In my past perspectives, I’ve written about the evolution from data at rest to data in motion and the fact that you can’t rely on dashboards for real-time analytics. Organizations are becoming more and more event-driven and operating based on streaming data. As well, analytics are becoming more and more intertwined with operations. More than one-fifth of organizations (22%) describe their analytics workloads as real time in our Data and Analytics Benchmark Research and nearly half (47%) of...
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Topics:
Analytics,
Business Intelligence,
Data,
Digital Technology,
Streaming Analytics,
Analytics & Data,
Streaming Data & Events
The current market landscape of data and analytics is undergoing rapid evolution, presenting organizations with a wide array of challenges and opportunities. As data sources and warehouses steadily migrate to the cloud, a significant number of organizations still depend on conventional tools. This reliance on legacy systems hinders the seamless accessibility and adoption of analytics and business intelligence within business processes. Organizations are increasingly turning to embedded...
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Topics:
embedded analytics,
Analytics,
Business Intelligence,
Streaming Analytics,
AI and Machine Learning
Organizations are becoming increasingly aware of the potential value that can be gained by processing big data. As data sources grow, it becomes important to have tools and methods to effectively process, analyze and visualize this information from disparate systems and warehouses.
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Topics:
business intelligence,
embedded analytics,
Analytics,
Streaming Analytics
Embedded business intelligence (BI) continues to transform the business landscape, enabling organizations to quickly interpret data and convert it into actionable insights. It allows organizations to extract information in real time and answer wide-ranging business questions. Embedding analytics helps tackle the issue of extracting information from data which is a time-consuming process. Our research shows organizations spend more time cleaning and optimizing data for analysis rather than...
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Topics:
embedded analytics,
Analytics,
Business Intelligence,
natural language processing,
Streaming Analytics,
AI and Machine Learning
As I recently pointed out, process mining has emerged as a pivotal technology for data-driven organizations to discover, monitor and improve processes through use of real-time event data, transactional data and log files. With recent advancements, process mining has become more efficient at discovering insights in complex processes using algorithms and visualizations. Organizations use it to better understand the current state of systems and business processes. It is also used to enable ...
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Topics:
Analytics,
Business Intelligence,
Process Mining,
Streaming Analytics,
AI and Machine Learning
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,
Analytics,
Business Intelligence,
Internet of Things,
Streaming Analytics,
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 & Data,
AI and Machine Learning
Organizations are continuously increasing the use of analytics and business intelligence to turn data into meaningful and actionable insights. Our Analytics and Data Benchmark Research shows some of the benefits of using analytics: Improved efficiency in business processes, improved communication and gaining a competitive edge in the market top the list. With a unified BI system, organizations can have a comprehensive view of all organizational data to better manage processes and identify...
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Topics:
business intelligence,
embedded analytics,
Data Governance,
Data Management,
natural language processing,
data operations,
Streaming Analytics,
Streaming Data & Events,
operational data plaftforms,
AI and Machine Learning
Organizations have been using data virtualization to collect and integrate data from various sources, and in different formats, to create a single source of truth without redundancy or overlap, thus improving and accelerating decision-making giving them a competitive advantage in the market. Our research shows that data virtualization is popular in the big data world. One-quarter (27%) of participants in our Data Lake Dynamic Insights Research reported they were currently using data...
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Topics:
embedded analytics,
Analytics,
Business Intelligence,
Streaming Analytics,
AI and Machine Learning
I have written previously that the world of data and analytics will become more and more centered around real-time, streaming data. Data is created constantly and increasingly is being collected simultaneously. Technology advances now enable organizations to process and analyze information as it is being collected to respond in real time to opportunities and threats. Not all use cases require real-time analysis and response, but many do, including multiple use cases that can improve customer...
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Topics:
Analytics,
Business Intelligence,
Internet of Things,
Data,
Digital Technology,
Streaming Analytics,
Analytics & Data,
Streaming Data & Events,
AI and Machine Learning