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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, Collaborative & Conversational Computing, Analytics and Data


Ventana Research recently announced its 2023 research agenda for the Office of Revenue, continuing the guidance we’ve offered for nearly two decades to help organizations realize their optimal value from applying technology to improve business outcomes. Chief Sales and Revenue Officers face an imperative to manage their sales and revenue organizations, but they don’t always have the guidance they...

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Topics: Sales, Analytics, Internet of Things, Data, Sales Performance Management, Digital Technology, Digital Commerce, Conversational Computing, mobile computing, Subscription Management, extended reality, intelligent sales, partner management, AI and Machine Learning


Ventana Research recently announced its Market Agenda in the expertise area of Customer Experience. CX has emerged as a way for organizations to demonstrate value and stand out in the marketplace. The technology underlying modern CX is transitioning from tools that are based on communication to those centered on data analysis and process automation. This allows organizations to build great...

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Topics: Customer Experience, Voice of the Customer, CEM, Self-service, Analytics, Contact Center, agent management, AI and Machine Learning


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, robotic automation, Collaborative & Conversational Computing, AI and Machine Learning


Ventana Research has announced its market agenda for 2023, continuing a 20-year tradition of credibility and trust in our objective efforts to educate and guide the technology market. Our research and insights are backed by our expertise and independence, as we do not share our Market Agenda or our market research – including analyst and market perspectives – with any external party before it is...

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Topics: Customer Experience, Human Capital Management, Marketing, Office of Finance, Analytics, Data, Digital Technology, Operations & Supply Chain, Office of Revenue


In today’s organization, the myriad of analytics and permutations of dashboards challenge workers’ ability to take contextual actions efficiently. Unfortunately, conventional wisdom for investing in analytics does not recognize the benefits of empowering the workforce to understand the situation, examine options and work together to make the best possible decision.

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Topics: business intelligence, Analytics, Data, Digital Technology, analytic data platforms, Analytics and Data, AI and Machine Learning


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...

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Topics: embedded analytics, Analytics, Business Intelligence, natural language processing, AI and 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...

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


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...

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Topics: Analytics, Business Intelligence, Data Governance, Data, Digital Technology, Analytics and 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...

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


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, Analytics and Data, AI and Machine Learning


The technology industry has established itself as a pivotal force in its ability to help organizations become more intelligent and automated. But doing so has required a journey of epic proportions for most organizations that have had to endure a transition of competencies and skills that was, in many places, transitioned to consulting firms who were hired appropriately to manage changes....

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Topics: Customer Experience, Human Capital Management, Marketing, Office of Finance, Analytics, Data, Digital Technology, Operations & Supply Chain, Office of Revenue


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...

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Topics: embedded analytics, Analytics, Business Intelligence, natural language processing, Streaming Analytics, AI and 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...

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


If you’ve ever been to London, you are probably familiar with the announcements on the London Underground to “mind the gap” between the trains and the platform. I suggest we also need to mind the gap between data and analytics. These worlds are often disconnected in organizations and, as a result, it limits their effectiveness and agility.

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Topics: embedded analytics, Analytics, Business Intelligence, Data Governance, Data Management, data operations, Analytics and Data


Artificial intelligence and machine learning are valuable to data and analytics activities. Our research shows that organizations using AI/ML report gaining competitive advantage, improving customer experiences, responding faster to opportunities and threats and improving the bottom line with increased sales and lower costs. No wonder nearly 9 in 10 (87%) research participants report using AI/ML...

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Topics: 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...

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


Process mining is defined as the analysis of application telemetry including log files, transaction data and other instrumentation to understand and improve operational processes. Log data provides an abundance of information about what operations are occurring, the sequences involved in the processes, how long the processes are taking and whether or not the processes are completed successfully....

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


Business intelligence has evolved. It now includes a spectrum of analytics, one of the most promising of which has been described as augmented intelligence. Some organizations have used the term to describe the practical reality that artificial intelligence with machine learning is not replacing human intelligence, but augmenting it. The term also represents the application of AI/ML to make...

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Topics: Analytics, Business Intelligence, natural language processing, Collaborative & Conversational Computing, Analytics and Data, AI and Machine Learning


When I looked at the state of analytics recently, it was clear that analytics are not as widely deployed within organizations as they should be. Only 23% of participants in our Analytics and Data Benchmark Research reported that more than one-half of their organization’s workforce are using analytics. There are many elements to becoming a data-driven organization, as my colleague Matt Aslett...

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Topics: embedded analytics, Analytics, Analytics and Data


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