Matt Aslett's Analyst Perspectives

The 2023 Ventana Research Buyers Guide for Data Orchestration research enables me to provide observations about how the market has advanced. 

I am happy to share insights gleaned from our latest Buyers Guide, an assessment of how well vendors’ offerings meet buyers’ requirements. The Ventana Research 2023 Data Pipelines Buyers Guide is the distillation of a year of market and product research by Ventana Research. Drawing on our Benchmark Research, we apply a structured methodology built on evaluation categories that reflect the real-world criteria incorporated in a request for proposal to Data vendors supporting the spectrum of Data...

The 2023 Ventana Research Buyers Guide for Data Pipelines research enables me to provide observations about how the market has advanced. 

I am happy to share insights gleaned from our latest Buyers Guide, an assessment of how well vendors’ offerings meet buyers’ requirements. The Ventana Research 2023 DataOps Buyers Guide is the distillation of a year of market and product research by Ventana Research. Drawing on our Benchmark Research, we apply a structured methodology built on evaluation categories that reflect the real-world criteria incorporated in a request for proposal to Data vendors supporting the spectrum of DataOps....

The 2023 Ventana Research Buyers Guide for DataOps research enables me to provide observations about how the market has advanced. 

The data platforms market may appear to have little or nothing to do with haute couture, but it is one of the data sectors most strongly influenced by the fickle finger of fashion. In recent years, various architectural approaches to data storage and processing have enjoyed a phase in the limelight, including data warehouse, data mart, data hub, data lake, cloud data warehouse, object storage, data lakehouse, data fabric and data mesh. These approaches are often heralded as the next big thing,...

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.

Organizations today have an ever-increasing appetite for platforms that improve the speed and efficiency of data analytics and business intelligence (BI). The ability to quickly process data enables organizations to make well-informed decisions in real time. This agile approach to data processing is crucial for staying ahead in today's competitive landscape. With the rising need for data-driven insights, organizations face the difficulty of dealing with massive volumes of distributed business...

Despite best intentions, many organizations still struggle with some fundamental aspects of data processing and analytics. Taking data from operational applications and making it available for analysis is a first step, but data management remains a perennial challenge. Data movement and transformation difficulties can lead to delays and data quality problems that prevent organizations from generating value from data. The inability to govern and integrate data from multiple data sources prevents...

Maintaining data quality and trust is a perennial data management challenge, often preventing organizations from operating at the speed of business. Recent years have seen the emergence of data observability as a category of DataOps focused on monitoring the quality and reliability of data used for analytics and governance projects and associated data pipelines. There is clear overlap with data quality, which is more established as both a discipline and product category for improving trust in...