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        Matt Aslett's Analyst Perspectives

        Ventana Research recently announced its 2024 Market Agenda for Analytics and Data, continuing the guidance we have offered for two decades to help enterprises derive optimal value and improve business outcomes.

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        Topics: embedded analytics, Business Intelligence, Data Governance, Data Management, natural language processing, data operations, Process Mining, Streaming Analytics, AI & Machine Learning, Analytics & Data, Streaming Data & Events, analytic data platforms, Operational Data Platforms

        The phrase ‘big data’ may have largely gone out of fashion, but the concept of storing and processing all relevant data continues to be important for enterprises seeking to be more data-driven. Doing so requires analytic data platforms capable of storing and processing data in multiple formats and data models. This will be an important focus for the forthcoming Data Platforms Buyer’s Guide 2024. 

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

        I previously described how Oracle had positioned its database portfolio to address any and all data platform requirements. The caveat to that statement at the time was that any organization wanting to take advantage of the company’s flagship Oracle Autonomous Database could only do so using Oracle Cloud Infrastructure (OCI) cloud computing service, their own datacenter or a hybrid cloud environment. The widespread popularity of Oracle Database and the advanced automation capabilities delivered...

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        Topics: Analytics, Business Intelligence, Cloud Computing, Data Management, Data, Digital Technology, AI & Machine Learning, Analytics & Data, analytic data platforms, Operational Data Platforms

        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, AI & Machine Learning, Analytics & Data, analytic data platforms, Operational Data Platforms

        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, AI & Machine Learning, Analytics & Data, analytic data platforms

        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 & Machine Learning

        The data platforms market has traditionally been divided between products specifically designed to support operational or analytic workloads, with other market segments having emerged in recent years for data platforms targeted specifically at data science and machine learning (ML), as well as real-time analytics. More recently, we have seen vendor strategies evolving to provide a more consolidated approach, with data platforms designed to address a combination of analytics and data science, as...

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        Topics: Analytics, Business Intelligence, Cloud Computing, Data, Digital Technology, AI & Machine Learning, Analytics & Data, analytic data platforms, Operational Data Platforms

        The recent publication of our Value Index research highlights the impact of intelligent applications on the operational data platforms sector. While we continue to believe that, for most use cases, there is a clear, functional requirement for either analytic or operational data platforms, recent growth in the development of intelligent applications infused with the results of analytic processes, such as personalization and artificial intelligence (AI)-driven recommendations, has increasing...

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        Topics: Analytics, Business Intelligence, Cloud Computing, Data, Digital Technology, Analytics & Data, analytic data platforms, Operational Data Platforms

        I have previously written about growing interest in the data lakehouse as one of the design patterns for delivering hydroanalytics analysis of data in a data lake. Many organizations have invested in data lakes as a relatively inexpensive way of storing large volumes of data from multiple enterprise applications and workloads, especially semi- and unstructured data that is unsuitable for storing and processing in a data warehouse. However, early data lake projects lacked structured data...

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        Topics: Business Intelligence, Data Governance, Data Management, Data, AI & Machine Learning, Streaming Data & Events, analytic data platforms

        Ventana Research’s Data Lakes Dynamics Insights research illustrates that while data lakes are fulfilling their promise of enabling organizations to economically store and process large volumes of raw data, data lake environments continue to evolve. Data lakes were initially based primarily on Apache Hadoop deployed on-premises but are now increasingly based on cloud object storage. Adopters are also shifting from data lakes based on homegrown scripts and code to open standards and open...

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        Topics: Business Intelligence, Cloud Computing, Data Governance, Data Management, Data, data operations, AI & Machine Learning, Analytics & Data, analytic data platforms, Operational Data Platforms
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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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