Ventana Research Analyst Perspectives

Cyber threats are becoming more sophisticated and pervasive, posing a major challenge for CIOs and IT leaders. To protect their digital assets and drive business growth, they need a new approach to security: Continuous Threat Exposure Management (CTEM). CTEM software continuously monitors and manages the enterprise’s exposure to cyber risks, enabling a swift and effective response to any security incident. In this analyst perspective, we will explore how CTEM software works, why it is essential...

After a year of near-constant AI chatter, the broad strokes of how the technology will roll out in business over the next three to five years are coming into place. It’s almost trite but worth repeating that artificial intelligence will drive a substantial boost in productivity as it’s adopted. Rather than making large swathes of jobs obsolete, it will take the robotic work out of those job descriptions, enabling people to focus on tasks with a greater economic return. 

The first wave of discussions around artificial intelligence (AI) in the contact center was focused on providing software buyers with a general understanding of what the technology could do. Now the conversations are becoming more specific, focused and direct. Buyers are more aware of the spectrum of available use cases and appear to be exploring how to map new tools to the particular business problems they face. Contact center buyers are approaching new technology deployments (or enhancements...

With a year of AI-everywhere-all-the-time chatter now in the rearview mirror, finance and accounting department executives appear to be in a state of apprehension and well-tuned skepticism about the impact this technology will have on their organization. There are solid reasons to believe that the next few years will be transformative, making it important for departments to adopt a fast-follower approach to artificial intelligence. Rather than being a laggard, leaders must be ready to take...

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...

We live in an era of uncertainty, not unpredictability. Managing in uncertain times is always difficult, but tools are available to improve the odds for success by making it easier and faster to plan for contingencies and scenarios. Software makes it possible to manage ahead of any future event, connecting the tactical trees to the strategic forest. The purpose of planning is not just to create a plan: Enterprises spend time thinking ahead because it enables leadership teams, executives and...

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...

Digitally transforming finance operations has been a priority since 2020. For purchasing and the procure-to-pay cycle, software can streamline processes, shorten process times, reduce unnecessary costs, provide greater visibility into cash flows, increase control and improve results. Digitizing operations helps attract and retain the best talent because professionals spend less time on mechanical, repetitive tasks. For all these reasons, beginning this year, Ventana Research’s Office of Finance...

The migration of on-premises applications to the cloud has become more than just a technological shift; it’s a strategic imperative for enterprises. This transition, driven by the need for competitiveness, agility and responsiveness in a rapidly evolving business environment that operates at the speed of digital, is not a simple task. It requires a careful balance between the technology roadmap and the strategic business objectives of the organization.

The increasing importance of intelligent operational applications driven by artificial intelligence (AI) is blurring the lines that have traditionally divided the requirements between operational and analytic data platforms. Operational data platforms have traditionally been deployed to support applications targeted at business users and decision-makers to run the business, with analytic data platforms typically supporting applications used by data and business analysts to analyze the business.