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        Analyst Perspectives

        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

        At one point, analytics and business intelligence were considered non-mission critical activities. One of the primary concerns in designing analytics systems was to ensure they didn’t interfere with or draw computing resources away from operational systems. But today, analytical systems are integral to many aspects of operations. More than 9 in 10 participants in our Analytics and Data Benchmark Research reported analytics had improved activities and processes. However, most analytics and BI...

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

        I recently wrote about the various technologies used by organizations to process and analyze data in real time. I explained that while the terms streaming data and events and streaming analytics are often used interchangeably, they are separate disciplines that make use of common underlying concepts and technologies such as events, event brokers and event-driven architecture. Confluent’s acquisition of Immerok earlier this year provided a reminder of this fact. Confluent is one of the most...

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        Topics: Analytics, Cloud Computing, Data Governance, Data, Digital Technology, Streaming Analytics, Streaming Data & Events

        If I had a magic wand, I would want to add scenario evaluation to all business intelligence tools on the market. I have previously written about the need to make intelligent decisions with decision intelligence. The data and analytics markets have evolved so that organizations have far greater capabilities to utilize data in decision-making processes. While there is some convergence around the concept of decision intelligence, there are still several “islands” of decision-making. Analyzing...

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        Topics: Analytics, Business Intelligence, Business Planning, Digital Technology, Analytics & Data

        The current market landscape of data and analytics is undergoing rapid evolution, presenting organizations with a wide array of challenges and opportunities. As data sources and warehouses steadily migrate to the cloud, a significant number of organizations still depend on conventional tools. This reliance on legacy systems hinders the seamless accessibility and adoption of analytics and business intelligence within business processes. Organizations are increasingly turning to embedded...

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        Topics: embedded analytics, Analytics, Business Intelligence, Streaming Analytics, AI and Machine Learning

        A century ago, the big breakthrough in telephones was the ability to dial your party’s number directly. Dialing became necessary when enough people had telephones to require a shift from people-assisted to fully automated connections. But direct dialing was only a local option – you still needed an operator to make long-distance calls. In the 1920s, commenting on their forecast for the expected growth of long-distance calling, the analysts at Bell Laboratories concluded that by midcentury, the...

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        Topics: Office of Finance, Analytics, Business Planning, AI and Machine Learning

        Real-time business is a modern phenomenon, and business transformation has accelerated many business events in recent years. However, the execution of business events has always occurred in real time. Rather, it is the processing of the data related to business events that has accelerated instead of the event itself.

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        Topics: Analytics, Data, Streaming Analytics, Streaming Data & Events

        It is a mark of the rapid, current pace of development in artificial intelligence (AI) that machine learning (ML) models, until recently considered state of the art, are now routinely being referred to by developers and vendors as “traditional.” Generative AI, and large language models (LLMs) in particular, have taken the AI world by storm in the past year, automating and accelerating the development of content, including text, digital images, audio and video, as well as computer programs and...

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

        As I have previously explained, we expect an increased demand for intelligent operational applications infused with the results of analytic processes, such as personalization and artificial intelligence-driven recommendations. These systems rely on the analysis of data in the operational data platform to accelerate worker decision-making or improve customer experience.

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        Topics: Analytics, Data, Digital Technology, Streaming Analytics, Analytics & Data, Streaming Data & Events, operational data platforms, AI and Machine Learning

        The publication of Ventana Research’s 2023 Operational Data Platforms Value Index earlier this year highlighted the importance of incorporating analytic processing into operational applications to deliver personalization and recommendations for workers, partners and customers. This importance is being accelerated by interest in generative AI, especially large language models. The emergence of intelligent applications has impacted the requirements for operational data platforms with the need to...

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        Topics: Analytics, Cloud Computing, Data, Digital Technology, Analytics & Data, operational data platforms, Analytic Data Platforms, 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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