How long does it take to complete the course?

The course consists of approximately 9 hours of video content. Depending on your pace and the time you allocate for practical exercises, the course may take a bit longer to complete. It's designed for learners to complete at their own speed, with ample opportunity for hands-on practice throughout the modules.

Can I preview a course before enrolling?

Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.

When will I have access to the lectures and assignments?

If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. You’ll be able to submit assignments once the session starts.

What will I get when I enroll?

Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. You’ll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.

When will I receive my Course Certificate?

If you complete the course successfully, your electronic Course Certificate will be added to your Accomplishments page - from there, you can print your Course Certificate or add it to your LinkedIn profile.

Why can’t I audit this course?

This course is currently available only to learners who have paid or received financial aid, when available.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Advanced Data Processing and Analytics with AWS

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Advanced Data Processing and Analytics with AWS

Ce cours fait partie de Spécialisation Data Engineering on AWS - The Complete Training

Instructeur : Packt - Course Instructors

Inclus avec

4 modules

Obtenez un aperçu d'un sujet et apprenez les principes fondamentaux.

niveau Intermédiaire

Expérience recommandée

1 semaine à compléter

à 10 heures par semaine

Planning flexible

Apprenez à votre propre rythme

4 modules

Obtenez un aperçu d'un sujet et apprenez les principes fondamentaux.

niveau Intermédiaire

Expérience recommandée

1 semaine à compléter

à 10 heures par semaine

Planning flexible

Apprenez à votre propre rythme

Ce que vous apprendrez

Master the use of Amazon Kinesis and MSK for real-time data processing.
Set up and manage big data workloads using Amazon EMR efficiently.
Build secure, scalable data lakes using AWS Lake Formation.
Optimize and query large datasets using Amazon Athena.

Compétences que vous acquerrez

Catégorie : Data Processing
Catégorie : Apache Hadoop
Catégorie : AWS Kinesis
Catégorie : Amazon S3
Catégorie : Apache Spark
Catégorie : Data Management
Catégorie : Query Languages
Catégorie : Apache Hive
Catégorie : Scalability
Catégorie : AWS Identity and Access Management (IAM)
Catégorie : Real Time Data
Catégorie : Serverless Computing
Catégorie : Data Lakes
Catégorie : Big Data
Catégorie : Apache Kafka
Catégorie : Amazon Redshift
Catégorie : Data Pipelines

Détails à connaître

Certificat partageable

Ajouter à votre profil LinkedIn

Récemment mis à jour !

décembre 2025

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Ce cours fait partie de la Spécialisation Data Engineering on AWS - The Complete Training

Lorsque vous vous inscrivez à ce cours, vous êtes également inscrit(e) à cette Spécialisation.

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Il y a 4 modules dans ce cours

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A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. This course equips learners with the skills to efficiently process and analyze large volumes of data using AWS services. You will gain expertise in streaming data with Amazon Kinesis and Amazon MSK, running big data workloads on Amazon EMR, building data lakes on AWS, and querying data using Amazon Athena. The course is designed to help you develop a deep understanding of AWS tools and best practices for managing data in cloud environments. Through the course, you will explore the fundamentals of streaming data and various AWS services that support real-time analytics, such as Kinesis and MSK. You’ll also dive into building scalable data lakes using AWS Lake Formation and learn how to run big data processing workloads using Amazon EMR, along with optimizing them for cost and performance. Each module builds on the last, allowing you to master streaming, storage, and query operations seamlessly. As you progress, you will learn how to configure and optimize systems for maximum throughput. The course features hands-on exercises and best practices for using AWS tools, ensuring that you develop practical skills for real-world applications. The structure ensures that you understand the foundational concepts before advancing to complex data management and optimization techniques. This course is ideal for data engineers, cloud architects, or anyone looking to advance their skills in AWS data processing. While prior experience with cloud services is helpful, the course is designed for those with an intermediate understanding of data management and analytics. By the end of the course, you will be able to configure AWS services for real-time data processing, set up data lakes, optimize big data workloads on Amazon EMR, and query data efficiently using Amazon Athena.

In this module, we will explore the fundamentals of real-time data streaming and dive deep into AWS services like Amazon Kinesis and Amazon Managed Streaming for Apache Kafka (MSK). You'll learn how to ingest, process, and deliver streaming data using tools such as Kinesis Data Streams, Firehose, and Flink, as well as build scalable Kafka pipelines. By the end, you'll be equipped to choose the right streaming architecture for your analytics and operational needs.

Inclus

25 vidéos2 lectures1 devoir

25 vidéosTotal 206 minutes

What Is Streaming Data?8 minutes
Streaming Services in AWS5 minutes
Amazon Kinesis Family2 minutes
Amazon Kinesis Data Streams13 minutes
Capacity Mode7 minutes
Shard Iterators13 minutes
Kinesis Data Generator7 minutes
Data Stream Producers4 minutes
Data Stream Consumer2 minutes
Enhanced Fan-Out5 minutes
Amazon Kinesis Firehose18 minutes
Dynamic Partitioning9 minutes
Data Stream vs. Data Firehose4 minutes
Managed Service for Apache Flink11 minutes
Flink Application15 minutes
Flink Studio3 minutes
Apache Kafka9 minutes
Amazon Managed Service for Kafka8 minutes
MSK Cluster9 minutes
Kafka Topic21 minutes
Send and Receive Messages5 minutes
Amazon MSK Serverless5 minutes
MSK Provisioned vs. Serverless2 minutes
Amazon MSK Connect4 minutes
Amazon Kinesis vs. Amazon MSK5 minutes

2 lecturesTotal 20 minutes

Introduction to the Course 'Advanced Data Processing and Analytics with AWS'10 minutes
Full Specialization Resource10 minutes

1 devoirTotal 15 minutes

Processing Streaming Data on Amazon Kinesis and Amazon MSK - Assessment15 minutes

In this module, we will delve into how Amazon EMR simplifies running big data frameworks like Hadoop, Spark, and Hive on AWS. You’ll learn how to configure EMR clusters, manage storage, and leverage EMR Serverless for auto-scaling workloads. The lessons also cover migration strategies and cost optimization techniques for efficient big data processing.

Inclus

10 vidéos1 devoir

10 vidéosTotal 71 minutes

What Is Big Data?3 minutes
MapReduce5 minutes
Big Data Ecosystem4 minutes
Amazon EMR7 minutes
Storage for EMR7 minutes
Creating EMR Cluster: Part 116 minutes
Creating EMR Cluster: Part 28 minutes
Migration9 minutes
Amazon EMR Serverless4 minutes
Cost Optimization3 minutes

1 devoirTotal 15 minutes

Running Big Data Workloads on Amazon EMR - Assessment15 minutes

In this module, we will guide you through building and managing a modern data lake on AWS using Lake Formation. You'll set up ingestion, define permissions, and manage metadata for secure, scalable data storage. We also explore the use of open table formats for analytics flexibility and performance.

Inclus

9 vidéos1 devoir

9 vidéosTotal 84 minutes

What Is a Data Lake?8 minutes
Data Warehouse vs. Data Lake7 minutes
AWS Lake Formation8 minutes
How It Works?10 minutes
Setting Up a Data Lake: Part 117 minutes
Setting Up a Data Lake: Part 27 minutes
Data Lake Permissions13 minutes
Tag-Based Permissions8 minutes
Open Table Formats3 minutes

1 devoirTotal 15 minutes

Building Data Lakes on AWS - Assessment15 minutes

In this module, we will explore how Amazon Athena enables serverless, SQL-based querying of your data stored in Amazon S3. You’ll learn to optimize queries, manage access with workgroups, and extend Athena’s capabilities through federated queries. By mastering these techniques, you'll streamline data analysis without managing infrastructure.

Inclus

7 vidéos1 lecture3 devoirs

7 vidéosTotal 87 minutes

Why Use Amazon Athena?6 minutes
How It Works?13 minutes
Optimizing Queries in Athena: Part 115 minutes
Optimizing Queries in Athena: Part 213 minutes
Workgroups13 minutes
Federated Query: Part 15 minutes
Federated Query: Part 219 minutes

1 lectureTotal 10 minutes

Conclusion to the Course 'Advanced Data Processing and Analytics with AWS'10 minutes

3 devoirsTotal 90 minutes

Query Your Data Using Amazon Athena - Assessment15 minutes
Full Course Assessment60 minutes
Full Course Practice Assessment15 minutes

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Instructeur

Packt - Course Instructors

Packt

1 218 Cours295 149 apprenants

Offert par

Packt

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Foire Aux Questions

Advanced Data Processing and Analytics with AWS is a comprehensive course designed to equip learners with the knowledge and skills needed to process large volumes of data using AWS services. The course covers essential topics such as streaming data, big data workloads, data lakes, and serverless analytics. With the increasing importance of real-time data processing, machine learning, and large-scale data management, the course provides invaluable expertise in using AWS tools and frameworks to process, analyze, and derive insights from data effectively. This is highly relevant for those looking to advance in fields like cloud computing, big data, and analytics.

This course focuses on advanced techniques for processing and analyzing data on AWS. It covers four key modules: processing streaming data using Amazon Kinesis and Amazon MSK, running big data workloads on Amazon EMR, building data lakes with AWS Lake Formation, and querying data using Amazon Athena. Each module includes hands-on examples that demonstrate how to work with AWS services like Kinesis, EMR, Lake Formation, and Athena to efficiently handle large datasets, perform real-time analytics, and optimize query performance.

After completing the course, you will be able to design and implement solutions for processing streaming data using AWS services, manage big data workloads with Amazon EMR, build and manage data lakes on AWS, and optimize data queries with Amazon Athena. You will have the skills to select and use appropriate AWS services to handle different types of data processing tasks, from real-time analytics to large-scale data management and querying, empowering you to tackle complex data challenges in a cloud environment.

A basic understanding of cloud computing, particularly AWS, is recommended for this course. Familiarity with data processing concepts, such as big data, data lakes, and streaming data, will be helpful but is not required. Additionally, some knowledge of SQL and general data analytics concepts will make it easier to grasp the material. However, the course is structured to help learners develop skills from the ground up, making it suitable for those with a foundational understanding of these concepts.

This course is ideal for data engineers, cloud architects, and IT professionals who want to deepen their expertise in data processing and analytics using AWS. It is also suitable for developers looking to enhance their skills in real-time data processing, big data technologies, and serverless analytics. If you're interested in working with AWS to handle complex data workloads and build scalable data solutions, this course will provide the necessary skills.