Matt Aslett's Analyst Perspectives

Increased enterprise focus on artificial intelligence (AI) and generative AI (GenAI) has served to sharpen the focus on the need for trusted data and reliable analytics and data operations. The ISG State of Generative AI Market Report highlighted that elevated expectations and demands associated with AI are a forcing function for enterprises to take long-overdue steps to improve data and analytics processes to ensure that data that is clean, well-organized and compliant with regulatory...

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 discovery and data governance. The data intelligence catalog is an emerging category that combines...

It is now more than two years since the launch of ChatGPT introduced the world to generative AI (GenAI) and large language models (LLMs). GenAI-based assistants and co-pilots are now widely adopted, with individuals and enterprises adopting GenAI models to automate the generation of text, digital images, audio, video and code, amongst other things.

Despite all the interest in artificial intelligence (AI) and generative AI (GenAI), ISG’s Buyers Guide for Data Platforms serves as a reminder of the ongoing importance of product experience functionality to address adaptability, manageability, reliability and usability. While new and emerging capabilities might catch the eye, features that address data platform security, performance and availability remain some of the most significant deal-breakers when enterprises are considering potential...

Too often, enterprises find that data is distributed across multiple silos on-premises and in the cloud. More than two-thirds of participants in ISG’s Market Lens Cloud Study are using a hybrid architecture involving both on-premises and cloud infrastructure for analytics and artificial intelligence deployments. Unifying data to achieve operational and analytic objectives requires complex data integration and management processes. Fulfilling these processes requires a smorgasbord of tools aimed...

I previously explained that data observability software has become a critical component of data-driven decision-making. Data observability addresses one of the most significant impediments to generating value from data by providing an environment for monitoring the quality and reliability of data on a continual basis. Maintaining quality and trust is a perennial data management challenge, the importance of which has come into sharper focus in recent years thanks to the rise of artificial...

Analytics software is used by business analysts and decision-makers to facilitate the generation of insights from data. It encompasses business intelligence and decision intelligence software, including reports and dashboards as well as embedded analytics and the development of intelligent applications infused with the results of analytic processes. Analytics software enables enterprises to improve business outcomes by operating more efficiently, accelerating product development and enhancing...

The development, testing and deployment of data pipelines is a fundamental accelerator of data-driven strategies, enabling enterprises to extract data from the operational applications and data platforms designed to run the business and load, integrate and transform it into the analytic data platforms and tools used to analyze the business. As I explained in our recent Data Pipelines Buyers Guide, data pipelines are essential to generating intelligence from data. Healthy data pipelines are...

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.