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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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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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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.

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Why Data Leaders Need to Care About Active Data Architecture™

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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Criticality of MDM to Data Leadership

Master data management (MDM) represents a perennial issue for many organizations that want to establish and maintain a common frame of reference (some use the phrase “single source of truth”) within key organizational data and analytics. For many and for too long, many business leaders view MDM as an “IT thing,” allowing and enabling pursuit of master data objectives in the absence of explicit connection to business value chains and business processes.


In all instances, achieving high quality, high confidence, and ultimately high trust in the most critical data for organizations—customers, products, vendors, charts of account, and similar—is foundational. Master data domains are the “nouns” around which business value chains are organized. 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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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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Collective Insights 2024

Collective Insights® builds upon our definition of Collaborative Business Intelligence and
adds user governance to the mix.


Collaborative Business Intelligence is a process where two or more people or organizations work together to develop a common understanding, which is shared and used to build consensus in support of organizational decision making.


User governance enhances the collaborative BI environment with facilities for directing content creation and sharing, thus improving information consistency and accelerating group-based decision making.

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Guided Analytics 2024

Guided Analytics® improves time to insight and action by supporting the creation of connections between related and relevant information and directing and suggesting analytical story flow. It is an important topic for organizations seeking to better leverage both information resources and scarce human experts to drive improved group-based decision-making in a governed fashion.


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