DataOps Platform Market

DataOps Platform Market - Global

The global DataOps Platform Market size as per revenue was surpassed $3.9 billion in 2023. Throughout the projection period, the DataOps Platform Industry is poised to increase at a CAGR of 23.0% in between 2023 to 2028 to reach around $10.9 billion in 2028.

DataOps is a holistic approach to data management that goes beyond technology and aims to combine agile methodologies, automation, and collaboration across data professionals to improve the quality, speed, and business value of data-related activities. DataOps platform is a transformational shift from traditional DevOps that aims to enhance communication, integration, and automation of data flow between data providers and data consumers.

DataOps Platform Market Technology Roadmap till 2030

DataOps platform market report covers technology roadmap till 2030, with insights around short-term, mid-term, and long-term developments.

Short-term roadmap (2023-2025)

• An increase in the adoption of DataOps platforms is expected across diverse industries and verticals.
• As more organizations migrate their data operations to the cloud, DataOps platforms are expected to incorporate cloud-native solutions.
• Automation and AI/ML will be the key focus areas for DataOps platform capabilities.

Mid-term roadmap (2026-2028)

• As organizations increasingly rely on real-time data for decision-making, DataOps platforms are expected to offer efficient real-time data processing and analytics.
• Emphasis on developing DataOps platform with automated data privacy and security management functionalities.

Long-term roadmap (2029-2030)

• As AI becomes prevalent across industries, AI governance will form a key enabler of DataOps platform adoption.
• With the rise of metaverse, the deployment of DataOps platform will enable efficient data processing and management in virtual environments.

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DataOps Platform Market Dynamics

Driver: Increased data complexity and accelerating data volumes

Organizations are dealing with ever-increasing data complexity, including large volumes of data from diverse sources, structured and unstructured data formats, and real-time data streams. Traditional data management approaches often struggle to keep up with the scale, velocity, and diversity of data, leading to inefficiencies, errors, and delays in data processing and analysis. DataOps platforms offer the necessary tools and technologies to handle this complexity and enable organizations to integrate, process, and analyse data efficiently. DataOps platforms can support batch processing as well as real-time data streaming data. These platforms are often integrated with big data technologies and cloud-based infrastructure to handle large-scale data processing. The volume of data being generated is growing exponentially, with the proliferation of digital technologies, IoT devices, social media, and other data sources. DataOps platforms provide scalable infrastructure and distributed computing capabilities that can handle massive data volumes and ensure optimal performance. Hence, organizations are turning to DataOps to gain better control over their data, improve data quality and governance, and enhance the efficiency and agility of their data operations.

Restraint: Data privacy and security concerns

Organizations are increasingly aware of the importance of protecting sensitive data and complying with data privacy regulations. DataOps platforms deal with sensitive and confidential data. Ensuring data privacy and compliance with regulations (such as GDPR or CCPA) and maintaining strong security measures can be a significant challenge. Organizations need to address these concerns and implement robust security frameworks. DataOps platforms rely on the integration of various tools and systems, which can increase the attack surface and potential vulnerabilities. Organizations may worry about the risk of data breaches and the potential impact on data privacy if the DataOps platform is not adequately secured.

Opportunity: Need to bridge gap between data engineers and data analysts

DataOps emerged also as a way to bridge the gap between data engineers and data analysts, who have different priorities and objectives. DataOps platforms foster collaboration and cross-functional alignment among different teams, including data engineers, data scientists, business analysts, and IT operations involved in data operations. DataOps platforms enable seamless collaboration, knowledge sharing, and consistent practices across teams, leading to improved productivity and outcomes by providing shared tools and workflows. Furthermore, DataOps platforms break down barriers between teams, encourage knowledge sharing, and enhance the overall effectiveness and efficiency of data operations by fostering collaboration and cross-functional alignment. This collaborative environment enables organizations to harness the collective expertise of their teams, drive innovation, and deliver high-quality data-driven insights.

Challenge: Need to mitigate the challenges of skilled talent shortage

 One of the main challenges faced in the DataOps platform market is the scarcity of highly skilled professionals. DataOps platforms require individuals with extensive knowledge in data engineering, data science, software development, and operations. However, the industry is currently experiencing a significant shortage of professionals with these specific skills, resulting in a talent gap. Consequently, organizations are encountering difficulties in finding suitable candidates to build, implement, and sustain DataOps platforms. This shortage of skilled talent is further exacerbated by the rapid pace of technological advancements. Existing team members may need additional training or retraining to adapt to the DataOps approach. Additionally, the lack of skilled talent is not limited to data scientists and machine learning engineers alone. DataOps platforms also require individuals specializing in areas such as data management, data visualization, and cloud computing. It is essential for organizations to address these skill gaps through initiatives that encompass training, recruitment, and knowledge sharing. These efforts are crucial for ensuring the successful adoption and implementation of DataOps platforms.

By offering, platform segment to account for the largest market size during the forecast period

Based on offerings DataOps platform market has been segmented into platform and services. DataOps platform and services are designed to streamline data management and analysis processes, allowing organizations to make more informed decisions and improve operational efficiency period. The platform segment is estimated to account for a larger market size during the forecast period. The increasing amount of data organizations need to manage, process, and analyze offers key lucrative opportunities to the DataOps platform market.

By deployment, cloud to account for the largest market size during the forecast period

The DataOps platform market has been segmented based on deployment mode into cloud and on-premises. In the DataOps platform market, deployment mode plays a significant role in setting up the required IT infrastructure for managing the IT ecosystem. It can either be on-premises or in the cloud, depending on the specific needs of a business. The ability to have greater control over data location and accessibility across a network is driving the adoption of cloud deployment mode in the DataOps platform market.

By type, agile development segment to account for the largest market size during the forecast period

The DataOps platform market has been segmented based on type into Agile Development, DevOps, Lean Manufacturing. DataOps combines Agile development, DevOps, and lean manufacturing principles to streamline the development and operation of data analytics. Agile development is a core principle of the DataOps platform, which emphasizes the importance of flexibility and rapid response to changing business needs. The need to adapt quickly changing requirements and market conditions drives the demand for agile development in DataOps platform.

North America to account for the largest market size during the forecast period

North America has emerged as a frontrunner in adopting DataOps platforms, driven by its flourishing technology industry and a steadfast commitment to innovation and digital transformation. The region encompasses major countries such as the United States and Canada, with the United States leading the adoption of DataOps due to the presence of numerous world-renowned technology companies. The key driver behind the widespread adoption of DataOps platforms in North America lies in the region's unwavering emphasis on innovation and digital transformation. North American businesses are continuously seeking novel approaches to foster innovation and gain a competitive edge, recognizing the potent capabilities of DataOps platforms in managing and analyzing data to extract insights that drive growth and spur innovation. Additionally, the thriving technology industry in North America plays a pivotal role in propelling the adoption of DataOps platforms. With many global technology giants headquartered in the region, substantial investments are being made in data infrastructure and analytics capabilities, reinforcing the momentum of DataOps platforms, and enabling businesses to effectively harness the power of data.

Top DataOps Platform Market Companies

Key players operating in the DataOps platform market across the globe are Microsoft (US), IBM (US), Oracle (US), AWS (US), Informatica (US), Teradata (US), Wipro (India), Accenture (Ireland), SAS Institute (US), Hitachi Vantara (US), DataKitchen (US),  Atlan (Singapore), Dataiku (US), Fosfor (India), Databricks (US), StreamSets (US), Talend (US), Collibra (US), Celonis (US),  BMC Software (US), Saagie (France), Composable Analytics (US), Tengu.io (Belgium), Unravel Data (US), Monte Carlo Data (US), Census (US), RightData (US), Zaloni (US), Datafold (US), DataOps.live (UK), and K2view (Israel). These DataOps platform vendors have adopted various organic and inorganic strategies to sustain their positions and increase their market shares in the global market.

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Scope of the Report

This research report categorizes the DataOps platform market based on offering, type, deployment mode, vertical, and region.

By Component:

• Platform
  • Data Integration
  • Data Quality
  • Data Governance
  • Master Data Management
  • Data Analytics
  • Automation
  • Collaboration
  • Data Visualization
  • Others
• Services
  • Consulting Services
  • Deployment & integration
  • Training, support & maintenance services

By Type:

• Agile Development
• DevOps
• Lean Manufacturing

By Deployment Mode:

• Cloud
  • Public
  • Private
  • Hybrid
• On-premises

By Vertical:

• BFSI
• Healthcare & life sciences
• Retail & eCommerce
• Manufacturing
• Government and Defense
• Telecommunications
• Transportation, and Logistics
• IT & ITeS
• Media and Entertainment
• Other Verticals

By Region:

• North America
  • US
  • Canada
• Europe
  • UK
  • Germany
  • France
  • Italy
  • Spain
  • Rest of Europe
• Asia Pacific
  • China
  • Japan
  • ASEAN
  • Australia and New Zealand
  • India
  • South Korea
  • Rest of Asia Pacific
• Middle East & Africa
  • UAE
  • Saudi Arabia
  • Israel
  • South Africa
  • Rest of the Middle East & Africa
• Latin America
  • Brazil
  • Mexico
  • Argentina
  • Rest of Latin America

Recent Developments:

• In April 2023, DataOps.live partnered with AWS and joined the AWS Partner Network on the Software Path and obtained the AWS Qualified Software Certification after successfully completing the AWS Foundational Technical Review.
• In March 2023, Blechwarenfabrik Limburg GmbH collaborated with Hitachi Vantara and adopted its Lumada DataOps Platform which includes Pentaho, to achieve real-time, standardized, integrated data analysis for increased sustainability and accelerated production.
• In February 2023, Informatica announced the launch of Cloud Data Integration-Free and PayGo, which is the only free cloud data loading, integration, and ETL/ELT service. This new service targets data practitioners and non-technical users such as in marketing, sales, and revenue operations teams to build data pipelines within minutes.
• In November 2022, Wipro had announced the launch of Data Intelligence Suite speeding up the cloud modernization and data monetization, focused on modernizing data estates, including data stores, pipelines, and visualizations, running on Amazon Web Services. It also provides a dependable and safe way to migrate from existing platforms and fragmented legacy systems to the cloud.
• In June 2022, Teradata announced the general availability and integration of the Teradata Vantage multi-cloud data and analytics platform with Amazon SageMaker. It enables organizations to widely employ advanced analytics to fully leverage their data.

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