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        Ventana Research Analyst Perspectives

        The technology landscape for enterprise IT faces a daunting challenge: complexity. As systems grow more intricate, organizations must actively seek ways to simplify the technology stack. This process, known as decomplexification, is crucial for enhancing efficiency, security and collaboration within an enterprise.

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        Topics: Cloud Computing, IT Service Management, Digital Technology, Digital Security, DevOps and Platforms, IoT and Edge Computing, Intelligent Automation, ITOps, IaC, CI/CD, SASE

        Enterprises are increasingly recognizing the need to streamline operations for efficiency, agility and innovation. This has led to various “operations” or “Ops” initiatives, each focusing on a specific aspect of enterprise IT. From software development and data analytics to IT and cloud management, these Ops groups are transforming the way enterprises operate and compete.

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        Topics: Analytics, Cloud Computing, Digital Technology, data operations, digital finance, Digital Security, Observability, Analytic Operations, DevOps and Platforms, ITOps, CloudOps, Machine Learning Operations, MLOps, SecOps, ProjectOps, AIOps, NetOps, DevSecOps, SecFinOps

        The migration of on-premises applications to the cloud has become more than just a technological shift; it’s a strategic imperative for enterprises. This transition, driven by the need for competitiveness, agility and responsiveness in a rapidly evolving business environment that operates at the speed of digital, is not a simple task. It requires a careful balance between the technology roadmap and the strategic business objectives of the organization.

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        Topics: Cloud Computing, Digital Technology, CloudOps, Migration

        The increasing importance of intelligent operational applications driven by artificial intelligence (AI) is blurring the lines that have traditionally divided the requirements between operational and analytic data platforms. Operational data platforms have traditionally been deployed to support applications targeted at business users and decision-makers to run the business, with analytic data platforms typically supporting applications used by data and business analysts to analyze the business.

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        Topics: embedded analytics, Cloud Computing, Analytics & Data, operational data platforms, Analytic Data Platforms, AI and Machine Learning

        Ventana Research recently announced its 2024 Market Agenda for Digital Technology. This agenda is designed to provide expertise to enterprises across various industries, helping them prioritize technology investments that enhance workforce effectiveness, customer engagement and enterprise agility. Digital Technology is especially important for CIO and Chief Digital Officers looking to rationalize and modernize their IT portfolio. Our expertise will see a significant expansion on this topic in...

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        Topics: Business Continuity, Cloud Computing, IT Service Management, Digital Technology, Digital Security, Observability, DevOps and Platforms, IoT and Edge Computing, Intelligent Automation, ITOps

        In recent years, many enterprises have migrated data platform workloads from on-premises infrastructure to cloud environments, attracted by the promised benefits of greater agility and lower costs. The scale of cloud data platform adoption is illustrated by Ventana Research’s Data Lakes Dynamic Insights research: For two-thirds (66%) of participants, the primary data platform used for analytics is cloud based. As the quantity and importance of the data platform workloads deployed in the cloud...

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        Topics: business intelligence, Cloud Computing, data operations, robotic automation, Analytics & Data, Analytic Data Platforms, AI and Machine Learning

        Discussion about potential deployment locations for analytics and data workloads is often based on the assumption that, for enterprise workloads, there is a binary choice between on-premises data centers and public cloud. However, the low-latency performance or sovereignty characteristics of a significant and growing proportion of workloads make them better suited to data and analytics processing where data is generated rather than a centralized on-premises or public cloud environment. ...

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        Topics: Cloud Computing, Internet of Things, Data, Digital Technology, Analytics & Data, operational data platforms, Analytic Data Platforms, AI and Machine Learning

        I recently discussed how fashion has a surprisingly significant role to play in the data market as various architectural approaches to data storage and processing take turns enjoying a phase in the limelight. Pendulum swing is a theory of fashion that describes the periodic movement of trends between two extremes, such as short and long hemlines or skinny and baggy/flared trousers. Pendulum swing theory is similarly a factor in data technology trends, with an example being the oscillation...

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        Topics: Analytics, Cloud Computing, Data Management, Data, Digital Technology, data operations, Analytics & Data, AI and Machine Learning

        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, Analytics & Data, operational data platforms, Analytic Data Platforms, AI and Machine Learning

        I recently articulated some of the reasons why IT teams can fail to deliver on the business requirements for data and analytics projects. This is an age-old and multifaceted problem that is not easily solved. Organizations have a role to play in alleviating the issue by ensuring that their business processes and project planning support a collaborative approach in which business and IT professionals work together. Data and analytics product vendors can also help by delivering products that are...

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