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                  🔽 Download Matt Aslett's Media Kit

                  About Matt Aslett

                  Director of Research, Data and Analytics

                  Matt leads the expertise for Analytics and Data covering technology that improves the utilization and value of data and analytics across business and IT. His focus areas of expertise and market coverage include analytic data platforms, data governance, data management, data operations, operational data platforms, and streaming data and events. Matt’s specialization is in the operational and analytical use of data and how businesses can modernize their approaches to accelerate the value realization of technology investments in support of hybrid and multi-cloud architecture. Matt has been an industry analyst for more than a decade and has pioneered the coverage of emerging data platforms including NoSQL and NewSQL databases, data lakes, and cloud-based data processing. He is a graduate of Bournemouth University.

                  Matt Aslett's Market Assertions

                  By 2026, more than two-thirds of all data processes will use artificial intelligence and machine learning to accelerate the realization of value from the data. 
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                  Through 2025, the primary concern for more than three-quarters of Chief Data Officers will be governing the reliability, privacy and security of their organization’s data.  
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                  Through 2026, the intersection of security and data sovereignty will require increased investment in technology and expertise to enable the realization of enterprise data-driven agendas. 
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                  Through 2025, high-performance data processing requirements will necessitate vendors' continued focus on specialist data platforms with differentiating operational and analytical capabilities. 
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                  Through 2026, the development of intelligent applications providing personalized experiences will drive demand for data platforms capable of supporting hybrid operational and analytic processing. 
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                  Through 2025, 7 in 10 organizations will be using cloud object stores as the primary persistence store for analytic data platform workloads. 
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                  Through 2026, and despite increased demand for hybrid data processing, more than three-quarters of data platform use cases will have functional requirements that encourage the use of specialized analytic or operational data platforms. 
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                  Through 2025, 8 in 10 organizations will migrate on-premises workloads to cloud data platforms, shifting focus to improving innovation and efficiency rather than maintaining existing systems. 
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                  To satisfy regional regulatory requirements, through 2026, nearly all multinational organizations will invest in local data processing infrastructure and services to mitigate against the risks associated with data transfer. 
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                  By 2026, one-half of organizations will adapt their data management and governance processes, taking a holistic approach to managing and governing data in motion alongside data at rest.
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                  Through 2026, almost all organizations using data catalog products will increase business user access, facilitating self-service data discovery and accelerating data democratization initiatives.
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                  Through 2026, 7 in 10 organizations will invest in organizational and leadership changes, leveraging executive support to accelerate data-driven business culture.
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                  Through 2026, 8 in 10 organizations will increase investment in training and the use of natural language interfaces to accelerate data literacy and facilitate self-service data discovery.
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                  Through 2026, more than three-quarters of organizations will invest in greater experimentation and exploration, utilizing data science to identify new business challenges and opportunities.
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                  Through 2025, 6 in 10 organizations will be engaged in data intelligence initiatives that leverage metadata to understand how, when and where data is used in their organization, and by whom, increasing trust in their data. 
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                  Through 2026, more than one-half of organizations will increase their investment in observability technology to accelerate the value being generated from telemetry data including logs, traces and metrics.
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                  Through 2026, more than one-quarter of organizations will combine business event data with machine-generated telemetry data to provide context and generate additional business value from observability.
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                  Through 2025, three-quarters of organizations utilizing telemetry data will have invested in observability pipelines to improve time to detection and resolution based on machine logs, traces and metrics.
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                  By 2026, three-quarters of organizations will use cloud-based products and services as their primary analytic data platform, making it easier to adopt and scale operations as necessary.
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                  By 2025, three-quarters of organizations will require unstructured data storage and processing capabilities in their data lakes to maximize the value of audio, video and image data. 
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                  By 2025, 8 in 10 current data lake adopters will be investing in data lakehouse architecture to improve the business value generated from the accumulated data. 
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                  Through 2026, data warehouse, data lake and data streaming technologies will converge to create analytic data platforms enabling organizations to collect and analyze all types of operations-generated information.
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                  Through 2026, analytic data platform vendors will continue to incorporate native data management, analytics, and machine learning with their data persistence and processing functionality to accelerate the delivery of actionable insight. 
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                  Through 2026, analytic data platform vendors will continue to evolve their offerings to deliver data processing and analytics across hybrid environments that span on-premises and multiple cloud providers.
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                  By 2026, more than one-half of organizations will adopt specialist real-time analytic data platforms to develop and support data-intensive operational applications.
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                  Through 2026, requirements for high-performance analytics will expedite adoption of data platforms designed to leverage GPUs and in-memory processing for analytics acceleration.
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                  By 2026, three-quarters of data lake users will adopt emerging table formats to support transactional consistency when inserting, updating and deleting data in data lake environments.
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                  Through 2026, analytic data platform vendors will increase their native support for artificial intelligence and machine learning algorithms, functions and tools to enable in-database data science. 
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                  Through 2025, more than one-half of all organizations will continue to utilize multiple data catalog technologies, running the risk of creating silos of information knowledge. 
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                  Through 2025, three-quarters of organizations will use data catalog technologies in order to improve data governance and accelerate data-driven decision-making. 
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                  Through 2025, more than one-half of organizations will continue to use spreadsheets in data governance, jeopardizing the robustness of operational effectiveness.  
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                  Through 2026, data governance functionality will continue to be a significant priority for data platforms vendors to enable self-service data discovery, analytics, and greater business agility. 
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                  Through 2026, regional regulations and cultural attitudes will continue to shape organizational priorities to the adoption of data governance technologies and processes.
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                  By 2026, more than three-quarters of organizations’ data management processes will be enhanced with artificial intelligence and machine learning to increase automation, accuracy, agility and speed. 
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                  By 2025, more than three-quarters of organizations’ information architectures will support ELT (extract, load, transform) patterns to accelerate data processing and maximize the value of large volumes of data. 
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                  By 2026, three-quarters of organizations will adopt data engineering processes that span data integration, transformation and preparation producing repeatable data pipelines that create more agile information architectures. 
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                  By 2025, more than three-quarters of enterprises will have data spread across multiple cloud providers and on-premises data centers, requiring investment in data management products that span multiple locations. 
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                  Through 2025, 7 in 10 organizations will be engaged in data integrity initiatives to increase trust in their data processes using data quality and master data management tools. 
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                  By 2026, more than one-half of organizations will adopt data orchestration technologies to automate and coordinate data workflows and increase efficiency and agility in data and analytics projects.
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                  By 2025, more than 6 in 10 organizations will adopt data fabric technologies to facilitate the management and processing of data across multiple data platforms and cloud environments.
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                  Through 2026, data management and analytic data platform vendors accelerate the delivery of native MLOps and AI governance functionality to better support the deployment, monitoring and management of AI and ML models.
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                  By 2026, three-quarters of organizations will use data virtualization and query federation capabilities to avoid data movement while accessing and querying data outside their primary analytic data platform.
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                  By 2025, one-half of organizations will have adopted a DataOps approach to their data engineering processes enabling them to be more flexible and agile. 
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                  Through 2025, awareness of DataOps will continue to increase as organizations adapt their data integration and engineering processes to the growing need for continuous and automated data ingestion, transformation, and delivery. 
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                  Through 2025, data observability will continue to be a priority for the evolution of data operations products as vendors deliver more automated approaches to data engineering and improving trust in enterprise data.
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                  Through 2026, approaches to data operations will continue to evolve as organizations adapt their approaches to data management and data governance to reflect increased adoption of event-driven architecture and microservices. 
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                  Through 2025, 6 in 10 organizations will invest in data reliability initiatives to improve trust in data through automated data quality monitoring, alerts and resolution.
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                  By 2026, more than one-half of organizations will adopt technologies to facilitate the delivery of data as a product as they adapt their cultural and organizational approaches to data ownership in the context of data mesh. 
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                  Through 2025, one-quarter of existing operational database workloads will remain on-premises due in part to security, data sovereignty, and performance reasons, requiring enterprises to explore long-term approaches to hybrid cloud. 
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                  Through 2025, two-thirds of organizations will re-examine their current operational database suppliers with a view to improving fault tolerance and supporting the development of new intelligent operational applications.
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                  Through 2026, emerging relational and non-relational database providers will primarily be adopted for new applications with incumbent relational database vendors deployed for the majority of existing operational workloads.
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                  Through 2026, operational data platform providers will continue to invest in hybrid operational and analytic processing capabilities to support growing demand for data-intensive intelligent operational applications. 
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                  Through 2026, operational data platform vendors will continue to evolve their offerings to deliver data processing across hybrid environments that span on-premises and multiple cloud providers.
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                  By 2026, more than one-half of organizations will adopt serverless databases to support development and test environments as well as ephemeral workloads with sporadic usage requirements.
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                  By 2026, more than one-quarter of organizations will adopt graph databases to support applications that rely on the identification and navigation of relationships.
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                  By 2026, more than one-half of organizations will adopt document databases to store data without fixed schema, facilitating rapid and application development and business agility.
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                  By 2026, more than one-quarter of organizations will adopt data platforms that span distributed architecture, supporting applications that require data processing across geographic and availability zones. 
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                  By 2025, more than 7 in 10 organizations’ standard information architectures will include streaming data and event processing allowing organizations to be more responsive and provide better customer experiences.
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                  By 2025, 6 in 10 organizations will require streaming and event data processes with low latency of seconds or sub-seconds to satisfy operational requirements.
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                  Through 2025 data platform and data management vendors will continue to prioritize support for data streaming and event processing functionality as they adapt their products to address the growing demand for real-time data processing. 
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                  By 2026, more than one-half of organizations will investigate the use of streaming database products to develop and support real-time applications based on streaming data and events.
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                  By 2026, more than one-half of organizations will invest in functionality to discover, catalog, monitor and govern events and event flows to generate greater business value from event-driven architecture.
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                  Through 2025, one-quarter of organizations will deem their blockchain technology skills as ineffective, requiring immediate talent acquisition to adopt and maintain across finance and operational supply chains.
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                  By 2025, one-third of organizations will adopt blockchain for secure distributed computing across business processes to realize efficient and effective governance of digital business.
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                  Through 2025, one-half of organizations will lack the competencies and skills to use blockchain across entities and business processes, leading to ineffectiveness. 
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                  Through 2025 data platform and management vendors will reassess their investments in general purpose blockchain products to focus on industry-specific adoption drivers and use-cases. 
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                  Through 2025, one-third of organizations will reevaluate the potential for adopting blockchain based on improvements related to scalability, security and energy consumption.
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                  Matt Aslett's Industry Assertions

                  Matt Aslett's Perspectives