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Featured Dresner Research

Research Insight and Wisdom of Crowds® reports offer the most comprehensive and objective insights available for data, analytics, and performance management. Our process is global, encompassing thousands of organizations across all industries, functions, and organization sizes.

Special Reports

Specialized reports rely on data collected directly from customers on a subset of vendors to provide an unbiased comparison within the broader market context.

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Hyperscale Data Clouds

The cloud-based analytical data infrastructure (ADI) market has become increasingly dominated by the main Hyperscale vendors: Amazon Web Services (AWS), Google Cloud Platform, and Microsoft Azure. These giants emerged as key players, each offering ADI solutions that cater to the expansive needs of modern enterprises in the digital era.


This special report draws upon data gathered from AWS, Google Cloud, and Microsoft Azure users to provide an impartial comparison of these vendors within the broader market context. We sourced data for this analysis exclusively from customers within the Dresner research community, without reliance on vendors or vendor-provided references.


The report aims to illuminate the competitive dynamics of cloud-based, analytical data infrastructure by evaluating factors such as product offerings, customer satisfaction, and market positioning. Stakeholders can leverage the insights from this report to make well-informed decisions and adeptly manage the complexities of the contemporary data landscape.

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Databricks versus Snowflake 2024

The cloud-based analytical data services industry has seen an emerging competitive dynamic between Snowflake and Databricks in recent years. The two emerge as prominent players offering solutions which have much of the same appeal to meet the evolving demands of organizations in the digital age, including multi-cloud capabilities.


The report seeks to shed light on the competitive landscape of cloud analytical data services by examining factors such as product and technology, customer satisfaction, and competitive market positioning. Stakeholders can utilize insights gained from this analysis to make informed decisions and effectively navigate the complexities of the modern data landscape. background graphic

Research Insights

Published throughout each month, Research Insights are thought leadership articles, covering important topics and issues, with pointed advice and recommendations for readers.

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Rising SI and Consultant Use on BI Projects Means Data Leaders Must Provide the Data and Analytics Guardrails

Our latest data show that use and perceived importance of system integrators (SIs) and consultants continues to rise. Organizations increasingly allocate greater percentages of their data and analytics project budgets to the use of SIs and consultants. In addition, expertise matters most when choosing an SI or consultant. And when sourcing that talent, organizations increasingly consider their vendors as trusted advisors that can direct them to the right potential SI and consultant resources to use.


As perceptions, use, and funding of SIs and consultants continue to rise, so do the stakes for data leaders. Hiring SIs and consultants for an increasing percentage of project responsibilities requires greater expertise in managing the engagements. In some cases, an engagement manager can handle more projects—as long as other less-critical workloads and responsibilities get offloaded easily and efficiently. Sometimes a data leader simply will have to make a business case for hiring more engagement managers. But in almost no instances—even for the most critical projects—should a data leader look to manage these engagements directly.

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Data Mesh and Fabric Confusing? Data Leaders Need to Unpack Next-Gen Data Architectures

Data architectures and their supporting technologies and capabilities (including analytic data infrastructure, and data engineering and data catalog products) face increased technology and business pressure to meet the requirements of more complex, diverse, and distributed business intelligence (BI) and analytics use cases and applications. The scale, distribution, mission-criticality, and pace of change facing data leaders and their teams is outpacing the ability of current architectural approaches. Data architectures that lack flexibility, adaptability, and scalability lead to challenges as organizations struggle to capture benefits and achieve positive returns from their BI investments.


In the face of these challenges, although data leaders realize they need to modernize data architectures to better support BI and analytics needs, they are unclear on how to do so in a game-changing manner. Approaches that continue to emphasize centralization, consolidation, physical data movement, and use-case-specific optimization remain common. Although better extract, transform, and load (ETL) processes and data-warehouse enhancements may yield marginal value gains, they will not create the breakthroughs needed to support the BI needs of the modern, Hyper-Decisive® organization.

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Generative AI Smoke Is Clearing; Data Leaders Need A Game Plan

Our latest data show that between 72-82 percent of organizations use or plan to use generative AI at some point. Although that number is down from the nearly 90 percent rate reported in 4Q23, it still includes a strong majority of organizations. Calling the “bloom off the rose” that is generative AI seems premature. We firmly expect generative AI will continue to have a prominent and critical role among organizations and vendors, and not fizzle out after significant hype (including Google Glass, the Segway, the Pebble smartwatch, and even the Sony Betamax).


Understanding where we are and how we got here requires a look back into the relatively recent past. Remember that generative AI truly emerged into the mainstream consciousness in 1Q23. In that quarter, OpenAI announced a premium subscription model for ChatGPT, released ChatGPT4, an API for application developers, and plugin support, including browsing and code interpreter. Microsoft announced and delivered ChatGPT-powered features for Bing. Anthropic launched Claude, its ChatGPT alternative, as did Google with Bard. background graphic

Wisdom of Crowds® Market Reports

Wisdom of Crowds® Market Reports offer in-depth research and reporting on key industry and technology topics, including user trends, perceptions, intentions and other drivers. Each report includes a section with objective and inclusive vendor ratings.

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Data and Analytics Governance Study 2024

This expanded edition of the Data and Analytics Governance Study Report includes in-depth sections on crucial topics such as the relative importance of governance in technologies and initiatives, the difficulty in finding data and analytic content, and organization and practices related to data and analytic governance.


Furthermore, the report delves into detailed aspects of governance organizational models, structures, and reporting, as well as the scope and activities of data governance programs. It also examines the current use of data governance solutions and their features, industry and vendor analysis, and governance vendor ratings.

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Business Intelligence Flagship Market Study Report 2024

This 15th edition of the Wisdom of Crowds BI Flagship Market Study includes in-depth sections on key topics such as automation goals and targets, user penetration, and objectives and achievements, among others. Furthermore, this year’s report includes an updated industry section that includes a new Value/TCO Model, offering essential insights for organizations navigating the ever-evolving market landscape. As the 15th edition, it provides an unparalleled historical view of the market, reflecting on trends and changes over time.


Data security, data quality, reporting, dashboards, and data integration are the top five technologies and initiatives strategic to business intelligence in 2024, while modern initiatives including data fabric and blockchain gain momentum. Organizations report ongoing and improving penetration levels of business intelligence usage, with high penetration levels increasing and bullish expansion plans.


The 2024 BI Market Study also includes a comprehensive analysis of the leading suppliers, ranking 24 vendors using four different models – a vendor-specific radar chart and three collective models. 

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Self-Service Business Intelligence 2024

The 2024 Self-Service Business Intelligence Market Study, part of our Wisdom of Crowds® series of research, examines end user perception and trends around self-service business intelligence (BI).


Self-service BI builds upon governance, data storytelling, collaborative support, generative AI, and natural language analytics to create an environment where users can easily create and share insights in a managed and consistent fashion.


In 2024, end-user self-service ranks 13th of 63 technologies and initiatives strategic to business intelligence, and fifty-five percent of respondents say self-service BI is critical or very important.


The perceived importance of end-user self-service correlates directly and positively to success with BI in 2024. In addition, the importance of end-user self-service gradually increases with organization size, as organizations seek to standardize and democratize the scale and scope of user constituencies and communities.


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