Analyst Perspectives

Despite a focus on being data-driven, many organizations find that data and analytics projects fail to deliver on expectations. These initiatives can underwhelm for many reasons, because success requires a delicate balance of people, processes, information and technology. Small deviations from perfection in any of those factors can send projects off the rails.

I have written before about the rising popularity of the data fabric approach for managing and governing data spread across distributed environments comprised of multiple data centers, systems and applications. I assert that by 2025, more than 6 in 10 organizations will adopt data fabric technologies to facilitate the management and processing of data across multiple data platforms and cloud environments. The data fabric approach is also proving attractive to vendors, including Microsoft, as a...

At one point, analytics and business intelligence were considered non-mission critical activities. One of the primary concerns in designing analytics systems was to ensure they didn’t interfere with or draw computing resources away from operational systems. But today, analytical systems are integral to many aspects of operations. More than 9 in 10 participants in our Analytics and Data Benchmark Research reported analytics had improved activities and processes. However, most analytics and BI...

I recently wrote about the various technologies used by organizations to process and analyze data in real time. I explained that while the terms streaming data and events and streaming analytics are often used interchangeably, they are separate disciplines that make use of common underlying concepts and technologies such as events, event brokers and event-driven architecture. Confluent’s acquisition of Immerok earlier this year provided a reminder of this fact. Confluent is one of the most...

This title plays on the now-ancient meme from the 1990s: “On the internet, nobody knows you’re a dog,” which pointed to a challenge of anonymity posed by new technology. In this case, though, I’m using it to highlight an opportunity that generative artificial intelligence presents in streamlining routine business functions that require some level of individual skill and experience to handle. Ordinary contracts are just one example of work products that require humans to create, edit, analyze,...

If I had a magic wand, I would want to add scenario evaluation to all business intelligence tools on the market. I have previously written about the need to make intelligent decisions with decision intelligence. The data and analytics markets have evolved so that organizations have far greater capabilities to utilize data in decision-making processes. While there is some convergence around the concept of decision intelligence, there are still several “islands” of decision-making. Analyzing...

It is a mark of the rapid, current pace of development in artificial intelligence (AI) that machine learning (ML) models, until recently considered state of the art, are now routinely being referred to by developers and vendors as “traditional.” Generative AI, and large language models (LLMs) in particular, have taken the AI world by storm in the past year, automating and accelerating the development of content, including text, digital images, audio and video, as well as computer programs and...

As I have previously explained, we expect an increased demand for intelligent operational applications infused with the results of analytic processes, such as personalization and artificial intelligence-driven recommendations. These systems rely on the analysis of data in the operational data platform to accelerate worker decision-making or improve customer experience.

The role of the chief information officer has evolved from managing IT to maximizing technology for business value. Many organizations launch digital transformation programs to identify and deliver the desired value but discover that digital transformation is a complex, lengthy process. Budgets and resources can be quickly exhausted with little to show for the investment. Yet business objectives remain.

Intelligent automation is a powerful tool that can help the CIO and IT leaders optimize business processes and outcomes while reducing costs, risks and errors. Automation takes many forms, each with its own applications, benefits and limitations. In a previous perspective, I shared how technology helps organizations automate processes and enhance workflow efficiency. This perspective explains the various types of automation enabled by artificial intelligence technologies and their applications...