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        Ventana Research Analyst Perspectives

        I previously discussed the trust and accuracy limitations of large language models, suggesting that data and analytics vendors provide guidance about potentially inaccurate results and the risks of creating a misplaced level of trust. In the months that have followed, we are seeing some clarity from these vendors about the approaches organizations can take to increase trust and accuracy when developing applications that incorporate generative AI, including fine-tuning and prompt engineering. It...

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        Topics: Analytics, Business Intelligence, Data, Digital Technology, natural language processing, Analytics & Data, operational data platforms, Analytic Data Platforms, AI and Machine Learning

        I previously described how Databricks had positioned its Lakehouse Platform as the basis for data engineering, data science and data warehousing. The lakehouse design pattern provides a flexible environment for storing and processing data from multiple enterprise applications and workloads for multiple use cases. I assert that by 2025, 8 in 10 current data lake adopters will invest in data lakehouse architecture to improve the business value generated from the accumulated data.

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        Topics: Analytics, Business Intelligence, Data Governance, Data Management, Data, Digital Technology, Analytics & Data, Analytic Data Platforms, AI and Machine Learning

        I am happy to share insights gleaned from our latest Buyers Guide, an assessment of how well vendors’ offerings meet buyers’ requirements. The Ventana Research 2023 Augmented Analytics Buyers Guide is the distillation of a year of market and product research by Ventana Research. Drawing on our Benchmark Research, we apply a structured methodology built on evaluation categories that reflect the real-world criteria incorporated in a request for proposal to Analytics and Data vendors supporting...

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        Topics: Analytics, AI and Machine Learning, Augmented Analytics

        The 2023 Ventana Research Buyers Guide for Augmented Analytics research enables me to provide observations about how the market has advanced. 

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        Topics: Analytics, AI and Machine Learning, Augmented Analytics

        The data platforms market may appear to have little or nothing to do with haute couture, but it is one of the data sectors most strongly influenced by the fickle finger of fashion. In recent years, various architectural approaches to data storage and processing have enjoyed a phase in the limelight, including data warehouse, data mart, data hub, data lake, cloud data warehouse, object storage, data lakehouse, data fabric and data mesh. These approaches are often heralded as the next big thing,...

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        Topics: Cloud Computing, Data Governance, Data Management, Data, Digital Technology, data operations, Analytics & Data, Streaming Data & Events, operational data platforms, Analytic Data Platforms, AI and Machine Learning

        Despite a focus on being data-driven, many organizations find that data and analytics projects fail to deliver on expectations. These initiatives can underwhelm for many reasons, because success requires a delicate balance of people, processes, information and technology. Small deviations from perfection in any of those factors can send projects off the rails.

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        Topics: Analytics, Business Intelligence, Data Management, Data, Digital Technology, data operations, AI and Machine Learning

        Organizations are continuously combining data from diverse and siloed sources for analytical, artificial intelligence and machine learning projects. As the volume of data grows, it becomes challenging for organizations to manage and keep current to extract valuable insights in a timely manner.

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        Topics: Analytics, Business Intelligence, AI and Machine Learning, Data Analytics

        I have written before about the rising popularity of the data fabric approach for managing and governing data spread across distributed environments comprised of multiple data centers, systems and applications. I assert that by 2025, more than 6 in 10 organizations will adopt data fabric technologies to facilitate the management and processing of data across multiple data platforms and cloud environments. The data fabric approach is also proving attractive to vendors, including Microsoft, as a...

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        Topics: Analytics, Business Intelligence, Cloud Computing, Data Governance, Data Management, Data, Digital Technology, Analytics & Data, Analytic Data Platforms, AI and Machine Learning

        Governance, risk management and compliance are essential tactics for a successful organization. Effective GRC practices help organizations achieve business objectives, mitigate risks and ensure compliance with laws and regulations. As a chief information officer or IT leader, it is important to evaluate new technologies and determine their impact on the business, including whether they fit within the scope of current GRC programs and processes.

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        Topics: Data Governance, Digital Business, Digital Security, Governance & Risk, AI and Machine Learning

        The world of human capital management (HCM) technology, and tech in general, is buzzing with excitement over the potential of generative artificial intelligence (GenAI). Startups, especially, are releasing software at seemingly breakneck speed, and larger vendors, specifically the platform providers, have been releasing their own net-new or enhanced features and functionality. We’ve all read that GenAI, and the practical application of large language models (LLMs), are the technological...

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        Topics: Human Capital Management, AI and Machine Learning
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        • 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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