The starting point of an era is never precise and rarely conforms to neat calendar delineations. For example, the start of the 20th century is associated with the outbreak of war in 1914. So I expect that decades from now, the consensus will hold that what became known as the 21st century began in the year 2020, with the pandemic serving as a catalyst that accelerated already existing trends and forced changes to prevailing norms and practices. This and other disruptive events that have...
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Topics:
Office of Finance,
Business Intelligence,
Business Planning,
Financial Performance Management,
digital finance,
AI & Machine Learning,
profitability management,
operational data platforms
I have written recently about the similarities and differences between data mesh and data fabric. The two are potentially complementary. Data mesh is an organizational and cultural approach to data ownership, access and governance. Data fabric is a technical approach to automating data management and data governance in a distributed architecture. There are various definitions of data fabric, but key elements include a data catalog for metadata-driven data governance and self-service, agile data...
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Topics:
Business Intelligence,
Cloud Computing,
Data Governance,
Data Management,
Data,
data operations,
AI & Machine Learning,
operational data platforms
Ventana Research’s Data Lakes Dynamics Insights research illustrates that while data lakes are fulfilling their promise of enabling organizations to economically store and process large volumes of raw data, data lake environments continue to evolve. Data lakes were initially based primarily on Apache Hadoop deployed on-premises but are now increasingly based on cloud object storage. Adopters are also shifting from data lakes based on homegrown scripts and code to open standards and open...
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Topics:
Business Intelligence,
Data Governance,
Data Management,
Data,
data operations,
AI & Machine Learning,
Analytics & Data,
Streaming Data & Events,
operational data platforms,
Analytic Data Platforms
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,
AI & Machine Learning,
Streaming Data & Events,
operational data platforms,
Analytic Data Platforms
I have written recently about increased demand for data-intensive applications infused with the results of analytic processes, such as personalization and artificial intelligence (AI)-driven recommendations. Almost one-quarter of respondents (22%) to Ventana Research’s Analytics and Data Benchmark Research are currently analyzing data in real time, with an additional 10% analyzing data every hour. There are multiple data platform approaches to delivering real-time data processing and analytics...
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Topics:
Cloud Computing,
Data,
Streaming Analytics,
Analytics & Data,
Streaming Data & Events,
operational data platforms,
Analytic Data Platforms
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,
AI & Machine Learning,
operational data platforms,
Analytic Data Platforms
Streaming data has been part of the industry landscape for decades but has largely been focused on niche applications in segments with the highest real-time data processing and analytics performance requirements, such as financial services and telecommunications. As demand for real-time interactive applications becomes more pervasive, streaming data is becoming a more mainstream pursuit, aided by the proliferation of open-source streaming data and event technologies, which have lowered the cost...
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Topics:
Data,
Streaming Analytics,
Streaming Data & Events,
operational data platforms
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 & Machine Learning,
operational data platforms