David Menninger's Analyst Perspectives

About the Analyst

David Menninger

David is responsible for the overall research direction of data, information and analytics technologies at Ventana Research covering major areas including Analytics, Big Data, Business Intelligence and Information Management along with the additional specific research categories including Information Applications, IT Performance Management, Location Intelligence, Operational Intelligence and IoT, and Data Science. David is also responsible for examining the role of cloud computing, collaboration and mobile technologies as they affect these areas. David brings to Ventana Research over twenty-five years of experience, through which he has marketed and brought to market some of the leading edge technologies for helping organizations analyze data to support a range of action-taking and decision-making processes. Prior to joining Ventana Research, David was the Head of Business Development & Strategy at Pivotal a division of EMC, VP of Marketing and Product Management at Vertica Systems, VP of Marketing and Product Management at Oracle, Applix, InforSense and IRI Software. David earned his MS in Business from Bentley University and a BS in Economics from University of Pennsylvania.


Recent Posts

Cloud Computing Realities Part 2: Hybrid and Multi-Cloud Architectures

Posted by David Menninger on Sep 27, 2022 3:00:00 AM

In my first perspective on cloud computing realities, I covered some of the cost considerations associated with cloud computing and how the cloud costing model may be different enough from on-premises models that some organizations are taken by surprise. In this perspective. I’d like to focus on realities of hybrid and multi-cloud deployments.

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Topics: Cloud Computing, Digital Technology

Enhancing Data Catalog with AI

Posted by David Menninger on Sep 22, 2022 3:00:00 AM

Organizations are collecting data from multiple data sources and a variety of systems to enrich their analytics and business intelligence (BI). But collecting data is only half of the equation. As the data grows, it becomes challenging to find the right data at the right time. Many organizations can’t take full advantage of their data lakes because they don’t know what data actually exists. Also, there are more regulations and compliance requirements than ever before. It is critical for organizations to understand the kind of data they have, who is handling it, what it is being used for and how it needs to be protected. They also have to avoid putting too many layers and wrappers around the data as it can make the data difficult to access. These challenges create a need for more automated ways to discover, track, research and govern the data.

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Topics: Business Intelligence, Data Governance, Data Management, Data, data operations, AI & Machine Learning

Augmented Intelligence Reduces Dependency on AI/ML Skill Sets

Posted by David Menninger on Sep 15, 2022 3:00:00 AM

Business intelligence has evolved. It now includes a spectrum of analytics, one of the most promising of which has been described as augmented intelligence. Some organizations have used the term to describe the practical reality that artificial intelligence with machine learning is not replacing human intelligence, but augmenting it. The term also represents the application of AI/ML to make business intelligence and analytics tools more powerful and easier to use. It’s this latter usage that I prefer and I’d like to explore in this perspective.

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Topics: Analytics, Business Intelligence, natural language processing, AI & Machine Learning, Analytics & Data, Collaborative & Conversational Computing

Cloud Computing Realities – Part 1

Posted by David Menninger on Sep 1, 2022 3:00:00 AM

The migration to cloud is obvious. Organizations are adopting cloud computing for all variety of applications and use cases. Managed cloud services, commonly referred to as software as a service (SaaS), offer many benefits to organizations including significantly reduced labor costs for system administration and maintenance, as many of these costs are shifted to the software vendor. SaaS also provides organizations with faster time to value as they adopt new technologies by eliminating the need to acquire and configure hardware, and it also eliminates the need to install software. In fact, we assert that by 2025, nine in 10 organizations will be using multiple cloud applications in order to minimize the costs of administration and maintenance. Yet, there are some challenges associated with cloud computing I’d like to address in a series of Analyst Perspectives:

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Topics: Cloud Computing, Digital Technology

Palantir Operationalizes Analytics and Data for Actions and Decisions

Posted by David Menninger on Aug 26, 2022 3:00:00 AM

Organizations are managing and analyzing large datasets every day, identifying patterns and generating insights to inform decisions. This can provide numerous benefits for an organization, such as improved operational efficiency, cost optimization, fraud detection, competitive advantage and enhanced business processes. By bringing the right, actionable data to the right user, organizations can potentially speed up processes and make more effective operational decisions.

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Topics: embedded analytics, Analytics, Business Intelligence, Internet of Things, Streaming Analytics, AI & Machine Learning

Embed Analytics for Greater Reach and More Responsiveness

Posted by David Menninger on Aug 18, 2022 3:00:00 AM

When I looked at the state of analytics recently, it was clear that analytics are not as widely deployed within organizations as they should be. Only 23% of participants in our Analytics and Data Benchmark Research reported that more than one-half of their organization’s workforce are using analytics. There are many elements to becoming a data-driven organization, as my colleague Matt Aslett points out, but analytics are a necessary component. Our research shows that organizations recognize the importance of embedded analytics, ranking it the second most important digital technology in their analytics and data efforts behind big data and ahead of artificial intelligence and machine learning (AI/ML).

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Topics: embedded analytics, Analytics, Analytics & Data

Qlik Advances Self-Service Analytics and Business Intelligence

Posted by David Menninger on Aug 11, 2022 3:00:00 AM

The analytics and business intelligence market landscape continues to grow as more organizations seek robust tools and capabilities to visualize and better understand data. BI systems are used to perform data analysis, identify market trends and opportunities and streamline business processes. They can collect and combine data from internal and external systems to present a holistic view.

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Topics: Analytics, Business Intelligence, Data Governance, Data Management, AI & Machine Learning, Analytics & Data

Expanding the Analytics Continuum: From Analysis to Action

Posted by David Menninger on Aug 2, 2022 3:00:00 AM

I often use the term “analytics” to refer to a broad set of capabilities, deliberately broader than business intelligence. In this Perspective, I’d like to share what decision-makers should consider as they evaluate the range of analytics requirements for their organization.

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Topics: Business Intelligence, natural language processing, AI and Machine Learning, Streaming Analytics, Analytics & Data

Tableau Brings Business Intelligence to Business Users

Posted by David Menninger on Jul 26, 2022 3:00:00 AM

Organizations are collecting vast amounts of data every day, utilizing business intelligence software and data visualization to gain insights and identify patterns and errors in the data. Making sense of these patterns can enable an organization to gain an edge in the marketplace and plan more strategically.

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Topics: embedded analytics, Business Intelligence, AI and Machine Learning

Data Governance, Then and Now

Posted by David Menninger on Jul 20, 2022 3:00:00 AM

We’ve recently published our latest Benchmark Research on Data Governance and it’s fair to say, “you’ve come a long way, baby.” Many of you reading this weren’t around when that phrase was introduced in 1968 to promote Virginia Slims cigarettes, but you may have heard the phrase because it went on to become a part of popular culture. We’ve learned a lot about cigarettes since then, and we’ve learned a lot about data governance, too.

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Topics: Big Data, Data Governance, Data Management, Analytics & Data