Analyst Perspectives

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...

Compensation data is everywhere. Internal equity metrics, market benchmarks, performance history, pay transparency requirements—there’s no shortage of data coming in from every direction. But volume does not always guarantee clarity. It is not about the data your system can collect, it is about whether that system—and the people behind it—can turn the data into decisions that actually make sense....

Frontline work is being reshaped from every direction: tighter labor pools, unpredictable demand and a workforce that expects more than just a paycheck. Yet too many organizations are still treating workforce scheduling like a game of Tetris—moving blocks around and hoping they fit. It’s time to admit that smart scheduling isn’t just a nice-to-have—it’s a frontline imperative. And if the...

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...

The learning management system (LMS) market is evolving, with the lines that once rigidly defined categories becoming increasingly blurred. Today, an LMS that lacks Learning Experience Platform (LXP) capabilities risks becoming obsolete in an environment where user expectations are shifting rapidly. In a similar vein, an LMS and LXP that fail to harness the power of artificial intelligence (AI)...

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...

Oracle’s recent industry analyst summit demonstrated significant progress in embedding artificial intelligence in its business applications—including those for finance, HR and supply chain management. This amplifies the already broad and deep functionality developed over decades. Oracle also continues to expand and extend its collaborative efforts with financial institutions, a form of...

Oracle, long known for its dominance in databases and enterprise software, has a new message for the business world: Artificial intelligence (AI) isn't just a technology trend, it's a business imperative. At the recent Oracle Industry and Application Analyst Event, company executives made their most compelling case yet for why non-technical executives should care about a deeply integrated tech...

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...

I recently attended the Oracle Apps & Industry Analyst Summit in Redwood City, California. Over the course of two days, Oracle offered a concentrated look at a market that is both racing ahead and tripping over its own shoelaces. Generative, predictive and now agentic artificial intelligence (AI) have become the new currency of competitive advantage across HCM; Oracle alone has delivered more...

I have previously described how data as a product was initially closely aligned with data mesh, a cultural and organizational approach to distributed data processing. As a result of data mesh’s association with distributed data, many assumed that the concept was diametrically opposed to the data lake, which offered a platform for combining large volumes of data from multiple data sources. That...

OneStream offers a platform designed to serve the needs of accounting and financial planning and analysis (FP&A) organizations. The software handles financial close and consolidation, planning and budgeting, analysis and reporting.

At this year’s Conga Connect 2025 conference held in Orlando, FL, the enterprise software provider unveiled both a new chief executive and a sharpened vision for the future of revenue management technology. David Osborne, recently appointed CEO of Conga, took the stage for his keynote address with a foundational question: “Why?”—as in, why does Conga exist?

I have previously explained how increased enterprise focus on artificial intelligence (AI) and agentic AI is a forcing function for enterprises to take long-overdue steps to improve data management and data governance. Data is integral to AI: large volumes of data are required to train models, while data freshness is important for inferencing in interactive applications and data quality is...

The development of artificial intelligence (AI) has transformed the idea of customer experience (CX) from a piecemeal, manually directed practice into a more streamlined and disciplined activity. The available technology has become so diverse and expansive that it is allowing enterprises to cope with a two-headed problem: providing more personalized and effective experiences is complex, and once...

A little under a year ago, I explained how Google was positioning its BigQuery product as a unified data platform for processing data in multiple formats, across multiple locations, for multiple use cases—including business intelligence (BI) and artificial intelligence (AI)—using a combination of multiple data engines, including SQL, Spark and Python. The evolution of BigQuery as the focus of...

The artificial intelligence (AI) landscape is undergoing dramatic transformation, with enterprises rapidly adapting to a world where AI is no longer just a possibility but a necessity. ISG Market Lensresearch of 300 enterprises shows that AI initiatives were the second largest category of IT spending for 2024, behind customer experience initiatives. Furthermore, enterprises plan to increase 2025...

The six costliest words in managing a finance department are, “We’ve always done it this way.” The record-to-report (R2R) cycle describes the process of finalizing and summarizing the financial activities of a business for a specific accounting period—typically a month, quarter or fiscal year. It is important to note that R2R exclusively covers the activities between recording (keeping the books)...

I recently described how business data catalogs are evolving into data intelligence catalogs. These catalogs combine technical and business metadata and data governance capabilities with knowledge graph functionality to deliver a holistic, business-level view of data production and consumption. The concept of the knowledge graph has been part of the data sector for decades, but adoption has...

Ten years have passed since artificial intelligence (AI) first appeared in sales technology, and the results are mixed. Early tools applied rudimentary machine learning (ML) models to customer relationship management (CRM) exports, assigning win probability scores or advising on the “ideal” time to call. The mathematics was sound, the demos impressive, yet adoption faltered because little thought...