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More Than Half of Enterprises Will Embrace DataOps by 2026

The expanding use of AI is driving enterprise interest in data operations (DataOps) to orchestrate data integration and processing and improve data quality and validity, according to a new report from Information Services Group (ISG).

The ISG Buyers Guides for DataOps, produced by ISG Software Research, predict more than half of enterprises will adopt agile and collaborative DataOps practices by the end of 2026 to enhance responsiveness, avoid repetitive tasks and deliver measurable data reliability improvements.

"As enterprise use of AI moves from initial pilots and trial projects through deployment and into production at scale, many enterprises are realizing the critical importance of agile, responsive data processes," said Matt Aslett, Director of Research, Analytics and Data, for ISG Software Research. "DataOps enables enterprises to effectively monitor the quality of data used in analytics and governance projects and ensure the reliability and health of the data environment."

Healthy data pipelines are necessary to ensure data is ingested, processed and loaded in the required sequence to generate business insights and AI, the report says. As data sources and requirements grow increasingly complex, enterprises are looking to automate and coordinate the creation, scheduling and monitoring of data pipelines as part of a DataOps approach to data management.

Such data orchestration automates and accelerates the flow of data to support operational and analytics initiatives and drive business value. By 2027, ISG says more than half of enterprises will adopt data orchestration technologies to automate and coordinate data workflows and increase efficiency and agility in data and analytics projects.

To fully deliver on the promise of DataOps, enterprises must adopt new approaches to people, processes and information, the report says. Processes and methodologies that support rapid innovation and experimentation, automation, collaboration, measurement and monitoring, and high data quality will improve the value generated by analytics and data initiatives.

"Enterprises need to enable data operation activities across business and IT to improve the agility of data scientists and data analysts in their daily work," said Mark Smith, Partner, ISG Software Research. "Orchestrating and managing pipelines of data to streamline the development of AI requires the efficient processing of data and governance of analytical and operational processes."

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More Than Half of Enterprises Will Embrace DataOps by 2026

The expanding use of AI is driving enterprise interest in data operations (DataOps) to orchestrate data integration and processing and improve data quality and validity, according to a new report from Information Services Group (ISG).

The ISG Buyers Guides for DataOps, produced by ISG Software Research, predict more than half of enterprises will adopt agile and collaborative DataOps practices by the end of 2026 to enhance responsiveness, avoid repetitive tasks and deliver measurable data reliability improvements.

"As enterprise use of AI moves from initial pilots and trial projects through deployment and into production at scale, many enterprises are realizing the critical importance of agile, responsive data processes," said Matt Aslett, Director of Research, Analytics and Data, for ISG Software Research. "DataOps enables enterprises to effectively monitor the quality of data used in analytics and governance projects and ensure the reliability and health of the data environment."

Healthy data pipelines are necessary to ensure data is ingested, processed and loaded in the required sequence to generate business insights and AI, the report says. As data sources and requirements grow increasingly complex, enterprises are looking to automate and coordinate the creation, scheduling and monitoring of data pipelines as part of a DataOps approach to data management.

Such data orchestration automates and accelerates the flow of data to support operational and analytics initiatives and drive business value. By 2027, ISG says more than half of enterprises will adopt data orchestration technologies to automate and coordinate data workflows and increase efficiency and agility in data and analytics projects.

To fully deliver on the promise of DataOps, enterprises must adopt new approaches to people, processes and information, the report says. Processes and methodologies that support rapid innovation and experimentation, automation, collaboration, measurement and monitoring, and high data quality will improve the value generated by analytics and data initiatives.

"Enterprises need to enable data operation activities across business and IT to improve the agility of data scientists and data analysts in their daily work," said Mark Smith, Partner, ISG Software Research. "Orchestrating and managing pipelines of data to streamline the development of AI requires the efficient processing of data and governance of analytical and operational processes."

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Businesses that face downtime or outages risk financial and reputational damage, as well as reducing partner, shareholder, and customer trust. One of the major challenges that enterprises face is implementing a robust business continuity plan. What's the solution? The answer may lie in disaster recovery tactics such as truly immutable storage and regular disaster recovery testing ...

IT spending is expected to jump nearly 10% in 2025, and organizations are now facing pressure to manage costs without slowing down critical functions like observability. To meet the challenge, leaders are turning to smarter, more cost effective business strategies. Enter stage right: OpenTelemetry, the missing piece of the puzzle that is no longer just an option but rather a strategic advantage ...

Amidst the threat of cyberhacks and data breaches, companies install several security measures to keep their business safely afloat. These measures aim to protect businesses, employees, and crucial data. Yet, employees perceive them as burdensome. Frustrated with complex logins, slow access, and constant security checks, workers decide to completely bypass all security set-ups ...

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In high-traffic environments, the sheer volume and unpredictable nature of network incidents can quickly overwhelm even the most skilled teams, hindering their ability to react swiftly and effectively, potentially impacting service availability and overall business performance. This is where closed-loop remediation comes into the picture: an IT management concept designed to address the escalating complexity of modern networks ...

In 2025, enterprise workflows are undergoing a seismic shift. Propelled by breakthroughs in generative AI (GenAI), large language models (LLMs), and natural language processing (NLP), a new paradigm is emerging — agentic AI. This technology is not just automating tasks; it's reimagining how organizations make decisions, engage customers, and operate at scale ...

In the early days of the cloud revolution, business leaders perceived cloud services as a means of sidelining IT organizations. IT was too slow, too expensive, or incapable of supporting new technologies. With a team of developers, line of business managers could deploy new applications and services in the cloud. IT has been fighting to retake control ever since. Today, IT is back in the driver's seat, according to new research by Enterprise Management Associates (EMA) ...

In today's fast-paced and increasingly complex network environments, Network Operations Centers (NOCs) are the backbone of ensuring continuous uptime, smooth service delivery, and rapid issue resolution. However, the challenges faced by NOC teams are only growing. In a recent study, 78% state network complexity has grown significantly over the last few years while 84% regularly learn about network issues from users. It is imperative we adopt a new approach to managing today's network experiences ...

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