Packt
AWS Data Processing and Analysis

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AWS Data Processing and Analysis

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Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

8 hours to complete
3 weeks at 2 hours a week
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

8 hours to complete
3 weeks at 2 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Integrate and scale data pipelines using AWS Lambda and Glue for efficient data processing

  • Analyze real-time data streams with Kinesis Analytics and OpenSearch to gain actionable insights

  • Implement security measures and manage data workflows for high-performance analysis

  • Analyze real-time data streams with Kinesis Analytics and OpenSearch to gain actionable insights

Details to know

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Recently updated!

October 2024

Assessments

1 assignment

Taught in English

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Build your subject-matter expertise

This course is part of the AWS Certified Data Analytics Specialty (2023) Hands-on Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
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There are 2 modules in this course

In this module, we will delve into AWS processing services, beginning with an introduction to AWS Lambda and Glue. You’ll learn how to integrate these tools for serverless and ETL workflows. We will also explore advanced topics such as Glue ETL job execution, Lambda's cost optimization strategies, and EMR’s integration with other AWS services like Apache Spark, Hive, and Hadoop. Hands-on exercises will cover using Spark with Kinesis and Redshift, and how to process data lakes with EMR.

What's included

35 videos2 readings

In this module, we will focus on analyzing and querying data using AWS’s powerful analytics services. We begin with an introduction to Kinesis Analytics, OpenSearch, and Athena, followed by performance tuning and security best practices. Through hands-on exercises, you’ll build real-world applications to monitor data streams, optimize queries using Glue and Athena, and perform data warehousing with Redshift. Additionally, we’ll explore Redshift's durability, distribution styles, and newer features like AQUA and serverless options to improve large-scale data analytics.

What's included

32 videos1 reading1 assignment

Instructor

Packt - Course Instructors
Packt
373 Courses11,275 learners

Offered by

Packt

Recommended if you're interested in Cloud Computing

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