Ventana Research 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

The 2021 Market Agenda for Analytics: Converting Data Into Insights

Posted by David Menninger on Feb 24, 2021 6:00:00 AM

Ventana Research recently announced its 2021 market agenda for Analytics, continuing the guidance we’ve offered for nearly two decades to help organizations derive optimal value from technology investments to improve business outcomes.

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Topics: embedded analytics, Analytics, Business Intelligence, natural language processing, AI and Machine Learning, Process Mining, Streaming Analytics

How to Take Advantage of AI/ML Today

Posted by David Menninger on Feb 8, 2021 6:00:00 AM

The industry is making huge strides with artificial intelligence (AI) and machine learning (ML). There is more data available to analyze. Analytics vendors have made it easier to build and deploy models, and AI/ML is being embedded into many types of applications. Organizations are realizing the value that AI/ML provides and there are now millions of professionals with AI or ML in their title or job description. AI/ML is even being used to make many aspects of itself easier. Organizations that want to build and deploy their own AI/ML models need to be realistic about the capabilities that are available today. As a practical matter, organizations should anticipate that a robust AI/ML deployment in the current environment requires a set of specialized skills and operational processes, including data operations (dataops) and ML operations (MLops). Collaboration across these disciplines and processes is also required.

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Topics: Sales, Customer Experience, Marketing, Analytics, Business Intelligence, Data Preparation, Digital Technology, AI and Machine Learning

Introducing Precisely for Data Integrity

Posted by David Menninger on Jan 25, 2021 6:00:00 AM

Data is becoming more valuable and more important to organizations. At the same time, organizations have become more disciplined about the data on which they rely to ensure it is robust, accurate and governed properly. Without data integrity, organizations cannot trust the information produced by their data processes, and will be discouraged from using that data, resulting in inefficiencies and reduced effectiveness.

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Topics: business intelligence, Analytics, Data Governance, Data Preparation, Information Management, Data, data lakes

Cloudera Consolidates Its Data Platform

Posted by David Menninger on Jan 22, 2021 6:00:00 AM

Organizations are dealing with exponentially increasing data that ranges broadly from customer-generated information, financial transactions, edge-generated data and even operational IT server logs. A combination of complex data lake and data warehouse capabilities are required to leverage this data. Our research shows that nearly three-quarters of organizations deploy both data lakes and data warehouses but are using a variety of approaches which can be cumbersome. A single platform that can provide both capabilities will help address organizations’ requirements.

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Topics: PROS Pricing, embedded analytics, Analytics, Business Intelligence, Collaboration, Data Governance, Data Preparation, Information Management, Data, data lakes, AI and Machine Learning

Tableau and Salesforce bring New Look to Business Analytics

Posted by David Menninger on Jan 20, 2021 6:00:00 AM

Businesses are transforming their organizations, building a data culture and deploying sophisticated analytics more broadly than ever. However, the process of using data and analytics is not always easy. The necessary tools are often separate, but our research shows organizations prefer an integrated environment. In our Data Preparation Benchmark Research, we found that 41% of participants use Analytics and Business Intelligence tools for data preparation.

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Topics: embedded analytics, Analytics, Business Intelligence, Collaboration, Data Preparation, Information Management, Internet of Things, Data, Digital Technology, natural language processing, Conversational Computing, AI and Machine Learning