Analytics on AWS
Access and analyze all your data in data lakehouse, data warehouse, and data lake. Analyze, prepare, and integrate data for analytics and AI using open-source frameworks. Build, discover, and share meaningful insights through modern interactive dashboards, pixel-perfect reports, natural language queries, and embedded analytics.
What is Big Data? - Big Data Analytics Explained - AWS
Big data is all about getting high value, actionable insights from your data assets. Ideally, data is made available to stakeholders through self-service business intelligence and agile data visualization tools that allow for fast and easy exploration of datasets.
AWS Workshops
Collection of workshops covering best practices to optimize costs and building resilient applications with Spot instances in common workloads: containerized environments, web applications, big data, CI/CD, batch... Each workshop takes ~90 minutes to complete.
Big Data Use Cases – Amazon Web Services (AWS)
With AWS you can build virtually any big data application. These are just a few examples of how organizations are driving value from big data with AWS On-Demand Big Data Analytics
Expert Guide on AWS Big Data's Tools and Best Practices
2024年10月14日 · From scalable storage to real-time data analytics, Amazon AWS Big Data simplifies complex workflows and ensures you can analyze data with precision and agility. AWS Big data allows organizations to scale their resources up or down based on demand without upfront costs or hardware constraints.
Introduction - Big Data Analytics Options on AWS
Whether your applications require real-time streaming or batch data processing, AWS provides the infrastructure and tools to tackle your next big data project. There is no hardware to procure, no infrastructure to maintain and scale—only what you need to collect, store, process, and analyze big data.
Big Data Analytics Options on AWS
2021年7月26日 · This whitepaper helps architects, data scientists, and developers understand the big data analytics options available in the Amazon Web Services (AWS) Cloud. It provides an overview of services.
Choosing an AWS analytics service
2023年11月17日 · This decision guide helps you ask the right questions to build your modern data architecture on AWS services. It explains how to break down your data silos (by connecting your data lake and data warehouses), your system silos (by connecting ML and analytics), and your people silos (by putting data in the hands of everyone in your organization).
AWS Big Data Blog
2024年12月5日 · Amazon SageMaker Lakehouse offers a unified solution for enterprise data access, combining data from warehouses and lakes. This post demonstrates how SageMaker Lakehouse integrates scattered data sources, enabling secure enterprise-wide access, and allowing teams to use their preferred tools for predicting and analyzing customer churn.
The AWS advantage in big data analytics
Analyzing large datasets requires significant compute capacity that can vary in size, based on the amount of input data and the type of analysis. This characteristic of big data workloads is ideally suited to the pay-as-you-go cloud computing model, where applications can easily scale up and down based on demand.
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