Analyst Perspectives

Tokenization is an emerging topic for business software providers. Tokenization is the process of representing something valuable or complex with a simple computer-readable substitute to enhance security or improve the efficiency and usability of a system. Tokens are already widely used in commerce. It’s now common for sensitive data used in a transaction, such as a bank account number or credit...

The emergence of natural language analytics interfaces driven by generative artificial intelligence (GenAI) models has accelerated enterprise initiatives to enable data democratization—making data available to business decision-makers without the need to train them to use business intelligence (BI) tools. It has also heightened the need for agreed semantic models and business metrics, as well as...

I previously described data mesh as a cultural and organizational approach to distributed data ownership, access and governance, rather than a product that could be acquired or even a technical architecture that could be built. While that remains true, many data management software providers have adapted their products in recent years to address the four key principles of data mesh:...

I previously wrote about IBM’s strategy of consolidating analytics, data and artificial intelligence (AI) functionality from various products under its watsonx brand, which was launched in 2023 to address the AI development life cycle, as well as data storage processing and AI governance. The company has added two more offerings to its watsonx portfolio in recent months, combining established...

The IT department of any enterprise is integral to implementing and managing the execution of its data objectives, just as the finance department is integral to implementing and managing financial objectives. Few enterprises would allow the finance department complete autonomy to define financial strategies; however, too many enterprises allow the IT department to define data strategies. Treating...

Artificial intelligence (AI) is no longer a futuristic concept but a current reality, and enterprise leaders are recognizing its profound impact on the IT sector. The development and deployment of AI-driven applications across various industries hinge on a robust IT infrastructure and skilled expertise. The words of industry leaders reinforce this sentiment: Amazon's CEO Andy Jassy indicates that...

As we stand precariously at the intersection of technology and business strategy, ServiceNow’s Knowledge ’25 conference unveiled “the art of the possible” for what service automation can mean in our efficiency-seeking world. ServiceNow has long been a champion of transforming the mundane into the extraordinary, and in the era of AI, it aims to harness the potential of intelligent automation. 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...

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...

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...

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...

It has been a little over a decade since the term data operations entered the analytics and data lexicon. It describes the application of agile development, DevOps and lean manufacturing by data engineering professionals in support of data production. DataOps was initially seen as antithetical to traditional data management approaches, which typically included batch-based and manual tools and...

Infor provides industry-specific enterprise software that enhances business performance and operational efficiency. These verticals and related micro-verticals include manufacturing, food and beverage, hospitality, healthcare, distribution and retail. Infor offers applications for enterprise resource planning, supply chain management, customer relationship management and human capital management,...

The recent recommendation by the European Commission to scale back the scope, granularity and timeline for sustainability reporting represents a sea change in this form of corporate disclosure requirements. If enacted, it will substantially reduce or eliminate the reporting requirements for many enterprises, especially small to midsize establishments, as well as provide more time for compliance....

Data catalogs provide an inventory of data assets that surface metadata from data platforms, analytics tools and applications that can be used to facilitate data discovery and data usage across an enterprise. As I recently explained, however, there are actually multiple types of data catalogs that offer functionality to address specific use cases and user roles, including data inventory, data...

Robotic process automation (RPA) relies on programming or the application of analytical algorithms to execute the most appropriate action in an automated workflow. RPA enables business users to configure a “robot” (actually, computer software) to interact with applications or data sources to process a transaction, move or manipulate data, communicate with other digital systems and manage...

Kofax offers Kapow, robotic process automation (RPA) software used to acquire information from a range of sources without human intervention and without having to write code. These sources include websites, applications, unstructured documents, data stores and desktop spreadsheets. RPA software does repetitive, low-value work that otherwise may be performed by person. It saves time in these...

When applying information technology to drive better business performance, companies and the systems integrators that assist them often underestimate the importance of organizing data management around processes. For example, companies that do not execute their quote-to-cash cycle as an end-to-end process often experience a related set of issues in their sales, marketing, operations, accounting...

Anaplan, a provider of cloud-based business planning software for sales, operations, and finance and administration departments, recently implemented its new Winter ’14 Release for customers. This release builds on my colleagues analysis on their innovation in business modeling and planning in 2013. Anaplan’s primary objective is to give companies a workable alternative to spreadsheets for...

Organizations succeed through continuous planning to achieve high levels of performance. For most organizations planning is not an easy process to conduct. Planning software is typically designed for only a few people in the process, such as analysts, or organizations might use spreadsheets, which are not designed for business planning across an organization. Most technologies only allow you to...