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        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, Analytics, Business Intelligence, Data Governance, Data Management, natural language processing, data operations, Process Mining, Streaming Analytics, Streaming Data Events, analytic data platforms, Analytics and Data

        In my past perspectives, I’ve written about the evolution from data at rest to data in motion and the fact that you can’t rely on dashboards for real-time analytics. Organizations are becoming more and more event-driven and operating based on streaming data. As well, analytics are becoming more and more intertwined with operations. More than one-fifth of organizations (22%) describe their analytics workloads as real time in our Data and Analytics Benchmark Research and nearly half (47%) of...

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        Topics: Analytics, Business Intelligence, Data, Digital Technology, Streaming Analytics, Streaming Data Events, Analytics and 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

        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

        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

        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, Streaming Data Events, Analytics and Data, AI and Machine Learning

        Organizations are becoming increasingly aware of the potential value that can be gained by processing big data. As data sources grow, it becomes important to have tools and methods to effectively process, analyze and visualize this information from disparate systems and warehouses.

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        Topics: business intelligence, embedded analytics, Analytics, Streaming Analytics

        Success with streaming data and events requires a more holistic approach to managing and governing data in motion and data at rest. The use of streaming data and event processing has been part of the data landscape for many decades. For much of that time, data streaming was a niche activity, however, with standalone data streaming and event-processing projects run in parallel with existing batch-processing initiatives, utilizing operational and analytic data platforms. I noted that there has...

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        Topics: Analytics, Data, Digital Technology, Streaming Analytics, Streaming Data Events, analytic data platforms, Analytics and 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 and Machine Learning

        As I recently pointed out, process mining has emerged as a pivotal technology for data-driven organizations to discover, monitor and improve processes through use of real-time event data, transactional data and log files. With recent advancements, process mining has become more efficient at discovering insights in complex processes using algorithms and visualizations. Organizations use it to better understand the current state of systems and business processes. It is also used to enable ...

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        Topics: Analytics, Business Intelligence, Process Mining, Streaming Analytics, AI and Machine Learning

        I recently wrote about the need for organizations to take a holistic approach to the management and governance of data in motion alongside data at rest. As adoption of streaming data and event processing increases, it is no longer sufficient for streaming data projects to exist in isolation. Data needs to be managed and governed regardless of whether it is processed in batch or as a stream of events. This requirement has resulted in established data management vendors increasing their focus on...

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        Topics: Big Data, Cloud Computing, Data Governance, Streaming Analytics, Streaming Data Events

        I have written recently about increased demand for data-intensive applications infused with the results of analytic processes, such as personalization and artificial intelligence (AI)-driven recommendations. Almost one-quarter of respondents (22%) to Ventana Research’s Analytics and Data Benchmark Research are currently analyzing data in real time, with an additional 10% analyzing data every hour. There are multiple data platform approaches to delivering real-time data processing and analytics...

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        Topics: Cloud Computing, Data, Streaming Analytics, Streaming Data Events, analytic data platforms, Analytics and Data

        Organizations are managing and analyzing large datasets every day, identifying patterns and generating insights to inform decisions. This can provide numerous benefits for an organization, such as improved operational efficiency, cost optimization, fraud detection, competitive advantage and enhanced business processes. By bringing the right, actionable data to the right user, organizations can potentially speed up processes and make more effective operational decisions.

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

        I recently noted that as demand for real-time interactive applications becomes more pervasive, the use of streaming data is becoming more mainstream. Streaming data and event processing has been part of the data landscape for many decades, but for much of that time, data streaming was a niche activity. Although adopted in industry segments with high-performance, real-time data processing and analytics requirements such as financial services and telecommunications, data streaming was far less...

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        Topics: Big Data, Data, Streaming Analytics, Streaming Data Events, Analytics and Data

        I often use the term “analytics” to refer to a broad set of capabilities, deliberately broader than business intelligence. In this Perspective, I’d like to share what decision-makers should consider as they evaluate the range of analytics requirements for their organization.

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        Topics: Business Intelligence, natural language processing, Streaming Analytics, Analytics and Data, AI and Machine Learning

        Streaming data has been part of the industry landscape for decades but has largely been focused on niche applications in segments with the highest real-time data processing and analytics performance requirements, such as financial services and telecommunications. As demand for real-time interactive applications becomes more pervasive, streaming data is becoming a more mainstream pursuit, aided by the proliferation of open-source streaming data and event technologies, which have lowered the cost...

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        Topics: Data, Streaming Analytics, Streaming Data Events

        When joining Ventana Research, I noted that the need to be more data-driven has become a mantra among large and small organizations alike. Data-driven organizations stand to gain competitive advantage, responding faster to worker and customer demands for more innovative, data-rich applications and personalized experiences. Being data-driven is clearly something to aspire to. However, it is also a somewhat vague concept without clear definition. We know data-driven organizations when we see them...

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        Topics: embedded analytics, Analytics, Business Intelligence, Data Governance, Data Integration, Data, Digital Technology, natural language processing, data lakes, data operations, Streaming Analytics, Streaming Data Events, Analytics and Data, AI and Machine Learning

        Organizations are continuously increasing the use of analytics and business intelligence to turn data into meaningful and actionable insights. Our Analytics and Data Benchmark Research shows some of the benefits of using analytics: Improved efficiency in business processes, improved communication and gaining a competitive edge in the market top the list. With a unified BI system, organizations can have a comprehensive view of all organizational data to better manage processes and identify...

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        Topics: business intelligence, embedded analytics, Data Governance, Data Management, natural language processing, data operations, Streaming Analytics, AI and Machine Learning

        Organizations have been using data virtualization to collect and integrate data from various sources, and in different formats, to create a single source of truth without redundancy or overlap, thus improving and accelerating decision-making giving them a competitive advantage in the market. Our research shows that data virtualization is popular in the big data world. One-quarter (27%) of participants in our Data Lake Dynamic Insights Research reported they were currently using data...

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

        I have written previously that the world of data and analytics will become more and more centered around real-time, streaming data. Data is created constantly and increasingly is being collected simultaneously. Technology advances now enable organizations to process and analyze information as it is being collected to respond in real time to opportunities and threats. Not all use cases require real-time analysis and response, but many do, including multiple use cases that can improve customer...

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        Topics: business intelligence, Analytics, Internet of Things, Data, Digital Technology, Streaming Analytics, Streaming Data Events, Analytics and Data, AI and Machine Learning

        Organizations of all sizes are dealing with exponentially increasing data volume and data sources, which creates challenges such as siloed information, increased technical complexities across various systems and slow reporting of important business metrics. Migrating to the cloud does not solve the problems associated with performing analytics and business intelligence on data stored in disparate systems. Also, the computing power needed to process large volumes of data consists of clusters of...

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        Topics: Analytics, Business Intelligence, Data Integration, Data, data lakes, data operations, Streaming Analytics, AI and Machine Learning

        How does your organization define and display its metrics? I believe many organizations are not defining and displaying metrics in a way that benefits them most. If an organization goes through the trouble of measuring and reporting on a metric, the analysis ought to include all the information needed to evaluate that metric effectively. A number, by itself, does not provide any indication of whether the result is good or bad. Too often, the reader is expected to understand the difference, but...

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        Topics: Analytics, Business Intelligence, Internet of Things, Data, Digital Technology, Streaming Analytics, AI and Machine Learning

        Our research shows that nearly all financial service organizations (97%) consider it important to accelerate the flow of information and improve responsiveness. Even just a few years ago, capturing and evaluating this information quickly was much more challenging, but with the advent of streaming data technologies that capture and process large volumes of data in real time, financial service organizations can quickly turn events into valuable business outcomes in the form of new products and...

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        Topics: Analytics, Internet of Things, Data, Digital Technology, Streaming Analytics

        The work environment today demands that your organization advances the efficiency to execute business processes for continuous operations to have a positive impact on business performance. The capability to be responsive to any range of minor to disruptive business events is required to support business continuity and level of organizational readiness to meet the needs of digital business. Ventana Research asserts that in 2025, one-quarter of organizations will remain digitally ineffective in...

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        Topics: Customer Experience, Voice of the Customer, embedded analytics, Analytics, Business Intelligence, Cloud Computing, Contact Center, Data, Digital Technology, Operations & Supply Chain, Enterprise Resource Planning, Digital transformation, natural language processing, continuous supply chain, agent management, Process Mining, Streaming Analytics, Experience Management, AI and Machine Learning

        Access to external data can provide a competitive advantage. Our research shows that more than three-quarters (77%) of participants consider external data to be an important part of their machine learning (ML) efforts. The most important external data source identified is social media, followed by demographic data from data brokers. Organizations also identified government data, market data, environmental data and location data as important external data sources. External data is not just part...

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        Topics: Analytics, Business Intelligence, Internet of Things, Data, Digital Technology, Lease Management, Streaming Data, Streaming Analytics, AI and Machine Learning

        Subscription management and billing services help organizations offer unique benefits and enhance delivery to customers. By making services more personalized, organizations can acquire – and retain – more customers.

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        Topics: Sales, Office of Finance, Continuous Planning, embedded analytics, Analytics, Business Intelligence, Business Planning, Product Information Management, Digital Commerce, Operations & Supply Chain, Enterprise Resource Planning, ERP and Continuous Accounting, natural language processing, revenue and lease accounting, continuous supply chain, Subscription Management, partner management, Process Mining, Streaming Analytics, Supplier Relationship Management, AI and Machine Learning

        Customer support operations increasingly rely on automation and complex workflow processes to reduce costs and improve experiences. Automation also allows organizations to make their service processes richer, incorporating information and staff from back offices, for example, or embedding conversational tools into contact center processes.

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        Topics: Customer Experience, embedded analytics, Analytics, Contact Center, natural language processing, agent management, Process Mining, Streaming Analytics, AI and Machine Learning

        Ventana Research recently announced its 2021 market agenda for Analytics, continuing the guidance we’ve 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, natural language processing, Process Mining, Streaming Analytics, 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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