Matt Aslett's Analyst Perspectives

As enterprises seek to increase data-driven decision-making, many are investing in strategic data democratization initiatives to provide business users and data analysts with self-service access to data across the enterprise. Such access has long been a goal of many enterprises, but few have achieved it. Only 15% of participants in Ventana Research’s Analytics and Data Benchmark Research say their organization is very comfortable allowing business users to work with data that has not been...

Cloud computing has had an enormous impact on the analytics and data industry in recent decades, with the on-demand provisioning of computational resources providing new opportunities for enterprises to lower costs and increase efficiency. Two-thirds of participants in Ventana Research’s Data Lakes Dynamic Insightsresearch are using a cloud-based environment as the primary data platform for analytics. 

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...

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.

In recent years, many enterprises have migrated data platform workloads from on-premises infrastructure to cloud environments, attracted by the promised benefits of greater agility and lower costs. The scale of cloud data platform adoption is illustrated by Ventana Research’s Data Lakes Dynamic Insights research: For two-thirds (66%) of participants, the primary data platform used for analytics is cloud based. As the quantity and importance of the data platform workloads deployed in the cloud...

Ventana Research recently announced its 2024 Market Agenda for Analytics and Data, continuing the guidance we have offered for two decades to help enterprises derive optimal value and improve business outcomes.

Discussion about potential deployment locations for analytics and data workloads is often based on the assumption that, for enterprise workloads, there is a binary choice between on-premises data centers and public cloud. However, the low-latency performance or sovereignty characteristics of a significant and growing proportion of workloads make them better suited to data and analytics processing where data is generated rather than a centralized on-premises or public cloud environment. ...

The phrase ‘big data’ may have largely gone out of fashion, but the concept of storing and processing all relevant data continues to be important for enterprises seeking to be more data-driven. Doing so requires analytic data platforms capable of storing and processing data in multiple formats and data models. This will be an important focus for the forthcoming Data Platforms Buyer’s Guide 2024. 

I recently discussed how fashion has a surprisingly significant role to play in the data market as various architectural approaches to data storage and processing take turns enjoying a phase in the limelight. Pendulum swing is a theory of fashion that describes the periodic movement of trends between two extremes, such as short and long hemlines or skinny and baggy/flared trousers. Pendulum swing theory is similarly a factor in data technology trends, with an example being the oscillation...

I previously described how Oracle had positioned its database portfolio to address any and all data platform requirements. The caveat to that statement at the time was that any organization wanting to take advantage of the company’s flagship Oracle Autonomous Database could only do so using Oracle Cloud Infrastructure (OCI) cloud computing service, their own datacenter or a hybrid cloud environment. The widespread popularity of Oracle Database and the advanced automation capabilities delivered...