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Culture and Methodologies
Agile Career Development Methodologies Team Management
Data Engineering
AI/ML Big Data Data Databases IoT
Software Design and Architecture
Cloud Architecture Containers Integration Microservices Performance Security
Coding
Frameworks Java JavaScript Languages Tools
Testing, Deployment, and Maintenance
Deployment DevOps and CI/CD Maintenance Monitoring and Observability Testing, Tools, and Frameworks

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Frank Eaves

Senior Software Engineer at N/A

Raleigh, US

Joined Jun 2018

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Moving Toward Smarter Data: Graph Databases and Machine Learning
A brief overview of database solutions, an introduction to using machine learning and graph databases, and real-world use cases for putting context back into your data.
August 5, 2020
· 23,756 Views · 20 Likes

Refcards

Refcard #357

NoSQL Migration Essentials

NoSQL Migration Essentials

Trend Reports

Trend Report

The Database Evolution

Organizations are constantly working to build up their big data capabilities with hopes to compete in the modern economy. SQL and NoSQL database types were supposed to help organizations identify and make sense of hidden patterns in the data that businesses collected. In recent years, however, the momentum of the big data movement has seemed to slow as business leaders around the world have failed to realize the results that were promised several years ago. As the momentum has decelerated, how is the use of SQL and NoSQL databases evolving to support these efforts as businesses attempt to course correct in the big data era? In DZone’s 2020 Trend Report “Database Evolution: SQL or NoSQL in the Age of Big Data,” we explore the role of two popular database types SQL and NoSQL in big data initiatives over the next 6-12 months. Readers will find original research, interviews with industry experts, and additional resources with helpful tips, best practices, and more.

The Database Evolution

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