Matt Aslett's Analyst Perspectives

ISG Software Research’s expertise examines the software provider landscape through two lenses: business applications (including office of finance, human capital management (HCM) and customer experience) and IT and technology (including digital business, digital technology, artificial intelligence (AI) and analytics and data). Most software providers fall into one of these two high-level expertise areas. One of the reasons that agentic AI is so potentially impactful on the software sector is...

I have been saying for several years that success with streaming data requires enterprises to manage data in motion alongside data at rest, rather than treating streaming as a niche activity. Software providers have also been moving in this direction. Many established data management providers have added the ability to manage, store and process streaming data alongside their existing batch data processing capabilities. At the same time, providers closely associated with streaming data, such as...

One of the key questions that will need to be solved if agentic artificial intelligence is to fulfill its potential is which technologies and providers will serve the role of orchestrating communication and integration between the various models, applications and data repositories involved. ISG Research defines agentic AI as software designed to execute business processes through autonomous actions, potentially controlling multiple processes and systems through the orchestration of one or more...

If a single phrase could sum up the big data craze of a dozen or so years ago, it would be “more data beats better algorithms.” Attributed to Google research director Peter Norvig, the quote effectively summarized a research paper Norvig jointly authored called The Unreasonable Effectiveness of Data and was embraced by big data enthusiasts as articulating the prevalent thinking that enterprises with the largest volumes of data have an advantage over rivals. The phrase was, of course, an...

My colleagues have recently described how agentic artificial intelligence (AI) has the potential to revolutionize enterprise computing by automating the handling of static and dynamic complexity to enable software to take action without the need for human intervention. Put simply, agentic AI is the orchestration of the execution of discreet business tasks by a combination of software components that automate business processes. While agentic AI is the next big thing, it can also be seen as the...

Domo is best known as a business intelligence (BI) and analytics software provider, thanks to its functionality for visualization, reporting, data science and embedded analytics. Additionally, as I recently explained, the company’s platform addresses a broad range of capabilities that includes data governance and security, data integration and application development, as well as the automation and incorporation of artificial intelligence (AI) and machine learning (ML) models into BI and...

Data governance has always been a critical part of the data and analytics landscape. However, for many years, it was seen as a preventive function to limit access to data and ensure compliance with security and data privacy requirements. To fulfill today’s data-driven agendas, many enterprises need an evolved perspective on data governance. The development of new applications driven by artificial intelligence requires a more agile and collaborative approach to data governance—one that automates...

Natural language interfaces for business intelligence products existed long before the emergence of generative artificial intelligence. Large language models have allowed BI providers to accelerate the delivery of functionality to convert natural language questions into analytic queries and generate summarizations and recommendations from data and charts. Features that enable natural language query and natural language generation are now ubiquitous.

In an earlier Analyst Perspective, I discussed data democratization’s role in creating a data-driven enterprise agenda. Building a foundation of self-service data discovery, data-driven organizations provide more workers with the ability to analyze and use data. I’ve also examined how generative artificial intelligence (GenAI) could revolutionize business intelligence software by using natural language interfaces to lower the barriers to working with analytics software. Today, however, data...

As enterprises embrace the potential opportunities presented by artificial intelligence (AI), they are quickly finding that good data management is a prerequisite. As was explained in ISG’s State of Generative AI Market Report, AI requires data that is clean, well-organized and compliant with regulatory standards. There are multiple challenges to delivering AI-ready data, including combining structured and unstructured data, ensuring that the combined data can be trusted, and validating that...