Analyst Perspectives

I’m proud to share Ventana Research’s 2021 market agenda for digital technology. Our focus in this agenda is to deliver expertise to help organizations prioritize technology investments that increase workforce effectiveness and organizational agility, ensuring ongoing operation during any type of disruption.

Ventana Research recently announced its 2021 market agenda in the expertise area of Customer Experience. Most organizations have some degree of focus on managing how they interact with their customers, but it is often a disjointed and constrained process. Developing an effective customer experience has become an investment priority in recent years as organizations increasingly recognize the importance of good experiences to profitability, customer longevity and advocacy on behalf of brands.

Ventana Research recently announced its 2021 market agenda for Analytics, continuing the guidance we’ve offered for nearly two decades to help organizations derive optimal value from technology investments to improve business outcomes.

The industry is making huge strides with artificial intelligence (AI) and machine learning (ML). There is more data available to analyze. Analytics vendors have made it easier to build and deploy models, and AI/ML is being embedded into many types of applications. Organizations are realizing the value that AI/ML provides and there are now millions of professionals with AI or ML in their title or job description. AI/ML is even being used to make many aspects of itself easier. Organizations that...

BlackLine recently held its first virtual user conference, Beyond the Black, where it detailed numerous additions and enhancements to its applications. Of note was the launch of BlackLine Cash Application, an accounts receivable (AR) processing software based on software originally developed by recently acquired Rimilia. The new application fits the company's product strategy of providing accounting departments with software that automates time-consuming repetitive tasks and substantially...

In the context of planning, budgeting and benchmarking, external data includes information about the world outside an organization such as economic and market statistics, competitors and customers. Today, a comprehensive set of external data is a “nice to have” item in most organizations, but that’s likely to change. External data is necessary for useful and accurate business-focused planning and budgeting, and for performance benchmarking. It is also essential for the effective applications of...

Organizations are dealing with exponentially increasing data that ranges broadly from customer-generated information, financial transactions, edge-generated data and even operational IT server logs. A combination of complex data lake and data warehouse capabilities are required to leverage this data. Our research shows that nearly three-quarters of organizations deploy both data lakes and data warehouses but are using a variety of approaches which can be cumbersome. A single platform that can...

Businesses are transforming their organizations, building a data culture and deploying sophisticated analytics more broadly than ever. However, the process of using data and analytics is not always easy. The necessary tools are often separate, but our research shows organizations prefer an integrated environment. In our Data Preparation Benchmark Research, we found that 41% of participants use Analytics and Business Intelligence tools for data preparation.

Traditional on-premises data processing solutions have led to a hugely complex and expensive set of data silos where IT spends more time managing the infrastructure than extracting value from the data. Big data architectures have attempted to solve the problem with large pools of cost-effective storage, but in doing so have often created on-premises management and administration challenges. These challenges of acquiring, installing and maintaining large clusters of computing resources gave rise...

Organizations are always looking to improve their ability to use data and AI to gain meaningful and actionable insights into their operations, services and customer needs. But unlocking value from data requires multiple analytics workloads, data science tools and machine learning algorithms to run against the same diverse data sets. Organizations still struggle with limited data visibility and insufficient insights, which are often caused by a multitude of reasons such as analytic workloads...