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        Analyst Perspectives

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        • for Topic: Ai Technologies
        • Available Posts: 0

        I have previously described how data as a product was initially closely aligned with data mesh, a cultural and organizational approach to distributed data processing. As a result of data mesh’s association with distributed data, many assumed that the concept was diametrically opposed to the data lake, which offered a platform for combining large volumes of data from multiple data sources. That assumption was always misguided: There was never any reason why data lakes could not be used as a data...

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        Topics: Operations, Data Platforms, Data Intelligence, AI & Technologies

        OneStream offers a platform designed to serve the needs of accounting and financial planning and analysis (FP&A) organizations. The software handles financial close and consolidation, planning and budgeting, analysis and reporting.

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        Topics: Office of Finance, Analytics, Business Planning, ERP and Continuous Accounting, digital finance, Consolidate and Close Management, AI & Technologies, AI and Machine Learning

        I have previously explained how increased enterprise focus on artificial intelligence (AI) and agentic AI is a forcing function for enterprises to take long-overdue steps to improve data management and data governance. Data is integral to AI: large volumes of data are required to train models, while data freshness is important for inferencing in interactive applications and data quality is fundamental to ensuring that the output of agentic and generative AI (GenAI) initiatives can be relied...

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        Topics: Governance, Data Management, Generative AI, AI & Technologies, Agentic AI

        A little under a year ago, I explained how Google was positioning its BigQuery product as a unified data platform for processing data in multiple formats, across multiple locations, for multiple use cases—including business intelligence (BI) and artificial intelligence (AI)—using a combination of multiple data engines, including SQL, Spark and Python. The evolution of BigQuery as the focus of Google’s analytics and AI offerings continued at the recent Google Cloud Next ‘25 event, with Google...

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        Topics: Data Platforms, Generative AI, AI & Technologies

        The artificial intelligence (AI) landscape is undergoing dramatic transformation, with enterprises rapidly adapting to a world where AI is no longer just a possibility but a necessity. ISG Market Lensresearch of 300 enterprises shows that AI initiatives were the second largest category of IT spending for 2024, behind customer experience initiatives. Furthermore, enterprises plan to increase 2025 IT spending on AI initiatives by 5.7%, which is more than any other category and nearly three times...

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        Topics: Generative AI, AI & Technologies, AI and Machine Learning, Cloud Infrastructure

        I recently described how business data catalogs are evolving into data intelligence catalogs. These catalogs combine technical and business metadata and data governance capabilities with knowledge graph functionality to deliver a holistic, business-level view of data production and consumption. The concept of the knowledge graph has been part of the data sector for decades, but adoption has typically been limited to industries and enterprises focused on the Semantic Web, such as media,...

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        Topics: Governance, Generative AI, Data Intelligence, AI & Technologies
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