Analyst Perspectives

I have previously written about the critical importance of data management to the development of artificial intelligence (AI) applications and agentic AI. The importance of data management is nothing new, but automation of business processes and decision-making raises the stakes in terms of the expectations and the risks. The need for enterprises to have trust in their data governance and data...

I have written several times this year about Model Context Protocol (MCP) and its importance in enabling agentic artificial intelligence (AI) use cases. Numerous data platform, data management, data operations and real-time data software providers have added support for MCP to their products in recent months. MCP has become so ubiquitous, in fact, that it is easy to forget the protocol was only...

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...

I previously wrote about the role that data intelligence catalogs play in enabling business leaders to understand the use of data across an enterprise. I also recently wrote about the importance of treating data as a business discipline to ensure that data projects are aligned with business strategy objectives. As I noted, although many data catalog products provide enterprises with information...

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...

Fragmentation is a pervasive problem for enterprises seeking to take advantage of data generated by various applications to drive business decision-making. For almost as long as the IT industry has existed enterprises have struggled to combine and integrate information from multiple data siloes created by a variety of applications and business units. Creating a “single version of the truth” that...

Databricks recently hosted its Data+AI Summit in San Francisco, an event that attracted 22,000 attendees. That’s a far cry from the Spark Summit I attended in 2016. As pointed out in my coverage of Databricks massive funding round earlier this year, the company was originally founded as a provider of cloud-based Apache Spark services. Since its inception, Spark has been associated with processing...

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...

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...

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 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...

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...

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...

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...

The emphasis on environmental, social and governance (ESG) issues has been growing for some time. I participated in the development of the Sustainability Accounting Standards Board (SASB) as a software industry expert more than a decade ago. The rise of ESG’s profile in corporate reporting is the latest evolution of “responsible investing,” a topic that goes back centuries in the west. The modern...

ESG reporting is a matter that organizations – and especially publicly held corporations – will be confronting over the next several years. Ventana Research asserts that by 2025, one-half of corporations with 1,000 or more employees will have a formal ESG reporting process in place to address legal mandates or shareholder demand. The roots of ESG investing go back many decades but it has gained...

With the announcement of Ventana Research market agenda, a new expertise in Digital Business has been launched, I will outline the areas of focus that provide insights to organizations that can be used to optimize technology, increase agility and organizational readiness. We are proud to provide expertise on digital effectiveness through our research and insights on trends and best practices.

SYSPRO is a 35-year-old software vendor that focuses on selling enterprise resource planning (ERP) systems to midsize companies, particularly those in manufacturing and distribution. In manufacturing, SYSPRO supports make, configure and assemble, engineer to order, make to stock and job shop environments. The company attempts to differentiate itself through vertical specialization and its years...