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Browse our extensive library of research reports, research-based content, and blogs for actionable data and expert analysis of the latest B2B technology trends, market dynamics, and business opportunities.

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Data Management, Analytics & AI

  • Data Platforms: The Path to Achieving Data-driven Empowerment

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    Stephen Catanzano

    Research Objectives

    To assess the current and future landscape for data platforms, including supportive technologies and processes, Enterprise Strategy Group surveyed 354 IT professionals in North America (US and Canada) involved with decisions for data and analytics, modern tooling, data technologies, and data-centric processes in their organization. 

    This study sought to answer the following questions:

    • How many tools or services do organizations leverage across all stages of their data platforms, from initial data collection to data visualization?
    • What are the key drivers behind modern data platform strategies?
    • Which areas of data platforms are most important? Which are most challenging?
    • How effective is the interoperability between different vendors contributing to data platform components?
    • What is the average delivery time for getting decision-making data to stakeholders? How will this change over the next 24 months?
    • How effectively are organizations delivering the right data to the right users at the right time?
    • What role do cloud services play in supporting modern data platform strategies? What are the drivers behind the use of cloud services for these platforms?
    • Who are the data stakeholders in organizations? To what extent is the number of data stakeholders growing?
    • From how many sources do organizations collect data to support their modern data platform initiatives? What types of data sources are used?
    • What are the most important expected outcomes from implementing data integration tools or services?
    • What types of data repositories are organizations currently using to store data for analysis and processing? What types of data repositories will they be using in 24 months?
    • What is the current and future adoption status for data organization tools and services such as data preparation, quality assurance, orchestration, classification, and cataloging?
    • What is the current and future data analysis and visualization tool adoption status?
    • How does data analysis impact organizations’ decision-making abilities or competitive advantage?
    • How will spending on data platform technologies change over the 12 months? Which technologies will represent the most significant investments? 

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  • Data Protection

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    Data protection is evolving to adjust to new IT infrastructure driven by digital transformation, cyber threats, legal mandates, and the risk of data loss.

    Data protection software and services are essential for preventing downtime, ensuring IT continuity, and facilitating system and data recovery. They are also crucial in the fight against ransomware.

    Enterprise Strategy Group’s Data Protection analysts and demand-side research cover the technologies and services available, both in the data center and in the cloud, including:

    • Backup
    • Business continuity/Disaster recovery
    • Cloud data protection
    • Compliance
    • Cyber resilience/Ransomware
    • Data privacy regulations
    • Data protection
    • Data replication
    • DRaaS
    • E-discovery
    • Intelligent data management

    Research Brief

    How Commercial Discovery and Classification Tools Can Ease Data Resilience Skill Shortage Impacts

    While even the best-resourced IT organization can perpetually feel like they need more help on hand to contend with the intense cybersecurity threat landscape, some organizations are solving the situation by deploying third-party tools to supersede internally developed tools. Internal resource constraints are forcing firms to find novel ways of stretching thin pools of expertise […]

    Read More

    Analysts Covering Data Protection

    Jon Brown

    Senior Analyst, Data Protection, Ops & Sustainability

    Areas of Expertise

    • AIOps
    • Backup
    • Business Continuity/Disaster Recovery
    • Data Protection
    • DRaaS
    • FinOps

    Read more

    Recent Data Protection Insights

    Research Brief | March 26, 2025

    IBM Announces IBM Storage Ceph as a Service

    Scott Sinclair

    Cloud & IT Operations

    Research Brief | February 28, 2025

    HPE ProLiant Compute Gen12 Enhances Security and Efficiency for the AI Era

    Scott Sinclair

    Cloud & IT Operations

    Research Brief | February 25, 2025

    Cloud Business Resilience With Commvault Cloud Rewind

    Scott Sinclair

    Cloud & IT Operations

    Research Brief | February 25, 2025

    IT Complexity Drives Increased 2025 Spending in Targeted Areas

    Scott Sinclair
    Emily Marsh
    Christian Perry

    Infrastructure

  • Data Platforms

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    Digital transformation and digitizing data have brought things like data governance, stewardship, observability, and ITOps into the spotlight.

    High-quality data is a prerequisite for reliable and trusted analytics and AI results. Analytics initiatives won’t pay off as expected unless the underlying data is aligned with them.

    Enterprise Strategy Group’s Data Platforms analysts and demand-side research cover every aspect of an organization’s data platform strategy and technology framework, including:

    • Data collection
    • Data integration
    • Data management
    • Data observability
    • Data platforms
    • Data preparation
    • Data quality
    • Data search/log
    • Data streaming
    • Data transformation
    • Data virtualization
    • Data warehousing
    • Databases
    • DataOps & data mesh

    Research Report

    Rethinking Database Requirements in the Age of AI

    The growing use of GenAI is changing how businesses manage operations and make decisions. Databases are becoming the core infrastructure of AI-based projects, providing the foundation for use cases that require efficiency and accuracy. It’s now a necessity to use cutting-edge tools such as vector and RAG for processing AI data, and organizations are seeking […]

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    Analysts Covering Data Platforms

    Stephen Catanzano

    Senior Analyst, Data Management

    Areas of Expertise

    • AI Tools for Data
    • Data Foundations for AI
    • Data Lakes & Warehouses
    • Data Management
    • Data Observability
    • Data Platforms

    Read more

    Recent Data Management Insights

    Research Brief | July 14, 2025

    Organizations Struggle to Manage Data Loss Prevention (DLP) Alert Noise

    Todd Thiemann
    Emily Marsh
    Bill Lundell

    Cybersecurity

    Research Brief | July 14, 2025

    Data Classification Must Be a Cornerstone of Enterprise DLP Strategies

    Todd Thiemann
    Emily Marsh
    Bill Lundell

    Cybersecurity

    Research Brief | April 30, 2025

    Industries Vary Navigation Routes Through Data Readiness Requirements

    Stephen Catanzano
    Emily Marsh
    Christian Perry

    Data Analytics & Artificial Intelligence

    Research Brief | April 25, 2025

    Data Complexity Inhibits Large Midmarket Organizations Along Their AI Journey

    Stephen Catanzano
    Emily Marsh
    Christian Perry

    Data Management

  • Data Analytics & Artificial Intelligence

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    Companies must quickly, easily, reliably, and securely process, merge, transform, and transact with data to derive value and insights at the speed of business.

    Organizations must improve data management efficiency to effectively leverage their data.

    According to our latest spending intentions research, AI, data science and machine learning ranks 2nd among broad IT initiatives that have become significantly more important to organizations’ futures over the past two years. ESG Data Analytics & AI analysts and demand-side research help tech vendors succeed in this rapidly evolving market by covering essential topics that include:

    • Analytics
    • Artificial intelligence hardware
    • BI & data visualization
    • Data platforms
    • Data science & machine learning platforms
    • Databases, warehouses, lakes & platforms
    • DataOps & MLOps
    • Generative AI
    • Speech, NLP & computer vision

    Research Brief

    Data Complexity Inhibits Large Midmarket Organizations Along Their AI Journey

    Although teams across industries are eager to unlock the potential of AI within their businesses and operations, they regularly run into roadblocks in integration complexity, data source utilization, and data quality and trust. Recent research by Enterprise Strategy Group, now part of Omdia, revealed that some of these issues might be correlated to organizational size […]

    Read More

    Analysts Covering Data Analytics & Artificial Intelligence

    Mark Beccue

    Principal Analyst, Artificial Intelligence

    Areas of Expertise

    • AI Development Platforms & Tools
    • AI Lifecycle Management
    • AI Risk Management
    • Foundation Models/LLMs
    • Legacy and Generative AI
    • Natural Language AI

    Read more

    Mike Leone

    Practice Director, Data Management, Analytics & AI

    Areas of Expertise

    • Analytics
    • Artificial Intelligence (AI)
    • BI & Data Visualization
    • Data Platforms
    • Data Science/Machine Learning
    • Data/AI Lifecycle

    Read more

    Recent Data Analytics & Artificial Intelligence Insights

    Research Brief | July 14, 2025

    Organizations Struggle to Manage Data Loss Prevention (DLP) Alert Noise

    Todd Thiemann
    Emily Marsh
    Bill Lundell

    Cybersecurity

    Research Brief | July 14, 2025

    Data Classification Must Be a Cornerstone of Enterprise DLP Strategies

    Todd Thiemann
    Emily Marsh
    Bill Lundell

    Cybersecurity

    Research Brief | July 8, 2025

    Databricks Unity Catalog Establishes Trust and Control Over Your Data

    Stephen Catanzano

    Data Analytics & Artificial Intelligence

    Research Brief | June 30, 2025

    Zscaler Showcases Innovation With Contextual Analysis and AI-driven Remediation at Zenith Live

    Tyler Shields

    Cybersecurity

  • Oracle X10M Delivers High Performance with Triple Query Speed, Making it Ideal for AI and Analytics Workloads

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    Stephen Catanzano

    In today’s data-driven world, the power of artificial intelligence (AI) and advanced analytics is undeniable. They have the potential to revolutionize industries, drive innovation, and unlock valuable insights. However, behind every successful AI and analytics initiative lies a crucial foundation: excellent data management capabilities.

    In a recent research survey from TechTarget’s Enterprise Strategy Group, Data Platforms: The Path to Achieving Data-driven Empowerment, when they were asked about the most important areas of their data platform, 31% of organizations ranked data management, including databases, at the top. In the same survey, 50% of participants identified faster business decision-making as the leading driver and goal for their modern data platform strategies, with 19% focused on creating competitive advantage. Database performance is critical to reaching the data-driven outcomes desired by organizations.

    Oracle has introduced its latest addition to the Exadata database machine family, the Exadata X10M, which is powered by AMD’s EPYC server processors. This release marks a significant milestone for Oracle and its database performance capabilities. The Exadata platform is known for its co-engineered hardware and software, specifically designed to support enterprise data management. It offers a complete stack system with optimized processors, memory, and storage, as well as system software for efficient data storage, indexing, and movement. With the Exadata X10M, Oracle continues its commitment to delivering high-performance database servers by leveraging AMD’s EPYC CPUs, incorporating up to 96 multithreaded cores, DDR5 memory, and RDMA over Converged Ethernet (RoCE) for low-latency, high-bandwidth connectivity.

    Oracle’s optimization efforts extend beyond hardware to its software stack, ensuring linear scalability and maximum performance across multiple cores. The Exadata X10M stands out with its high performance, surpassing its predecessor, the X9M, in terms of OLTP performance, analytics, and database consolidation. Oracle’s decades-long expertise in both enterprise database software and hardware solutions enables the company to provide a tailored data management platform that combines performance, value, and cost-effectiveness.

    Customers can deploy Exadata on-premises, in the cloud, or as a hybrid solution, benefiting from Oracle’s collaboration with public cloud providers and high-speed interconnectivity options. Overall, Oracle’s focus on innovation and customer-centric solutions positions Exadata X10M as a compelling choice for organizations seeking high performance in their data management and analytics initiatives.

  • Aviv Kaufmann

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  • Bill Lundell

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  • Enterprise Strategy Group

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  • Tony Palmer

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  • Stephen Catanzano

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    About

    Senior Analyst Stephen Catanzano brings more than 20 years of industry experience and deep expertise in data management to his role at Enterprise Strategy Group, where he focuses on how organizations can build a strong data foundation for generative AI and operationalize data at scale to maximize organizational value.

    Alongside his operational roles in larger enterprises, Stephen has successfully created and grown multiple SaaS startups, led M&A transactions, and raised both venture and private equity capital.

    Stephen holds a BS in Finance and Economics from Bentley University in Waltham, Massachusetts.

    Areas of Expertise

    • AI Tools for Data
    • Data Foundations for AI
    • Data Lakes & Warehouses
    • Data Management
    • Data Observability
    • Data Platforms
    • Data Quality and Governance
    • Data Streaming
    • Data Transformation
    • Data Visualization
    • Databases
    • DataOps

    Connect with Stephen Catanzano

    Request Briefing

    Quoation Mark

    Maximizing the value of data is about building data-driven organizations by turning data at scale into intelligence for faster corporate and consumer decision-making, quicker innovations, competitive advantages, and achieving operational efficiencies.”

    Stephen Catanzano
    Senior Analyst, Data Management
    Vertical Pills

    Survey Results

    Data Governance in the Age of AI

    This Complete Survey Results presentation focuses on data user trends, data classification and lineage, drivers behind data governance strategies, challenges with data governance adoption, the impact of AI on data governance, the importance of data governance elements, and investment plans. Already an Enterprise Strategy Group client? Log in to read the full report. If you are […]

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    Stephen Has Appeared In

    Latest Insights from Stephen

    Research Brief | July 8, 2025

    Databricks Unity Catalog Establishes Trust and Control Over Your Data

    Stephen Catanzano

    Data Analytics & Artificial Intelligence

    Video | July 7, 2025

    Data Readiness for Impactful Generative AI

    Stephen Catanzano

    Video | July 7, 2025

    Rethinking Database Requirements in the Age of AI

    Stephen Catanzano

    Research Brief | May 30, 2025

    Glean Empowers Enterprises to Deliver AI Agents at Scale, Built on Their Existing Data Foundation

    Stephen Catanzano

    Data Analytics & Artificial Intelligence

    See Stephen’s Content on TechTarget

  • Mike Leone

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    About

    Principal Analyst Mike Leone leads ESG’s analyst team focused on data management, analytics and artificial intelligence.

    Mike draws upon his enthusiasm for bleeding-edge technology and his engineering and marketing background to provide a unique perspective to enterprise technology vendors. At Enterprise Strategy Group, Mike focuses on all things data, analytics, and AI. His passion shines through in helping organizations improve everything from go-to-market strategies and messaging to product development and content creation.

    Mike has a strong technical background, with early roles in software and hardware engineering focused on future product feasibility, modeling, and performance. He gradually moved into roles that interfaced with marketing by helping translate deep technical concepts into understandable business benefits.

    Mike holds a BS in Computer Science from Stonehill College in Easton, Massachusetts.

    Areas of Expertise

    • Analytics
    • Artificial Intelligence (AI)
    • BI & Data Visualization
    • Data Platforms
    • Data Science/Machine Learning
    • Data/AI Lifecycle
    • Databases, Warehouses, Lakes & Platforms
    • DataOps/MLOps
    • Generative AI

    Connect with Mike Leone

    Request Briefing

    Quoation Mark

    While data has the power to transform the business in radical ways, achieving data excellence requires an equal balance of tightly integrated technology, well-defined processes, and the empowerment of all stakeholders to confidently bring the right data to every decision.”

    Mike Leone
    Practice Director, Data Management, Analytics & AI
    Vertical Pills

    Survey Results

    Evaluating the Pillars of Responsible AI

    This Complete Survey Results presentation focuses on responsible AI maturity, prioritization, best practices, terms, outcomes, challenges, responses to issues, bias mitigation, measurements, acceptable fairness levels, data and analytics impact, and stakeholders. Already an Enterprise Strategy Group client? Log in to read the full report. If you are not yet a Subscription Client but would like to […]

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    Mike Has Appeared In

    Latest Insights from Mike

    Video | July 7, 2025

    Evaluating the Pillars of Responsible AI

    Mike Leone

    Video | July 7, 2025

    Navigating the Generative AI Partner and Alliance Landscape

    Mike Leone

    Research Brief | June 30, 2025

    Moving Beyond Conversational Analytics With Qlik’s Agentic Experience

    Mike Leone

    Data Analytics & Artificial Intelligence

    Research Brief | June 12, 2025

    Moving Beyond Conversational Analytics With Qlik’s Agentic Experience

    Mike Leone

    Data Analytics & Artificial Intelligence

    See Mike’s Content on TechTarget

  • Aaron Tan

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    About

    As Enterprise Strategy Group’s regional director of analyst services for APAC, Aaron Tan helps clients identify and quantify key market trends on a wide range of technology topics, including cloud infrastructure, DevOps, business applications, and cybersecurity in the Asia-Pacific region.

    Aaron also serves as Editor in Chief, APAC at ESG’s parent company, TechTarget.

    Aaron is a seasoned media and information professional who has been involved in technology implementations in the public sector and has nearly two decades of experience covering B2B technology for leading media companies. He has held various managerial roles in the Singapore public sector, including the National Library Board of Singapore and the Infocomm Media Development Authority.

    Aaron holds a bachelor’s degree in Communications from Nanyang Technological University Singapore and a master’s degree in Information Science from Syracuse University in Syracuse, New York.

    Areas of Expertise

    • Application Modernization & DevOps
    • Business Applications
    • Cloud Computing
    • Cybersecurity
    • DevOps
    • IaaS/Cloud
    • IoT
    • Networking & 5G
    • Storage

    Connect with Aaron Tan

    Request Briefing

    Quoation Mark

    The growing use of public cloud services in Asia-Pacific has not only drawn cloud suppliers to the region but also integration platform players who provide the glue that ties cloud services together in a multi- cloud and hybrid IT environment.”

    Aaron Tan
    Regional Director Analyst Services, APAC