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市場調査レポート
商品コード
1309681
DataOpsプラットフォームの世界市場規模、シェア、産業動向分析レポート:展開別、サービスモデル別、コンポーネント別、業界別、地域別展望、2023年~2030年予測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 |
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DataOpsプラットフォームの世界市場規模、シェア、産業動向分析レポート:展開別、サービスモデル別、コンポーネント別、業界別、地域別展望、2023年~2030年予測 |
出版日: 2023年06月30日
発行: KBV Research
ページ情報: 英文 347 Pages
納期: 即納可能
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DataOpsプラットフォーム市場規模は2030年までに146億米ドルに達すると予測され、予測期間中のCAGRは21.2%の市場成長率で上昇する見込みです。
市場成長要因
データの複雑化と量の増加
組織は、構造化形式や非構造化形式、リアルタイムのデータストリームなど、多くのソースから増え続けるデータに対処しなければならないです。データの量、速度、多様性により、従来のデータ管理技術では追いつくことが難しくなり、データ処理や分析の非効率性、ミス、遅延が頻繁に発生しています。組織は、この複雑さを処理するために必要なツールとテクノロジーを提供するDataOpsプラットフォームの助けを借りて、データを効率的に統合、処理、分析することができます。データ運用のためのプラットフォームは、バッチ処理とリアルタイムのデータストリーミングの両方を可能にします。こうした要因が市場の成長を後押ししています。
クラウドネイティブなDataOpsの採用増加
クラウドネイティブDataOpsは、DataOpsプラットフォーム市場においてまだ比較的新しい開拓であるにもかかわらず、データ運用の近代化を目指す企業が増えるにつれて、急速に他のアプローチを追い越しつつあります。クラウド・コンピューティング・プラットフォーム上でデータ・パイプラインとプロセスを作成し、デプロイすることは、この戦略の基盤です。クラウドネイティブなDataOpsの主な利点の1つはスケーラビリティです。クラウド技術はリソースの迅速な拡張を可能にするため、組織はインフラの制約を気にすることなく大量のデータを管理できます。これにより、さまざまなエンドユーザーによるDataOpsプラットフォームの利用が促進され、市場の拡大が促進されると予測されます。
市場の抑制要因
人材不足がもたらす課題に対処する必要性
より能力の高い専門家の必要性は、市場における最も大きな障害の1つです。DataOpsプラットフォームには、データサイエンス、データエンジニアリング、ソフトウェア開発、運用の専門家が必要です。しかし、これらの特定のスキルを持つ専門家の深刻な不足により、人材格差が発生しています。その結果、企業はDataOpsプラットフォームの設計、実装、保守を行う有能な候補者を見つけるのに苦労しています。さらに、技術開発の急速な速度がこの人材ギャップを悪化させています。その結果、既存のチームメンバーは、DataOpsの手法に慣れるために追加トレーニングや再トレーニングが必要になる可能性があります。
コンポーネントの展望
コンポーネントに基づき、市場はプラットフォームとサービスに区分されます。プラットフォーム・セグメントは、2022年の収益シェアで最大となり、市場を独占しました。このセグメントの成長は、非効率的なデータ生産と処理、ミスや不整合によって引き起こされるデータ品質の低下といった問題に対処するための利用によるものです。同プラットフォームは、データのライフタイム全体を通じて統合・最適化された、データのキュレーション、ガバナンス、管理、プロビジョニングのための俊敏なソフトウェアへのアクセスをサプライチェーンのすべての人に提供します。
サービスモデルの展望
サービスモデルに基づいて、市場はアジャイル開発、DevOps、リーン生産に分けられます。DevOpsセグメントは、2022年の市場で大きな収益シェアを獲得しました。これは、DataOpsがDevOpsツールを使用してデータの洞察を生産用のアウトプットに変換するためです。さらに、リアルタイムモニタリングは、データパイプラインの最適化を支援するこれらの技術の特徴です。さらに、DevOpsの原則は、ユーザーやビジネスチームから提供されたインプットをスムーズに実装するのに役立ちます。従って、DevOpsのこのような特徴は、予測される期間においてセグメントの拡大を急増させると予想されます。
展開の展望
デプロイメントによって、市場はクラウドとオンプレミスに分類されます。クラウドセグメントは、2022年の同市場において最大の収益シェアを占めています。このセグメントの成長は、顧客がインターネット接続があればどこからでもDataOpsプラットフォームにアクセスでき、柔軟性とアクセシビリティが向上するクラウド展開の採用によるものです。企業は、アクセシビリティの向上により、物理的な場所に制約されることなくプラットフォームの機能を活用できるようになっています。
クラウド型の展望
クラウドの種類によって、市場はパブリッククラウド、プライベートクラウド、ハイブリッドクラウドに分けられます。2022年の売上高シェアはパブリッククラウドが最大で、市場をリードしています。これは、クラウドコンピューティングの導入形態として最も普及しているのがパブリッククラウドであるためです。パブリッククラウドでは、プロバイダーがハードウェア、ソフトウェア、その他のサポートインフラを所有・管理します。パブリック・クラウドでは、ユーザーはサービスの対価を支払うだけで、ハードウェアやソフトウェアを購入する必要はないです。パブリック・クラウドではメンテナンスも不要です。さらに、ビジネス・ニーズに合わせてオンデマンドでリソースを利用できるため、ほぼ無限のスケーラビリティを実現できます。
業界別の展望
業界別では、BFSI、ヘルスケア・歯科、小売、製造、政府、IT・通信、エネルギー・ユーティリティ、メディア・エンターテインメント、その他に分類されます。2022年の市場では、IT・通信分野が大きな収益シェアを記録しました。これは、大規模な事業を展開しながら、卓越した差別化された消費者体験を提供するためには、データへの高速かつ安全なアクセスが不可欠だからです。また、通信事業者は、DevOpsデータプラットフォームを導入することで、個人顧客データを保護しながら、クラウド移行などのプロジェクトのために企業データを安全かつ効率的に供給することができます。
地域別展望
地域別に見ると、市場は北米、欧州、アジア太平洋、LAMEAで分析されています。北米地域は、2022年に最大の収益シェアを獲得して市場をリードしました。これは、同地域の盛んなテクノロジー部門と、イノベーションとデジタルトランスフォーメーションへの揺るぎない献身によるものです。北米地域でDataOpsプラットフォームが広く利用されている背景には、イノベーションとデジタルトランスフォーメーションへの揺るぎない注力があります。北米の企業は、イノベーションを促進し、競争力を獲得するための新たな戦略を常に模索しています。
List of Figures
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