Analyst Perspectives

We live in a time of uncertainty, not unpredictability. Especially when a business finds itself on an undefined journey with an unclear destination—whether caused by internal events or the world at large—having plans to deal with a range of outcomes increases the odds of success. Or, at least enduring the least amount of damage. Managing an organization in uncertain times is always hard, but tools are available to improve the odds of success by making it easier and faster to plan for...

Founded as Software Development Laboratories in 1977, Oracle is a behemoth in the software industry, generating more than $50 billion in revenue in its fiscal year 2024. Originally focused solely on the relational database market, the software provider operated as Relational Systems, Inc. for several years before adopting the name Oracle in 1982. The company went public in 1986 and became one of the largest software providers in the world, eventually amassing a large portfolio of business...

As enterprises seek to expand and accelerate the adoption of artificial intelligence (AI) many are finding that longstanding analytics and data challenges are a barrier to success. 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. The need for good data management is by no means new, but the expectations and demands associated with AI are a forcing function for enterprises to take long-overdue...

AI, like analytics, must lead to action. Too often, in both cases, too much of the exercise is left to the reader. We have tools to provide sophisticated analyses, including AI platforms that can be used to predict many types of behavior, but we fall short in helping the workforce know what to do with that information. Some examples are more obvious, such as fraud detection. If a transaction is predicted to be fraudulent, the transaction should be blocked. But even this example is not as cut...

In the technology industry, 2023 will be remembered as the year of generative artificial intelligence. Yes, the world was made aware of GenAI when ChatGPT was publicly launched in November of 2022, but few knew the impact it would have at that point in time. Since then, GenAI has taken the world by storm, with vendors applying the technology to make it easier to ask questions about data, write code (including SQL), prepare data for analyses, document data pipelines and use software products...

I have previously written about the impact of intelligent operational applications on the requirements for data platforms. Intelligent applications are used to run the business but also deliver personalization, recommendations and other features generated by machine learning and artificial intelligence. As such, they require a combination of operational and analytic processing functionality. The emergence of these intelligent applications does not eradicate the need for separate analysis of...

Unstructured data has been a significant factor in data lakes and analytics for some time. Twelve years ago, nearly a third of enterprises were working with large amounts of unstructured data. As I’ve pointed out previously, unstructured data is really a misnomer. The data is structured; it's just not structured into rows and columns that fit neatly into a relational table like much of the other information enterprises process. Consequently, it requires different skills, different technology...

We’ve been saying for years that natural language processing (NLP) and natural language analytics would greatly expand access to analytics. However, prior to the explosion of generative AI (GenAI), software providers had struggled to bring robust natural language capabilities to market. It required considerable manual effort. Many analytics providers had introduced natural language capabilities, but they didn’t really resonate with enterprise requirements. They required significant effort to...

Ventana Research recently announced its 2024 Market Agenda for Artificial Intelligence, continuing the guidance we have offered for two decades to help enterprises derive optimal value from technology and improve business outcomes.

Roughly half of my more than 30-year career in human capital management was spent as a line manager responsible for HR technology strategy, selection and deployment. I learned a number of lessons during these years — some just in time, some after the fact. If I had to identify one common thread that unites these insights, it would be that inadequate attention to change management is an ROI-killer on these strategic initiatives every time.