David Menninger's Analyst Perspectives

Ventana Research recently announced its 2023 Market Agenda for Analytics, continuing the guidance we have offered for nearly two decades to help organizations derive optimal value from technology investments to improve business outcomes.

Topics: embedded analytics, Analytics, Business Intelligence, Data, Digital Technology, natural language processing, Process Mining, Analytics & Data, Collaborative & Conversational Computing

For far too long, business intelligence technologies have left the rest of the exercise to the reader. Many of these tools do an excellent job providing information in an interactive way that lets organizations dive into the data and learn a lot about what has happened across all aspects of the business. More recently, many of these tools have added augmented intelligence capabilities that help explain why things happened. But rarely did any of these tools provide information about what to do or how to evaluate the alternative ways in which you might respond.

Topics: business intelligence, Analytics, Digital Technology, AI and Machine Learning, Analytics & Data

Analytics processes are all about how organizations use data to create metrics that help manage and improve operations. Yet, the discipline applied to analytics processes seems to be lacking compared to data processes. I’ve pointed out that the weak link in data governance is often analytics. Organizations can also do a better job tying AnalyticOps to DataOps and do more to define and manage metrics. Our research has shown that creating and managing metrics in a semantic model improves analytics processes.

Topics: Analytics, Business Intelligence, Data Governance, Data, Digital Technology, Analytics & Data

In previous perspectives in this series, I’ve discussed some of the realities of cloud computing including costs, hybrid and multi-cloud configurations and business continuity. This perspective examines the realities of security and regulatory concerns associated with cloud computing. These issues are often cited by our research participants as reasons they are not embracing the cloud. To be fair, the majority of our research participants are embracing the cloud. However, among those that have not yet made the transition to the cloud, security and regulatory concerns are among the most common issues cited across the various studies we have conducted.

Topics: Analytics, Business Intelligence, Cloud Computing, Data Governance, Digital Technology, AI & Machine Learning, Analytics & Data, Governance & Risk

Recently, I suggested you need to “mind the gap” between data and analytics. This perspective addresses another gap — the gap in skills between business intelligence (BI) and artificial intelligence/machine learning (AI/ML).

Topics: Analytics, Business Intelligence, Digital Technology, AI & Machine Learning, Analytics & Data

If you’ve ever been to London, you are probably familiar with the announcements on the London Underground to “mind the gap” between the trains and the platform. I suggest we also need to mind the gap between data and analytics. These worlds are often disconnected in organizations and, as a result, it limits their effectiveness and agility.

Topics: business intelligence, embedded analytics, Analytics, Data Governance, Data Management, data operations, Analytics & Data

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.

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

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).

Topics: embedded analytics, Analytics, Analytics & Data

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.

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

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.

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