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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...

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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


Data mesh is the latest trend to grip the data and analytics sector. The term has been rapidly adopted by numerous vendors — as well as a growing number of organizations —as a means of embracing distributed data processing. Understanding and adopting data mesh remains a challenge, however. Data mesh is not a product that can be acquired, or even a technical architecture that can be built. It is...

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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


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...

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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,...

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


Organizations face various challenges with analytics and business intelligence processes, including data curation and modeling across disparate sources and data warehouses, maintaining data quality and ensuring security and governance. Traditional processes are slow when transforming large and diverse datasets into something which is easily consumable in BI. And, it can take days or weeks to...

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Topics: Big Data, Analytics, Business Intelligence


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...

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Topics: Analytics, Data, AI and Machine Learning


Natural language processing (NLP) is a field that combines artificial intelligence (AI), data science and linguistics that enables computers to understand, interpret and manipulate text or spoken words. NLP includes generating narratives based on a set of data values, using text or speech as inputs to access information, and analysing text or speech, for instance, to determine its sentiment....

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Topics: Big Data, Analytics, natural language processing, NLP


Despite all the advances organizations have made with respect to analytics, our most recent research shows the majority of the workforce in the majority of organizations are not using analytics and business intelligence (BI). Less than one-quarter (23%) report that one-half or more of their workforce is using analytics and BI. This is a problem. It means organizations are not enabling their...

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Topics: Sales, business intelligence, embedded analytics, Analytics, Data, Sales Performance Management, Digital Technology, Digital Commerce, natural language processing, Subscription Management, partner management, Collaborative & Conversational Computing


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...

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


Many organizations invest in data governance out of concern over misuse of data or potential data breaches. These are important considerations and valid aspects of data governance programs. However, good data governance also has positive impacts on organizations. For example, I have previously written about the valuable connection between the use of data catalogs and satisfaction with an...

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Topics: embedded analytics, Analytics, Data Governance, Data, Digital Technology


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...

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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...

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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...

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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 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...

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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 2022 Market Agenda for Analytics, continuing the guidance we have offered for nearly two decades to help organizations derive optimal value from technology investments in order to improve business outcomes.

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


I’m proud to share Ventana Research’s 2022 Market Agenda for Digital Technology. Our focus in this agenda is to deliver expertise to help organizations prioritize technology investments that increase workforce effectiveness and organizational agility, ensuring ongoing operations during any type of disruption.

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Topics: Analytics, Cloud Computing, Internet of Things, Data, Digital Technology


Ventana Research has announced its market agenda for 2022, continuing the tradition of reliability in our efforts to educate and guide the technology market. Our assessments are backed by our expertise and independence, as we do not share our market agenda or our research – including analyst and market perspectives or our Value Index – with any external party until it is published. We review and...

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


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...

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


Few trends have had a bigger impact on the data platforms landscape than the emergence of cloud computing. The adoption of cloud computing infrastructure as an alternative to on-premises datacenters has resulted in significant workloads being migrated to the cloud, displacing traditional server and storage vendors. Almost one-half (49%) of respondents to Ventana Research’s Analytics and Data...

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Topics: Analytics, Business Intelligence, Data Governance, Data Integration, Data


Organizations today are working with multiple applications and systems, including enterprise resource planning (ERP), customer relationship management (CRM), supply chain management (SCM) and other systems, where data can easily become fragmented and siloed. And as the organization increases its data sources and adds more systems and custom applications, it becomes challenging to manage the data...

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


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