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        Analyst Perspectives

        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

        Earlier this year I described the growing use-cases for hybrid data processing. Although it is anticipated that the majority of database workloads will continue to be served by specialist data platforms targeting operational and analytic workloads respectively, there is increased demand for intelligent operational applications infused with the results of analytic processes, such as personalization and artificial intelligence-driven recommendations. There are multiple data platform approaches to...

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        Topics: Business Intelligence, Cloud Computing, Data, Streaming Data Events, analytic data platforms, AI and Machine Learning

        A predictive finance department is one that can command technology to be more forward-looking and action-oriented while still fulfilling its core role of handling the financial elements of its organization including accounting, treasury and corporate finance. Beyond just automating rote tasks, technology also facilitates a shift toward becoming a predictive finance organization. Greater amounts of information, now available in near real time, and the increasing use of artificial intelligence...

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        Topics: Office of Finance, Business Intelligence, Data Management, Business Planning, Financial Performance Management, ERP and Continuous Accounting, 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. As computing power has increased and storage costs have decreased, the economics of collecting and...

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

        Organizations are collecting data from multiple data sources and a variety of systems to enrich their analytics and business intelligence (BI). But collecting data is only half of the equation. As the data grows, it becomes challenging to find the right data at the right time. Many organizations can’t take full advantage of their data lakes because they don’t know what data actually exists. Also, there are more regulations and compliance requirements than ever before. It is critical for...

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        Topics: Business Intelligence, Data Governance, Data Management, data operations, AI and Machine Learning

        Kinaxis recently announced it has acquired a Netherlands-based company, MPO, a cloud-based software offering that orchestrates multiparty supply chain execution. The combination is designed to enable Kinaxis to extend its concurrent planning platform to handle core elements of supply chain execution. Kinaxis acquired all the shares of MPO for approximately US$45 million, with some of the final consideration dependent on performance. MPO will continue to operate as a standalone business, but...

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        Topics: Business Intelligence, Business Planning, Operations & Supply Chain, Enterprise Resource Planning, continuous supply chain, AI and Machine Learning

        I have written about vendor efforts to use artificial intelligence (AI) and advanced analytics in their applications targeted at sales and revenue teams to improve focus and prioritize activities, both for pipeline management as well as individual opportunities. Since then, vendors have continued to innovate, and there have been more releases showcasing efforts to aid sales and revenue. And with this continuing innovation, we believe that by 2026, two-thirds of revenue leaders will begin...

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        Topics: 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 business intelligence and analytics tools more powerful and easier to use. It’s this latter usage that I...

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

        Organizations do not live in a vacuum and things happening outside their walls have a direct impact on how they perform. So, it is essential for them to incorporate external data in their forecasting, planning and budgeting, especially for predictive analytics and machine learning (ML) to support artificial intelligence (AI). I use the term external data to include any information about the world outside an organization (including economic and market statistics), competitors (such as pricing...

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        Topics: Office of Finance, Business Planning, Financial Performance Management, AI and Machine Learning

        Zoho presented analysts with a deep look at its strategy and roadmap at its July analyst conference, describing how it intends to meld its many business applications together through integration at the level of the platform. The company, which is privately owned and funded, has generally sought to build its own tools rather than buy or partner. This approach has allowed the firm to create a suite of tightly linked tools that share a common interface.

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        Topics: Customer Experience, Voice of the Customer, Data, AI and Machine Learning

        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

        The analytics and business intelligence market landscape continues to grow as more organizations seek robust tools and capabilities to visualize and better understand data. BI systems are used to perform data analysis, identify market trends and opportunities and streamline business processes. They can collect and combine data from internal and external systems to present a holistic view.

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        Topics: Analytics, Business Intelligence, Data Governance, Data Management, Analytics and Data, AI and Machine Learning

        Anaplan offers a cloud-based business planning platform that incorporates a modeling and calculation engine. The tool makes it relatively easy to add or expand the scope of plans that can be connected and monitored on a single platform. This Integrated Business Planning (IBP) approach enables organizations to use the software for financial planning or budgeting, sales, supply chain, workforce, marketing and IT planning. These are the types of plans in which companies often need to create models...

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        Topics: Office of Finance, Continuous Planning, Business Intelligence, Business Planning, Financial Performance Management, continuous supply chain, AI and Machine Learning

        I recently explained how emerging application requirements were expanding the range of use cases for NoSQL databases, increasing adoption based on the availability of enhanced functionality. These intelligent applications require a close relationship between operational data platforms and the output of data science and machine learning projects. This ensures that machine learning and predictive analytics initiatives are not only developed and trained based on the relationships inherent in...

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        Topics: Business Intelligence, Data, analytic data platforms, AI and Machine Learning

        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

        Organizations are collecting vast amounts of data every day, utilizing business intelligence software and data visualization to gain insights and identify patterns and errors in the data. Making sense of these patterns can enable an organization to gain an edge in the marketplace and plan more strategically.

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

        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

        OneStream offers a platform designed to serve the needs of accounting and financial planning and analysis organizations. The software handles financial close and consolidation, planning and budgeting, analysis and reporting. For me, the most significant announcement at the company’s recent user conference was the unveiling of its Sensible ML (Machine Learning) offering, which is in limited general release. I’ve commented on the importance of artificial intelligence in business applications, and...

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        Topics: Business Planning, Financial Performance Management, ERP and Continuous Accounting, AI and Machine Learning

        I recently wrote about the growing range of use cases for which NoSQL databases can be considered, given increased breadth and depth of functionality available from providers of the various non-relational data platforms. As I noted, one category of NoSQL databases — graph databases — are inherently suitable for use cases that rely on relationships, such as social media, fraud detection and recommendation engines, since the graph data model represents the entities and values and also the...

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        Topics: business intelligence, Analytics, Cloud Computing, Data, Digital Technology, Analytics and Data, AI and Machine Learning

        A few years ago – somewhat tongue in cheek – I began using the term “data pantry” to describe a type of data store that’s part of a business application platform, created for a specific set of users and use cases. It’s a data pantry because, unlike a general-purpose data store such as a data warehouse, everything the user needs is readily available and easily accessible, with labels that are immediately recognized and understood.

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        Topics: Data Management, Business Planning, Financial Performance Management, ERP and Continuous Accounting, 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

        I previously described the concept of hydroanalytic data platforms, which combine the structured data processing and analytics acceleration capabilities associated with data warehousing with the low-cost and multi-structured data storage advantages of the data lake. One of the key enablers of this approach is interactive SQL query engine functionality, which facilitates the use of existing business intelligence (BI) and data science tools to analyze data in data lakes. Interactive SQL query...

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        Topics: Analytics, Business Intelligence, Cloud Computing, Data, Digital Technology, data lakes, data operations, Analytics and Data, AI and Machine Learning

        I’ve never been a fan of talking about semantic models because most of the workforce probably doesn’t understand what they are, or doesn’t recognize them by name. But the findings in our recent Analytics and Data Benchmark Research have changed my mind. The research shows how important a semantic model can be to the success of data and analytics processes. Organizations that have successfully implemented a semantic model are more than twice as likely to report satisfaction with analytics (77%)...

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        Topics: Business Intelligence, Data Management, data operations, Analytics and Data, AI and Machine Learning

        Artificial intelligence using machine learning has passed through the bright, shiny object stage and software vendors are well into the process of making the concept a reality in their offerings. Ventana Research defines AI as the use of technology to process information in much the way humans do, including improving accuracy in recommendations, actions and conclusions as more data is received. I like the alternative term “augmented intelligence” because it emphasizes that these systems enhance...

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        Topics: Planning, Machine Learning, Budgeting, Business Planning, Financial Performance Management, forecasting, AI and Machine Learning

        I recently wrote about the potential benefits of data mesh. As I noted, data mesh is not a product that can be acquired, or even a technical architecture that can be built. It’s an organizational and cultural approach to data ownership, access and governance. While the concept of data mesh is agnostic to the technology used to implement it, technology is clearly an enabler for data mesh. For many organizations, new technological investment and evolution will be required to facilitate adoption...

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

        I recently described the use cases driving interest in hybrid data processing capabilities that enable analysis of data in an operational data platform without impacting operational application performance or requiring data to be extracted to an external analytic data platform. Hybrid data processing functionality is becoming increasingly attractive to aid the development of intelligent applications infused with personalization and artificial intelligence-driven recommendations. These...

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

        There is a fundamental flaw in information technology, or at least in the way it is most commonly delivered. Most technology systems are developed under the assumption that all people will use the system primarily in the same way. Sure, there are some options built in — perhaps the same action can be initiated by either clicking on a button, selecting a menu item or invoking a keyboard short-cut. The problem is that when every variation needs to be coded into the system, the prospect of...

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        Topics: Business Intelligence, Data Management, natural language processing, data operations, Analytics and Data, AI and Machine Learning

        I recently described how the operational data platforms sector is in a state of flux. There are multiple trends at play, including the increasing need for hybrid and multicloud data platforms, the evolution of NoSQL database functionality and applicable use-cases, and the drivers for hybrid data processing. The past decade has seen significant change in the emergence of new vendors, data models and architectures as well as new deployment and consumption approaches. As organizations adopted...

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        Topics: business intelligence, Analytics, Data Integration, Data, 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 recently wrote about the importance of data pipelines and the role they play in transporting data between the stages of data processing and analytics. Healthy data pipelines are necessary to ensure data is integrated and processed in the sequence required to generate business intelligence. The concept of the data pipeline is nothing new of course, but it is becoming increasingly important as organizations adapt data management processes to be more data driven.

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        Topics: Analytics, Business Intelligence, Data Governance, Data Integration, Data, Digital Technology, Digital transformation, data lakes, data operations, Streaming Data Events, Analytics and Data, 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

        For years, maybe decades, we have heard about the struggles between IT and line-of-business functions. In this perspective, we will look at some of the data from our Analytics and Data Benchmark Research about the roles of IT and line-of-business teams in analytics and data processes. We will also look at some of the disconnects between these two groups. And, by looking at how organizations are operating today and the results they are achieving, we can discern some of the best practices for...

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

        Despite widespread and increasing use of the cloud for data and analytics workloads, it has become clear in recent years that, for most organizations, a proportion of data-processing workloads will remain on-premises in centralized data centers or distributed-edge processing infrastructure. As we recently noted, as compute and storage are distributed across a hybrid and multi-cloud architecture, so, too, is the data it stores and relies upon. This presents challenges for organizations to...

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        Topics: Analytics, Business Intelligence, Data Governance, Data, data operations, AI and Machine Learning

        The various NoSQL databases have become a staple of the data platforms landscape since the term entered the IT industry lexicon in 2009 to describe a new generation of non-relational databases. While NoSQL began as a ragtag collection of loosely affiliated, open-source database projects, several commercial NoSQL database providers are now established as credible alternatives to the various relational database providers, while all the major cloud providers and relational database giants now also...

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        Topics: Analytics, Data, AI and Machine Learning

        I recently described the emergence of hydroanalytic data platforms, outlining how the processes involved in generating energy from a lake or reservoir were analogous to those required to generate intelligence from a data lake. I explained how structured data processing and analytics acceleration capabilities are the equivalent of turbines, generators and transformers in a hydroelectric power station. While these capabilities are more typically associated with data warehousing, they are now...

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        Topics: Analytics, Data Governance, Data, Digital Technology, data lakes, data operations, Streaming Data Events, AI and Machine Learning

        The use of artificial intelligence (AI) using machine learning (ML) will be the single most important trend in business software this decade because it can multiply the investment value of such applications and provide vendors an important source of differentiation to achieve a competitive advantage in what are today very mature software categories. I assert that by 2025, almost all Office of Finance software vendors will have incorporated some AI capabilities to reduce workloads and improve...

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        Topics: Office of Finance, embedded analytics, Data Management, Business Planning, Financial Performance Management, ERP and Continuous Accounting, AI and Machine Learning

        As I stated when joining Ventana Research, the socioeconomic impacts of the pandemic and its aftereffects have highlighted more than ever the differences between organizations that can turn data into insights and are agile enough to act upon it and those that are incapable of seeing or responding to the need for change. Data-driven organizations stand to gain competitive advantage, responding faster to worker and customer demands for more innovative, data-rich applications and personalized...

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

        I recently described how the data platforms landscape will remain divided between analytic and operational workloads for the foreseeable future. Analytic data platforms are designed to store, manage, process and analyze data, enabling organizations to maximize data to operate with greater efficiency, while operational data platforms are designed to store, manage and process data to support worker-, customer- and partner-facing operational applications. At the same time, however, we see...

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        Topics: embedded analytics, Analytics, Business Intelligence, Data, Digital Technology, 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

        Ventana Research recently announced its 2022 Market Agenda for the Office of Finance, continuing the guidance we have offered since 2003 on the practical use of technology for the finance and accounting department. Our insights and best practices aim to enable organizations to operate with agility and resiliency, improving performance and delivering greater value as a strategic partner.

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        Topics: Office of Finance, Business Intelligence, Collaboration, Business Planning, Financial Performance Management, ERP and Continuous Accounting, Revenue, blockchain, robotic finance, Predictive Planning, AI and Machine Learning, lease and tax accounting

        Ventana Research recently announced its 2022 Market Agenda for the Office of Revenue, continuing the guidance we have offered for nearly two decades to help organizations realize optimal value from applying technology to improve business outcomes. Chief sales and revenue officers and their associated operations teams are experts in their respective fields but may not have the guidance needed to employ technology effectively. As we look to 2022, we are focusing on the entire selling and buying...

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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

        Organizations today have huge volumes of data across various cloud and on-premises systems which keep growing by the second. To derive value from this data, organizations must query the data regularly and share insights with relevant teams and departments. Automating this process using natural language processing (NLP) and artificial intelligence and machine learning (AI/ML) enables line-of-business personnel to query the data faster, generate reports themselves without depending on IT, and...

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

        The internet is a rich source of information and is used by buyers to research new applications and offerings well before ever engaging a vendor and salesperson. Along with massive growth in offerings, this is a major reason why sales teams are facing increasing challenges to successfully sell and attain targets.

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        Topics: Sales, AI and Machine Learning

        Data lakes have enormous potential as a source of business intelligence. However, many early adopters of data lakes have found that simply storing large amounts of data in a data lake environment is not enough to generate business intelligence from that data. Similarly, lakes and reservoirs have enormous potential as sources of energy. However, simply storing large amounts of water in a lake is not enough to generate energy from that water. A hydroelectric power station is required to harness...

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

        As I noted when joining Ventana Research, the range of options faced by organizations in relation to data processing and analytics can be bewildering. When it comes to data platforms, however, there is one fundamental consideration that comes before all others: Is the workload primarily operational or analytic? Although most database products can be used for operational or analytic workloads, the market has been segmented between products targeting operational workloads, and those targeting...

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        Topics: business intelligence, Analytics, Data, data lakes, data operations, AI and Machine Learning

        With the emergence of multiple selling channels and the rise of the subscription model, the need for a unified approach to revenue planning and execution should be a priority for every organization. As I have written about in my analyst perspective Revenue Management: The Opportunity for Innovation and Optimization, this need to unify the approach and focus on alignment across all revenue supporting teams in furtherance of an organization’s objectives and targets is of key importance to ensure...

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        Topics: Sales, Customer Experience, Sales Performance Management, Subscription Management, AI and Machine Learning

        Any organization that relies heavily on a large labor force looks to automation to reduce costs, and contact centers are no exception. They handle interactions at such large scale that almost any effort to automate some part of the process can deliver measurable efficiencies. Two factors have ratcheted up attention on automating customer experience workflows: the dramatic expansion of digital interaction channels, and the development of artificial intelligence and machine learning tools to...

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        Topics: Customer Experience, Voice of the Customer, Analytics, Data Integration, Contact Center, Data, agent management, data operations, Experience Management, AI and Machine Learning

        TIBCO is a large, independent cloud-computing and data analytics software company that offers integration, analytics, business intelligence and events processing software. It enables organizations to analyze streaming data in real time and provides the capability to automate analytics processes. It offers more than 200 connectors, more than 200 enterprise cloud computing and application adapters, and more than 30 non-relational structured query language databases, relational database management...

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        Topics: embedded analytics, Analytics, Collaboration, Data Governance, Information Management, Data, Digital Technology, data lakes, AI and Machine Learning

        Talend is a data integration and management software company that offers applications for cloud computing, big data integration, application integration, data quality and master data management. The platform enables personnel to work with relational databases, Apache Hadoop, Spark and NoSQL databases for cloud or on-premises jobs. Talend data integration software offers an open and scalable architecture and can be integrated with multiple data warehouses, systems and applications to provide a...

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        Topics: Analytics, Business Intelligence, Collaboration, Data Governance, Data Preparation, Information Management, Data, Digital Technology, data lakes, AI and Machine Learning

        When migrating their communications stacks to the cloud, many organizations come face to face with a quandary: do they emphasize the business phone system and gravitate toward a unified communications vendor? Or should they focus on the specific applications needed for running their contact centers and seek out a CCaaS vendor?

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        Topics: Customer Experience, Voice of the Customer, Contact Center, agent management, AI and Machine Learning

        Enterprises looking to adopt cloud-based data processing and analytics face a disorienting array of data storage, data processing, data management and analytics offerings. Departmental autonomy, shadow IT, mergers and acquisitions, and strategic choices mean that most enterprises now have the need to manage data across multiple locations, while each of the major cloud providers and data and analytics vendors has a portfolio of offerings that may or may not be available in any given location. As...

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        Topics: Analytics, Cloud Computing, Data Governance, Data Integration, Data, Digital Technology, data lakes, data operations, 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

        When NICE acquired inContact in 2016, it began a transformation that saw it broaden its product offering and positioned itself to play a larger role in the contact center and customer experience industries. It was a prescient move, creating a firm that could supply end-to-end contact center functionality in the cloud. And it anticipated today’s market dynamic, in which NICE and its competitors are racing to define (and capitalize on) the post-contact center future.

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        Topics: Customer Experience, Voice of the Customer, Business Continuity, Analytics, Contact Center, Data, Digital transformation, agent management, Experience Management, AI and Machine Learning

        In part one of this Analyst Perspective on the use of artificial intelligence within contact center applications, we focused on the evolution — and resulting benefits — of tools embedded with AI, including ease-of-use for non-data-scientists.

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        Topics: Customer Experience, Voice of the Customer, Analytics, agent management, AI and Machine Learning

        Databricks is a data engineering and analytics cloud platform built on top of Apache Spark that processes and transforms huge volumes of data and offers data exploration capabilities through machine learning models. It can enable data engineers, data scientists, analysts and other workers to process big data and unify analytics through a single interface. The platform supports streaming data, SQL queries, graph processing and machine learning. It also offers a collaborative user interface —...

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        Topics: embedded analytics, Analytics, Business Intelligence, Collaboration, Data Governance, Information Management, Data, data lakes, AI and Machine Learning

        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

        When artificial intelligence emerged from the labs and vendors started offering it as a component of their software, many contact-center buyers shied away from it. From their point of view, AI and machine learning tools were new, expensive, relatively untested and had an uncertain use case. This stance was understandable, as contact center professionals are traditionally expected to be risk-averse when deploying technology into their operations. Contact centers are, by design, supposed to be...

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        Topics: Customer Experience, Voice of the Customer, Analytics, Contact Center, agent 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

        Alteryx is a data analytics software company that offers data preparation and analytics tools to simplify and automate data wrangling, data cleaning and modeling processes, enabling line-of-business personnel to quickly access, manipulate, analyze and output data. The platform features tools to run a variety of analytic functions such as diagnostic, predictive, prescriptive and geospatial analytics in a unified platform, and can connect to various data warehouses, cloud applications,...

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        Topics: embedded analytics, Analytics, Business Intelligence, Collaboration, Data Preparation, Data, AI and Machine Learning

        Collibra is a data governance software company that offers tools for metadata management and data cataloging. The software enables organizations to find data quickly, identify its source and assure its integrity. Line-of-business workers can use it to create, review and update the organization's policies on different data assets. Collibra’s software uses a microservice architecture and open application programming interfaces to connect to various data ecosystems. Its data intelligence cloud...

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        Topics: Analytics, Business Intelligence, Data Governance, Data Preparation, Information Management, Data, data lakes, AI and Machine Learning

        Sisu Data is an analytics platform for structured data that uses machine learning and statistical analysis to automatically monitor changes in data sets and surface explanations. It can prioritize facts based on their impact and provide a detailed, interpretable context to refine and support conclusions. The product features fact boards, annotations and the ability to share facts and analysis across teams. Data teams and analysts start by creating common definitions of key performance...

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        Topics: business intelligence, embedded analytics, Analytics, Collaboration, Data, 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

        Rapidminer is a visual enterprise data science platform that includes data extraction, data mining, deep learning, artificial intelligence and machine learning (AI/ML) and predictive analytics. It can support AI/ML processes with data preparation, model validation, results visualization and model optimization. Rapidminer Studio is its visual workflow designer for the creation of predictive models. It offers more than 1,500 algorithms and functions in their library, along with templates, for...

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        Topics: embedded analytics, Analytics, Business Intelligence, Collaboration, Data Preparation, Data, data lakes, AI and Machine Learning

        Confluent Platform is a streaming platform built by the original creators of Apache Kafka. It enables organizations to organize and manage streaming data from various sources. Confluent launched its IPO in June this year and raised $828 million to further expand its business. Confluent Platform was brought to several public cloud vendor marketplaces last year as Confluent Cloud. The offering is currently available in Azure, AWS, and GCP marketplaces. Furthermore, the company strengthened its...

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

        The annual Ventana Research Digital Innovation Awards showcase advances in the productivity and potential of business applications, as well as technology that contributes significantly to the improved processes and performance of an organization. Our goal is to recognize technology and vendors that have introduced noteworthy digital innovations to advance business and IT.

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        Topics: Customer Experience, Analytics, Internet of Things, Digital Technology, blockchain, natural language processing, Awards, Conversational Computing, collaborative computing, mobile computing, extended reality, AI and Machine Learning

        The annual Ventana Research Digital Innovation Awards showcase advances in the productivity and potential of business applications, as well as technology that contributes significantly to the improved processes and performance of an organization. Our goal is to recognize technology and vendors that have introduced noteworthy digital innovations to advance business and IT.

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        Topics: Continuous Planning, Analytics, Product Information Management, Price and Revenue Management, Digital Technology, Operations & Supply Chain, Enterprise Resource Planning, Conversational Computing, collaborative computing, continuous supply chain, work experience management, AI and Machine Learning

        The annual Ventana Research Digital Innovation Awards showcase advances in the productivity and potential of business applications, as well as technology that contributes significantly to the improved processes and performance of an organization. Our goal is to recognize technology and vendors that have introduced noteworthy digital innovations to advance business and IT.

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        Topics: Analytics, Business Intelligence, Collaboration, Data Governance, Data Preparation, Information Management, Data, Digital Technology, blockchain, data lakes, AI and Machine Learning

        Dialpad provides contact center and business phone services, a market that is in transition due to a convergence of technologies and business conditions.

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        Topics: Customer Experience, Voice of the Customer, Analytics, Collaboration, Contact Center, natural language processing, agent management, AI and Machine Learning

        The annual Ventana Research Digital Innovation Awards showcase advances in the productivity and potential of business applications, as well as technology that contributes significantly to the improved processes and performance of an organization. Our goal is to recognize technology and vendors that have introduced noteworthy digital innovations to advance business and IT.

        Read More

        Topics: embedded analytics, Analytics, Business Intelligence, Collaboration, Internet of Things, Digital Technology, natural language processing, AI and Machine Learning

        The annual Ventana Research Digital Innovation Awards showcase advances in the productivity and potential of business applications, as well as technology that contributes significantly to the improved processes and performance of an organization. Our goal is to recognize technology and vendors that have introduced noteworthy digital innovations to advance business and IT.

        Read More

        Topics: Sales, Analytics, Product Information Management, Digital Commerce, AI and Machine Learning

        A year of business uncertainty, lockdowns and operational disruptions forced finance and accounting organizations to adapt and change in many ways that are proving to be permanent. The need to operate virtually resulted in some organizations accelerating their adoption of technology, bringing them closer to achieving a transformation of the finance and accounting function: reshaping the department into an organization that is more forward-looking and strategic. Strategic in the sense of...

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        Topics: Office of Finance, Business Intelligence, Data Governance, Data Preparation, Business Planning, Financial Performance Management, ERP and Continuous Accounting, blockchain, robotic finance, Predictive Planning, AI and Machine Learning

        The annual Ventana Research Digital Innovation Awards showcase advances in the productivity and potential of business applications, as well as technology that contributes significantly to the improved processes and performance of an organization. Our goal is to recognize technology and vendors that have introduced noteworthy digital innovations to advance business and IT.

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        Topics: Customer Experience, Human Capital Management, Marketing, Office of Finance, Voice of the Customer, Continuous Planning, embedded analytics, Learning Management, Analytics, Business Intelligence, Collaboration, Data Governance, Data Preparation, Information Management, Internet of Things, Business Planning, Contact Center, Data, Product Information Management, Sales Performance Management, Workforce Management, Financial Performance Management, Price and Revenue Management, Digital Technology, Digital Marketing, Digital Commerce, Operations & Supply Chain, Enterprise Resource Planning, ERP and Continuous Accounting, Revenue, blockchain, natural language processing, data lakes, Total Compensation Management, robotic finance, Predictive Planning, employee experience, candidate engagement, Conversational Computing, Continuous Payroll, collaborative computing, mobile computing, continuous supply chain, Subscription Management, agent management, extended reality, intelligent marketing, sales enablement, work experience management, robotic automation, AI and Machine Learning, lease and tax accounting

        As mentioned in my Analyst Perspective, Revenue Performance Management: Leadership and Operations for Optimal Outcomes, there is continuing pressure on sales leaders to deliver against sales targets in increasingly competitive markets. Among the various levers that sales leadership can use to support these efforts, are applications and processes that best position sales teams to achieve targets, such as planning and allocating territories, establishing quotas and devising incentive compensation...

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        Topics: Sales, Analytics, Sales Performance Management, Price and Revenue Management, sales enablement, AI and Machine Learning

        Customer Service & Support (CSS) is a software segment that provides tools for tracking and resolving customer problems, primarily through contact centers. The segment has been mature for decades but today is reinvigorated by a new emphasis on workflows and automation. Vendors, like ServiceNow, have been innovative in developing new technologies for managing self-service and field service, and providing agents with contextually relevant information during interactions. The new technologies...

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        Topics: Customer Experience, Voice of the Customer, Analytics, Contact Center, Product Information Management, Digital Commerce, Subscription Management, agent management, AI and Machine Learning

        We are happy to share some insights about Amazon QuickSight drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements.

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        Topics: embedded analytics, Analytics, Collaboration, Data Governance, Data Preparation, Information Management, Data, natural language processing, AI and Machine Learning

        We are happy to share some insights about Google Looker drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements.

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        Topics: embedded analytics, Analytics, Collaboration, Data Governance, Data Preparation, Information Management, Data, natural language processing, AI and Machine Learning

        We are happy to share some insights about ThoughtSpot drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements.

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        Topics: embedded analytics, Analytics, Business Intelligence, Collaboration, Data Governance, Data Preparation, Information Management, Data, natural language processing, AI and Machine Learning

        We are happy to share some insights about TIBCO Spotfire drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements.

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        Topics: business intelligence, embedded analytics, Analytics, Collaboration, Data Governance, Data Preparation, Information Management, Data, AI and Machine Learning

        We are happy to share some insights about Sisense drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements.

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        Topics: business intelligence, embedded analytics, Analytics, Collaboration, Data Governance, Data Preparation, Information Management, Data, natural language processing, AI and Machine Learning

        We are happy to share some insights about Infor Birst drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements.

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        Topics: business intelligence, embedded analytics, Analytics, Collaboration, Data Preparation, Data, Information Management (IM), natural language processing, AI and Machine Learning

        We are happy to share some insights about Microsoft Power BI drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements.

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        Topics: embedded analytics, Analytics, Business Intelligence, Collaboration, Data Governance, Data Preparation, Information Management, Data, natural language processing, AI and Machine Learning

        We are happy to share some insights about Tableau drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements.

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        Topics: embedded analytics, Analytics, Business Intelligence, Collaboration, Data Governance, Data Preparation, Information Management, Data, natural language processing, AI and Machine Learning

        We are happy to share some insights about SAS drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements.

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        Topics: embedded analytics, Analytics, Business Intelligence, Collaboration, Data Governance, Data Preparation, Information Management, Data, natural language processing, AI and Machine Learning

        Teradata introduced some enhancements to its Vantage platform last year in which they expanded its analytics functions and language support, and strengthened tools to improve collaboration between data scientists, business analysts, data engineers and business personnel. Some of the key enhancements included expanding the native support for R and Python, extending the ability to execute a wide range of open-source analytics algorithms, and automatic generation of SQL from R and Python code....

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        Topics: business intelligence, embedded analytics, Analytics, Collaboration, Data Preparation, Information Management, Data, AI and Machine Learning

        We are happy to share some insights about SAP drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements.

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        Topics: business intelligence, embedded analytics, Analytics, Collaboration, Data Governance, Data Preparation, Data, natural language processing, AI and Machine Learning

        There has been a lot of market activity around vendors offering sales-forecasting products (or functionality to address sales forecasting) as part of a wider technology offering for sales and revenue management. As I have discussed in my Analyst Perspective: The Art and Science of Sales from the Inside Out, the pandemic accelerated the prior trends that are now forcing sales leaders and sales teams to reexamine traditional notions of how B2B sales are conducted. In addition, with the rise of...

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        Topics: Sales, Office of Finance, Analytics, Business Planning, Sales Performance Management, Price and Revenue Management, AI and Machine Learning

        We are happy to share some insights about Board International drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements.

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        Topics: embedded analytics, Analytics, Business Intelligence, Collaboration, Data Governance, Data Preparation, Information Management, Data, natural language processing, AI and Machine Learning

        We are happy to share some insights about Yellowfin drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements.

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        Topics: embedded analytics, Analytics, Business Intelligence, Collaboration, Data Governance, Data Preparation, Information Management, Data, natural language processing, AI and Machine Learning

        As laid out in my recent Analyst Perspective, Revenue Management: The Opportunity for Innovation and Optimization, revenue management is a new way look at generating and managing the top line. It unifies multiple sources: the traditional focus on new customers to existing customers as well as all types of revenue from new, additional channels. This could include customer retention, upsell and cross sell, in addition to other selling channels such as through partners or digital sales channels...

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        Topics: Sales, Analytics, Sales Performance Management (SPM), Price and Revenue Management, Digital Commerce, Subscription Management, AI and Machine Learning

        We are happy to share some insights about Domo drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements.

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        Topics: embedded analytics, Analytics, Business Intelligence, Collaboration, Data Governance, Data Preparation, Information Management, Data, natural language processing, AI and Machine Learning

        We are happy to share some insights about Oracle Analytics Cloud drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements.

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        Topics: embedded analytics, Analytics, Business Intelligence, Collaboration, Data Governance, Data Preparation, Information Management, Data, AI and Machine Learning

        We are happy to share some insights about Qlik drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements.

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        Topics: business intelligence, embedded analytics, Analytics, Collaboration, Data Governance, Data Preparation, Data, Information Management (IM), natural language processing, AI and Machine Learning

        We are happy to share some insights about Information Builders’ WebFOCUS Business Intelligence and Analytics Platform drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements.

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        Topics: business intelligence, embedded analytics, Analytics, Collaboration, Data Governance, Data Preparation, Information Management, Data, natural language processing, AI and Machine Learning

        We are happy to share some insights about MicroStrategy drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements.

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        Topics: business intelligence, embedded analytics, Analytics, Collaboration, Data Governance, Data Preparation, Information Management, Data, natural language processing, AI and Machine Learning

        We are happy to share some insights about IBM drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements.

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        Topics: embedded analytics, Analytics, Business Intelligence, Collaboration, Data Governance, Information Management, natural language processing, AI and Machine Learning

        Customer service and support (CSS) is a term with two meanings. Most generally, it refers to the functions of a contact center in handling post-sales customer inquiries that require some effort or action on the part of the business. More specifically, it refers to the elements of the software stack that facilitate those operations, primarily case tracking and trouble ticketing.

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        Topics: Customer Experience, Analytics, Contact Center, agent management, AI and Machine Learning

        Alation recently announced the release of its 2021.1 version, introducing new data governance capabilities, enhancements in search and discovery through data domains, and extended connector and query coverage for data sources. Alation’s new federated authentication enables users to query cloud services such as Amazon Web Services, Snowflake, Tableau and more, using a single sign-on. The release also includes a Search application programming interface that allows for the integration of Alation...

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        Topics: Analytics, Business Intelligence, Collaboration, Data Preparation, Data, Information Management (IM), AI and Machine Learning

        Unit4’s Financial Planning and Analysis (formerly Prevero) is a planning and budgeting application designed for the requirements of midsize corporations and the public sector. These organizations are challenged in buying software because they have almost all the requirements of larger enterprises but have a smaller budget and limited technical resources.

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        Topics: Office of Finance, embedded analytics, Analytics, Business Intelligence, Business Planning, Financial Performance Management, Price and Revenue Management, Digital Technology, ERP and Continuous Accounting, Predictive Planning, collaborative computing, AI and Machine Learning

        Observed both here and elsewhere, average sales quota attainments appear to be in an exorable decline. As I discussed in my recent Analyst Perspective, "The Art and Science of Sales from the 'Inside Out'," vendors of sales technology have reacted to this by adding a slew of new functionality including the potential for artificial intelligence (AI) to be a game changer for sales. One can argue that this use of AI is still relatively immature having been generally available only since 2014, but...

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        Topics: Sales, Human Capital Management, Analytics, Business Intelligence, Sales Performance Management, candidate engagement, sales enablement, AI and Machine Learning
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          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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