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Hazelcast Weaves Wider Logic Threads Through The Data Fabric

Adrian Bridgwater for Forbes

A data fabric is textured approach to combining disparate data sources, data pipelines, databases, data streams and cloud data services into one woven unified entity.

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Announcing the 2024 Data Engineering & Ai X Innovation Summits

ODSC - Open Data Science

Data Engineering Summit Our second annual Data Engineering Summit will be in-person for the first time! Like our first Data Engineering Summit , this event will bring together the leading experts in data engineering and thousands of practitioners to explore different strategies for making data actionable.

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The Data Integration Solution Checklist: Top 10 Considerations

Precisely

As enterprise technology landscapes grow more complex, the role of data integration is more critical than ever before. Wide support for enterprise-grade sources and targets Large organizations with complex IT landscapes must have the capability to easily connect to a wide variety of data sources.

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Mainframe Technology Trends for 2023

Precisely

Organizations that can master the challenges of data integration, data quality, and context will be well positioned to identify opportunities and threats quickly, and then to take decisive action to gain competitive advantage. Containerization Docker containers are revolutionizing the way organizations host and deply applications.

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How Cloud Data Platforms improve Shopfloor Management

Data Science Blog

The fusion of data in a central platform enables smooth analysis to optimize processes and increase business efficiency in the world of Industry 4.0 using methods from business intelligence , process mining and data science. Cloud Data Platform for shopfloor management and data sources such like MES, ERP, PLM and machine data.

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How Databricks and Tableau customers are fueling innovation with data lakehouse architecture

Tableau

In many of the conversations we have with IT and business leaders, there is a sense of frustration about the speed of time-to-value for big data and data science projects. We often hear that organizations have invested in data science capabilities but are struggling to operationalize their machine learning models.

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How Databricks and Tableau customers are fueling innovation with data lakehouse architecture

Tableau

In many of the conversations we have with IT and business leaders, there is a sense of frustration about the speed of time-to-value for big data and data science projects. We often hear that organizations have invested in data science capabilities but are struggling to operationalize their machine learning models.

Tableau 52