不斷尋找新的戰略來促進創新並獲得競爭優勢。
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