Building Batch Data Analytics Solutions on AWS

عالج كميات كبيرة من البيانات دفعياً على AWS. تطلق مجموعات Amazon EMR وتضبطها، وتحوّل البيانات باستخدام Spark وHive وAWS Glue، وتنسّق خطوط المعالجة، وتؤمّن أحمال العمل وتراقبها.

يوم واحدمتوسط9 وحدات

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المحتوى التقني أدناه معروضٌ باللغة الإنجليزية كما ورد في منهاج الدورة، حفاظاً على دقّة المصطلحات.

Launch and configure clusters using Amazon EMR for batch workloads
Transform and analyze batch data using Spark, Hive, and AWS Glue
Secure data in transit and at rest using AWS-native tools
Monitor and optimize performance using built-in EMR tools
Apply cost management strategies to large-scale workloads

المنهاج

9 وحدات

Overview of batch data workflows
Define components of a modern AWS-based data pipeline
Identify analytics use cases across business functions

Understand how Amazon EMR supports Spark, Hadoop, Hive, and HBase
Interactive Demo: Launching an EMR cluster
Explore cost management and auto scaling options

Compare techniques for data ingestion
Optimize data storage with S3, compression, and tiering
Integrate with AWS Glue and AWS Lake Formation

Implement transformation and analytics with Apache Spark
Interactive Demo: Run Spark commands using Spark shell
Practice Lab: Use EMR Notebooks for low-latency analytics

Query and transform structured data using Hive on Amazon EMR
Practice Lab: Run Hive jobs for batch processing tasks

Automate workflows with AWS Step Functions
Catalog and transform data using AWS Glue
Practice Lab: Orchestrate Spark jobs using Step Functions

Protect data using EMRFS encryption and IAM
Interactive Demo: Enable client-side encryption in EMRFS
Monitor performance using logs, CloudWatch, and Spark History Server

Apply cost, performance, and security tradeoffs to pipeline design
Activity: Design a real-world batch data analytics solution

Combine open-source and AWS services in flexible architectures
Use Hive, HBase, and Redshift for complex batch analytics
Integrate EMR with AWS Glue and Lake Formation
Practice Lab: Process and analyze batch data using Hive and HBase
Practice Lab: Coordinate Spark jobs using AWS Step Functions
Explore real-world scenarios for enterprise-scale analytics pipelines
Discuss how to structure architectures to support data lakes and data warehouses

لمن هذه الدورة

مهندسو البيانات ومحلّلوها العاملون مع البيانات الضخمة على AWS.