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  • for Author: Matt Aslett
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Executive Summary Key Takeaways Application integration has become a foundational capability for enabling real-time interoperability across increasingly complex enterprise application portfolios. Organizations rely on integration platforms to connect business processes, APIs, data flows and automation across hybrid and multicloud environments. AI, event-driven architectures and API-led... Read More

Executive Summary Key Takeaways Real-time data emerging providers are helping enterprises accelerate adoption of event-driven architectures, streaming analytics and real-time decision-making capabilities. These providers often focus on specialized areas of the real-time data ecosystem, delivering innovation in messaging, stream processing, streaming databases and real-time analytics. As AI-driven... Read More

Executive Summary Key Takeaways Real-time data technologies are becoming foundational to enterprise automation by enabling organizations to process, analyze and act on business events as they occur. Enterprises are increasingly adopting streaming data, event processing and real-time analytics to support operational responsiveness, AI-driven decision-making and intelligent applications. The... Read More

Executive Summary Key Takeaways Streaming data platforms have become foundational technologies for enterprises seeking to process, enrich and act on event data as it is generated. Organizations increasingly rely on streaming data capabilities to support real-time decision-making, event-driven architectures and AI-enabled automation across distributed environments. The convergence of streaming,... Read More

Executive Summary Key Takeaways Streaming analytics is becoming a critical capability for enterprises seeking to act on business events as they occur rather than relying on delayed, batch-oriented analysis. Organizations are increasingly combining streaming data, real-time analytics and AI-driven decision-making to improve responsiveness and support intelligent applications. As event-driven... Read More

Executive Summary Master Data Management Despite efforts made by enterprises to be more data-driven, some of the most fundamental questions about an enterprise—such as how many customers it has—remain difficult to answer. Trust in data is foundational for an enterprise to make data-driven business decisions. The problem lies not just in being able to accurately count how many customers the... Read More

Topics: Master Data Management, Data Management, Artificial intelligence, Data Intelligence


Executive Summary Data Intelligence Today’s enterprises seek to increase data-driven decision-making to gain competitive advantage and improve efficiency. It is ironic, however, that many enterprises lack information about when and how data is used in decision-making processes. The capabilities that provide enterprises with information about how data is generated and consumed across the... Read More

Topics: Data Management, Artificial intelligence, Data Intelligence


Executive Summary Data Governance Data governance is integral to an overall data management strategy. Good data governance provides guardrails that enable enterprises to act quickly while protecting the business from risks related to regulatory requirements, data-quality issues and data-reliability concerns. It accelerates the delivery of analytics projects, providing the confidence required to... Read More

Topics: Data Governance, Data Management, Artificial intelligence, Data Intelligence


Executive Summary Data Quality Maintaining data quality and trust is a perennial data-management challenge, often preventing enterprises from operating at the speed of business. As enterprises aspire to be more data-driven, trust in the data used to make decisions becomes more critical. Without data quality processes and tools, enterprises may make decisions based on old, incomplete, incorrect or... Read More

Topics: Data Quality, Data Management, Artificial intelligence, Data Intelligence


Executive Summary Data Management Data management combines functionality addressing data governance, data quality, master data management, data integration and data intelligence to ensure that the enterprise is collecting, storing and processing data in accordance with strategic goals and regulatory requirements. Data management has been a critical component of enterprise IT strategies for... Read More

Topics: Data Management, Artificial intelligence, Data Intelligence


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