As part of APMdigest's 2025 Predictions Series, industry experts offer predictions on how DataOps and related technologies will evolve and impact business in 2025. Part 2 covers DataOps roles, Data Observability, Business Intelligence and Analytics.
DATAOPS: THE RACE TO DATA DEMOCRACY
DataOps will shift from niche to necessity as organizations demand faster, more reliable access to data insights. By 2025, companies will compete fiercely to democratize data, as 90% of businesses with strong DataOps initiatives outperform those without in speed to market (IDC, 2023). Data pipelines will transform into "highways" carrying real-time data that fuels rapid, agile decision-making.
Ravi Ithal
GVP and CTO of Proofpoint DSPM, Normalyze
DATA ROLES EVOLVE IN 2025
How learning data will shape the industry: In 2025, data roles will continue to evolve through the next generation of data workers. Previously, those pursuing a data-driven career had to learn the ins and outs of applications and code, which also required foundational domain knowledge. Now, with alternative sources for learning beyond schooling, combined with the automation that comes from AI, more workers across industries and departments can focus without having to spend so much time to learn new software and coding. Now, more time can be spent on the specific job and tasks required. Overall, this is a significant increase in productivity for all data workers. Because of this, the reliance on traditional data scientists with more profound knowledge of the foundations of data is decreasing. This, however, potentially forces organizations to consider if that leaves them open to any blind spots, such as not having teams equipped to face issues with applications coding.
Joshua Burkhow
Chief Evangelist, Alteryx
DATA RELIABILITY ENGINEERS
Secure Data Pipelines with the rise of roles like Data Reliability Engineers: In the last few years, we've seen the rise of roles like Service Reliability Engineers (SREs) who are tasked with automated CI/CD processes to reliably and securely operate enterprise cloud applications — that has been significantly focused on infrastructure-as-code and application automation. In 2025, we'll see enterprises focused on making their data to be "AI-ready" and thus an increased focus on data architectures to reliably and securely operate enterprise data integrations and pipelines. Roles like data reliability engineers (either complementing SREs or expanding scope of SREs) will become essential for any business hoping to delivery resilient and secure AI applications infused with enterprise data.
Nataraj Nagaratnam
IBM Fellow, CTO for Cloud Security, IBM
DBA ROLE CONVERGES WITH DEVELOPMENT
The traditional DBA position will continue to evolve. In 2025, the traditional role of the DBA will continue to fade as companies increasingly integrate operational and analytical database responsibilities. While the core skills of a DBA remain crucial, these tasks will be distributed across development and data teams. Much like how DevOps blended development and operations, the future will see developers taking on more responsibility for how infrastructure decisions impact data processing, interpretation, and long-term performance.
Bennie Grant
COO, Percona
REAL-TIME DATA OBSERVABILITY
Real-time data observability is going to become critical and organizations will need to ensure real-time observability of data in motion. Visibility into dynamic data workflows means teams can continuously optimize data pipelines in the moment. The result is a dramatic enhancement in system responsiveness and overall operational efficiency. Data pipelines don’t just run smoothly, they also evolve in tandem with business requirements.
Somesh Saxena
CEO and Founder, Pantomath
DATA OBSERVABILITY: ON-PREM
Expanding Data Observability to Legacy and On-Premises Systems: As data observability matures, there's a growing need to extend beyond cloud-native environments to encompass legacy and on-premises data systems. Enterprises realize that a full migration to cloud data infrastructure is neither feasible nor desirable in the near term. Data observability tools that adapt to on-premises systems, will play a crucial role in meeting the reality of hybrid data environments, ensuring comprehensive visibility across the entire data
stack.
Egor Gryaznov
Chief Technology Officer, Bigeye
FILLING VISIBILITY GAPS
Filling Visibility Gaps Will Drive GenAI Data Platform Growth: Although the technology for GenAI's data ecosystem exists, deployment remains inconsistent. In 2025, enterprises will focus on filling visibility gaps by enhancing their platforms to support vector data, similarity search, knowledge graphs, and raw data stores. This will require balancing data control with accessibility while integrating GenAI into core systems for better insights and control. As enterprises scale from trials to full deployment, their systems will face new challenges. To unlock GenAI's full potential, platforms must handle massive data ingestion and provide parallelized access to support larger, more complex operations.
Lenley Hensarling
Technical Advisor, Aerospike
DATA-CENTRIC BUSINESS MODEL
By 2025, data will become the central asset driving business value, leading to the rise of data-centric business models. Enterprises will harness advanced data management and analytics platforms to monetize data, improve customer experiences, and create new revenue streams. CIOs will need to prioritize data governance and secure data sharing frameworks to unlock the full potential of data as a strategic asset.
Woody Sessom
Chief Business Officer, Graphiant
REAL-TIME ANALYTICS
Instant Data Gratification: Businesses will prioritize real-time analytics, delivering insights within minutes to keep pace with intensifying customer and market demand and competition. This shift will enable faster decision-making across departments, from marketing to customer service, giving organizations a competitive edge. Real-time data will become essential for companies aiming to act on insights immediately, transforming analytics from an ad hoc, retrospective tool to a proactive business driver.
Justin Borgman
Co-Founder and CEO, Starburst
From Streams to Insights - 2025 Marks the Real-Time Analytics Revolution: Real-time analytics will finally hit its stride as organizations complete the "last mile" of their data architecture. Over the past few years, businesses have focused heavily on building out event streaming systems like Apache Kafka, ensuring that data flows smoothly in real-time. However, many are now realizing that traditional analytic endpoints, such as data warehouses and batch-based solutions, are unable to fully harness the potential of these streams. These legacy systems simply can't deliver the instant insights needed in today's fast-paced environment. In 2025, organizations will prioritize real-time analytics platforms that can process, analyze, and act on data instantly, closing the loop and unlocking the true value of their streaming architectures. This shift will enable innovative use cases such as hyper-personalized customer experiences, real-time external-facing data products, and adaptive risk management systems—far beyond the capabilities of traditional solutions.
Kishore Gopalakrishna
Cofounder and CEO, StarTree
NEW ERA OF BUSINESS INTELLIGENCE
2025 will mark a new era of business intelligence, with more AI and less hands-on intervention: As enthusiasm for AI has surged, we're seeing demand for data and analytics systems to be driven by AI and push the boundaries of innovation and decision-making. In the coming year, AI — particularly with generative capabilities — will play an even larger role, automating insight generation with minimal human input. Business users will be able to access tailored insights and recommendations directly through chatbots and voice interfaces built into their existing data environments. Natural language processing will become the norm, making data and analytics even more accessible to non-technical users.
Trevor Schulze
Chief Digital & Information Officer, Alteryx
In 2025, BI will evolve from traditional reporting to become a central force in strategic decision-making, enabling businesses to anticipate trends and respond to opportunities with accelerated agility. As organizations increasingly prioritize data-driven cultures, the demand for real-time, actionable insights will intensify, making BI an essential tool for gaining a competitive edge. AI-powered analytics will take BI to the next level, allowing for more accurate forecasting and automated decision-making. Additionally, the expansion of self-service BI tools will empower non-technical users to explore and analyze data independently, while embedded analytics will integrate these insights directly into operational systems, ensuring data-driven decisions are seamlessly woven into daily workflows. This shift will not only enhance productivity but also enable organizations to uncover deeper insights from their data, driving innovation and growth."
Casey Ciniello
Reveal and Slingshot Senior Product Manager, Infragistics
DIGITAL BEHAVIOR DATA
Digital behavioral data will be hottest trend in Large Datasets behind GenAI: In 2025, enterprises will increasingly embrace their digital behavioral data to fuel revenue growth. In a landscape where every investment must show measurable impact, digital behavioral data uniquely fills gaps left by traditional analytics, offering richer insights into customer preferences, engagement patterns, and pain points. Collected from user interactions — like website views, newsletter sign-ups, shopping cart actions, and signals of frustration, such as "rage clicks" — this data will empower companies to make more precise, user-focused decisions. I expect we'll see continued innovation in how behavioral data is applied, fundamentally reshaping the ways organizations understand and engage with their audiences.
Scott Voigt
CEO and Founder, Fullstory
