Cloud Computing

Cloud Computing

1. Relationships

   • Big Data Analytics
     • Involves the process of examining large and complex datasets to uncover hidden patterns, correlations, and insights that can help organizations make data-driven decisions.
     • Key Components
       • Data collection, storage, processing, analysis, and visualization.
     • Technologies and Tools
       • Hadoop, Spark, Apache Flink, data mining algorithms, etc.
     • Applications
       • Business intelligence, predictive analytics, customer insights, etc.
   • Scalability
     • Cloud computing, scalable resources, big data processing, analytics, performance, handle large volumes of data
   • Cost Efficiency
     • Cloud platforms, cost-effective solutions, storing, processing, pay-as-you-go models, upfront investments, optimize costs, allocate resources
   • Data Processing Technologies
     • Cloud infrastructure, big data processing technologies, Hadoop, Spark, Apache Flink, distributed computing, analyze, derive insights, large datasets.
   • Data Security and Privacy
     • Cloud providers, security measures, safeguard, sensitive data, big data analytics, encryption, access controls, compliance, data confidentiality, integrity, availability.
   • Intersections and Overlaps
     • Cloud-based Big Data Analytics Platforms
     • Data Migration and Integration

2. Refers to the delivery of computing services—including servers, storage, databases, networking, software, and analytics—over the internet, providing flexible resources and on-demand access to shared computing resources

3. Key Components

   • Infrastructure as a Service (IaaS), Platform as a Service (PaaS), Software as a Service (SaaS)

4. Service Models

   • Public cloud, private cloud, hybrid cloud.

5. Providers

   • Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP), etc.

Bilder und Dateien der Mindmap