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        David Menninger's Analyst Perspectives

        Ventana Research recently announced its 2023 Market Agenda for Analytics, continuing the guidance we have offered for nearly two decades to help organizations derive optimal value from technology investments to improve business outcomes.

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        Topics: embedded analytics, Analytics, Business Intelligence, Data, Digital Technology, natural language processing, Process Mining, Analytics & Data, Collaborative & Conversational Computing

        I’m proud to share Ventana Research’s 2023 Market Agenda for Digital Technology. Our focus in this agenda is to deliver expertise to help organizations prioritize technology investments that improve customer, partner and workforce experiences while also increasing organizational effectiveness and agility.

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        Topics: Analytics, Cloud Computing, Internet of Things, Data, Digital Technology, blockchain, mobile computing, extended reality, AI & Machine Learning, robotic automation, Collaborative & Conversational Computing

        Organizations conduct data analysis in many ways. The process can include multiple spreadsheets, applications, desktop tools, disparate data systems, data warehouses and analytics solutions. This creates difficulties for management to provide and maintain updated information across multiple departments. Our Analytics and Data Benchmark Research shows that organizations face a variety of challenges with analytics and business intelligence. One-third of participants find it difficult to integrate...

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        Topics: embedded analytics, Analytics, Business Intelligence, natural language processing, AI & Machine Learning

        For far too long, business intelligence technologies have left the rest of the exercise to the reader. Many of these tools do an excellent job providing information in an interactive way that lets organizations dive into the data and learn a lot about what has happened across all aspects of the business. More recently, many of these tools have added augmented intelligence capabilities that help explain why things happened. But rarely did any of these tools provide information about what to do...

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        Topics: business intelligence, Analytics, Digital Technology, AI & Machine Learning, Analytics & Data

        Analytics processes are all about how organizations use data to create metrics that help manage and improve operations. Yet, the discipline applied to analytics processes seems to be lacking compared to data processes. I’ve pointed out that the weak link in data governance is often analytics. Organizations can also do a better job tying AnalyticOps to DataOps and do more to define and manage metrics. Our research has shown that creating and managing metrics in a semantic model improves...

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

        In previous perspectives in this series, I’ve discussed some of the realities of cloud computing including costs, hybrid and multi-cloud configurations and business continuity. This perspective examines the realities of security and regulatory concerns associated with cloud computing. These issues are often cited by our research participants as reasons they are not embracing the cloud. To be fair, the majority of our research participants are embracing the cloud. However, among those that have...

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        Topics: Analytics, Business Intelligence, Cloud Computing, Data Governance, Digital Technology, AI & Machine Learning, Analytics & Data, Governance & Risk

        Recently, I suggested you need to “mind the gap” between data and analytics. This perspective addresses another gap — the gap in skills between business intelligence (BI) and artificial intelligence/machine learning (AI/ML).

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

        Embedded business intelligence (BI) continues to transform the business landscape, enabling organizations to quickly interpret data and convert it into actionable insights. It allows organizations to extract information in real time and answer wide-ranging business questions. Embedding analytics helps tackle the issue of extracting information from data which is a time-consuming process. Our research shows organizations spend more time cleaning and optimizing data for analysis rather than...

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        Topics: embedded analytics, Analytics, Business Intelligence, natural language processing, Streaming Analytics, AI & Machine Learning

        In today’s data-driven world, organizations need real-time access to up-to-date, high-quality data and analysis to keep pace with changing market dynamics and make better strategic decisions. By mining meaningful insights from enterprise data quickly, they gain a competitive advantage in the market. Yet, organizations face a multitude of challenges when transitioning into an analytics-driven enterprise. Our Analytics and Data Benchmark Research shows that more than one-quarter of organizations...

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        Topics: embedded analytics, Analytics, Business Intelligence, IBM, IBM Watson, AI & Machine Learning

        In my previous perspectives on cloud computing, I addressed some of the realities of cloud costs as well as hybrid and multi-cloud architectures. In the midst of the pandemic, my colleague, Mark Smith, authored a series of perspectives on considerations for business continuity in general, beginning with this look at some of the investments organizations must make to mitigate the risk of business disruptions. In this perspective, I’d like to address some of the realities of business continuity...

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        Topics: Business Continuity, Cloud Computing, Digital Technology, digital business
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