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        Analyst Perspectives

        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

        Data governance has always been a critical part of the data and analytics landscape. However, for many years, it was seen as a preventive function to limit access to data and ensure compliance with security and data privacy requirements. To fulfill today’s data-driven agendas, many enterprises need an evolved perspective on data governance. The development of new applications driven by artificial intelligence requires a more agile and collaborative approach to data governanceone that automates...

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        Topics: Governance, Machine Learning, Operations, AI, Data Intelligence

        It has been a little over a decade since the term data operations entered the analytics and data lexicon. It describes the application of agile development, DevOps and lean manufacturing by data engineering professionals in support of data production. DataOps was initially seen as antithetical to traditional data management approaches, which typically included batch-based and manual tools and practices. The term was embraced by emerging software providers as a means of differentiating from...

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        Topics: Governance, Machine Learning, Operations, AI, Generative AI, Data Intelligence

        In an earlier Analyst Perspective, I discussed data democratization’s role in creating a data-driven enterprise agenda. Building a foundation of self-service data discovery, data-driven organizations provide more workers with the ability to analyze and use data. I’ve also examined how generative artificial intelligence (GenAI) could revolutionize business intelligence software by using natural language interfaces to lower the barriers to working with analytics software. Today, however, data...

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        Topics: Analytics, AI, Data Intelligence

        SAP was formed in 1972 to create standardized business software that would integrate all business processes and enable data processing in real time. Following the success of the initial release and subsequent R/2, the company went public in 1988 and has grown into one of the world’s largest software companies, reporting more than $37 billion in revenues in its most recent annual report. Through internal development efforts and numerous acquisitions, including Business Objects, Sybase, Ariba,...

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        Topics: Machine Learning, Analytics, AI, Data Intelligence
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        Our Analyst Perspective Policy

        • Ventana Research’s Analyst Perspectives are fact-based analysis and guidance on business, industry and technology vendor trends. Each Analyst Perspective presents the view of the analyst who is an established subject matter expert on new developments, business and technology trends, findings from our research, or best practice insights.

          Each is prepared and reviewed in accordance with Ventana Research’s strict standards for accuracy and objectivity and reviewed to ensure it delivers reliable and actionable insights. It is reviewed and edited by research management and is approved by the Chief Research Officer; no individual or organization outside of Ventana Research reviews any Analyst Perspective before it is published. If you have any issue with an Analyst Perspective, please email them to ChiefResearchOfficer@ventanaresearch.com

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