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        Matt Aslett's Analyst Perspectives

        As I noted in the 2024 Buyers Guide for Operational Data Platforms, intelligent applications powered by artificial intelligence have impacted the requirements for operational data platforms. These applications, infused with contextually relevant recommendations, predictions and forecasting, are driven by machine learning and generative AI.

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        Topics: Data Platforms, Analytics & Data

        As I explained in our recent Buyers Guide for Data Platforms, the popularization of generative artificial intelligence (GenAI) has had a significant impact on the requirements for data platforms in the last 18 months. While there is an ongoing need for data platforms to support data warehousing workloads involving analytic reports and dashboards, there is increasing demand for analytic data platform providers to add dedicated functionality for data engineering, including the development,...

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        Topics: Analytics, natural language processing, AI & Machine Learning, Data Platforms, Generative AI, Model Building and Large Language Models, Machine Learning Operations

        Enterprises face a bewildering level of choice in relation to data platforms, as evidenced by the number of software providers and products assessed in our recent Data Platforms Buyers Guide. There are numerous data platform providers and products to choose from, but also a diverse array of functional and architectural options. Is the workload primarily operational or analytic? Will it be deployed on-premises or in the cloud? Should it be distributed or centralized? Data warehouse or data...

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        Topics: AI & Machine Learning, Data Platforms, Data Intelligence, Analytics and Data

        I have written on multiple occasions about the increasing proportion of enterprises embracing the processing of streaming data and events alongside traditional batch-based data processing. I assert that, by 2026, more than three-quarters of enterprises’ standard information architectures will include streaming data and event processing, allowing enterprises to be more responsive and provide better customer experiences.

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        Topics: AI & Machine Learning, Data Platforms, Analytics & Data, Streaming Data & Events

        I am happy to share insights gleaned from our latest Buyers Guide, an assessment of how well software providers’ offerings meet buyers’ requirements. The Data Platforms Ventana Research Buyers Guide is the distillation of a year of market and product research by ISG and Ventana Research.

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        Topics: Data Platforms, Analytics & Data, analytic data platforms, Operational Data Platforms

        The emergence of generative artificial intelligence (GenAI) has significant implications at all levels of the technology stack, not least analytics and data products, which serve to support the development, training and deployment of GenAI models, and also stand to benefit from the advances in automation enabled by GenAI. The intersection of analytics and data and GenAI was a significant focus of the recent Google Cloud Next ’24 event. My colleague David Menninger has already outlined the key...

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        Topics: Analytics, natural language processing, AI & Machine Learning, Data Platforms, Analytics & Data, Generative AI

        I previously wrote about the potential for rapid adoption of the data lakehouse concept as enterprises combined the benefits of data lakes based on low-cost cloud object storage with the structured data processing functionality normally associated with data warehousing. By layering support for table formats, metadata management and transactional updates and deletes as well as query engine and data orchestration functionality on top of low-cost storage of both structured and unstructured data,...

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        Topics: Analytics, Data Platforms, Analytics & Data

        I recently wrote about the development, testing and deployment of data pipelines as a fundamental accelerator of data-driven strategies. As I explained in the 2023 Data Orchestration Buyers Guide, today’s analytics environments require agile data pipelines that can traverse multiple data-processing locations and evolve with business needs.

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        Topics: Analytics, data operations, AI & Machine Learning, Data Platforms, Analytics & Data, Generative AI, Data Intelligence

        I wrote recently about the role that data intelligence has in enabling enterprises to facilitate data democratization and the delivery of data as a product. Data intelligence provides a holistic view of how, when, and why data is produced and consumed across an enterprise, and by whom. This information can be used by data teams toensure business users and data analysts are provided with self-service access to data that is pertinent to their roles and requirements. Delivering data as a product...

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        Topics: Analytics, Data Ops, data operations, AI & Machine Learning, Data Platforms, Analytics & Data, GenAI, Data Intelligence

        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...

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        Topics: Analytics, AI, data operations, AI & Machine Learning, Data Platforms, Analytics & Data, Data Intelligence
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