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

TIBCO Broadens Portfolio for Improved Analytics Efficiency

Posted by David Menninger on Nov 30, 2021 3:00:00 AM

TIBCO is a large, independent cloud-computing and data analytics software company that offers integration, analytics, business intelligence and events processing software. It enables organizations to analyze streaming data in real time and provides the capability to automate analytics processes. It offers more than 200 connectors, more than 200 enterprise cloud computing and application adapters, and more than 30 non-relational structured query language databases, relational database management systems and data warehouses.

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Topics: embedded analytics, Analytics, Collaboration, Data Governance, Information Management, Data, Digital Technology, data lakes, AI and Machine Learning

Analytic Ops: The Last Mile of Data Ops

Posted by David Menninger on Nov 24, 2021 3:00:00 AM

Organizations have become more agile and responsive, in part, as a result of being more agile with their information technology. Adopting a DevOps approach to application deployment has allowed organizations to deploy new and revised applications more quickly. DataOps is enabling organizations to be more agile in their data processes. As organizations are embracing artificial intelligence (AI) and machine learning (ML), they are recognizing the need to adopt MLOps. The same desire for agility suggests that organizations need to adopt AnalyticOps.

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Topics: business intelligence, Analytics, Data Governance, Data, Digital Technology, data operations, data platforms

Talend Data Fabric Simplifies Data Life Cycle Management

Posted by David Menninger on Nov 16, 2021 3:00:00 AM

Talend is a data integration and management software company that offers applications for cloud computing, big data integration, application integration, data quality and master data management. The platform enables personnel to work with relational databases, Apache Hadoop, Spark and NoSQL databases for cloud or on-premises jobs. Talend data integration software offers an open and scalable architecture and can be integrated with multiple data warehouses, systems and applications to provide a unified view of all data. Its code generation architecture uses a visual interface to create Java or SQL code.

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Topics: Analytics, Business Intelligence, Collaboration, Data Governance, Data Preparation, Information Management, Data, Digital Technology, data lakes, AI and Machine Learning

What Makes a Metric a KPI?

Posted by David Menninger on Nov 9, 2021 3:00:00 AM

How does your organization define and display its metrics? I believe many organizations are not defining and displaying metrics in a way that benefits them most. If an organization goes through the trouble of measuring and reporting on a metric, the analysis ought to include all the information needed to evaluate that metric effectively. A number, by itself, does not provide any indication of whether the result is good or bad. Too often, the reader is expected to understand the difference, but why leave this evaluation to chance? Why not be more explicit about what results are expected?

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Topics: Analytics, Business Intelligence, Internet of Things, Data, Digital Technology, AI and Machine Learning, Streaming Analytics

Using Event Data in Financial Services to Improve Business Processes

Posted by David Menninger on Nov 3, 2021 3:00:00 AM

Our research shows that nearly all financial service organizations (97%) consider it important to accelerate the flow of information and improve responsiveness. Even just a few years ago, capturing and evaluating this information quickly was much more challenging, but with the advent of streaming data technologies that capture and process large volumes of data in real time, financial service organizations can quickly turn events into valuable business outcomes in the form of new products and services or revenue.

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Topics: Analytics, Internet of Things, Data, Digital Technology, Streaming Analytics