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AWS Certified Data Engineer - Associate

AWS Certified Data Engineer - Associate

The AWS Certified Data Engineer - Associate course provides in-depth training on designing, implementing, and managing data solutions on AWS. It covers essential topics such as data ingestion, transformation, and security using services like Kinesis, Redshift, and S3. Participants will gain practical skills in handling data pipelines and optimizing data processing on the AWS platform.

Prerequisites:

Basic understanding of cloud computing concepts and AWS services.
Familiarity with data storage and ingestion processes.
Proficiency in SQL and database concepts.
Fundamental programming knowledge, preferably in Python or a similar language.
Experience with data manipulation and transformation.
Familiarity with core AWS services such as S3, Lambda, and IAM.

Target Audience:

Data Engineers
Data Architects
Database Administrators
ETL Developers
Cloud Solutions Architects
Big Data Professionals
DevOps Engineers
Machine Learning Engineers
IT Managers
Cloud Engineers
Data Analysts
System Administrators
Data Scientists
Software Engineers focusing on data operations
IT Professionals transitioning to cloud data management

Learning Objectives:

Data Ingestion:
- Read and ingest data from sources like Kinesis, MSK, and Redshift.
- Implement batch ingestion and configure schedulers and event triggers.
- Manage data distribution through throttling and fan-in/fan-out strategies.
Transform and Process Data:
- Optimize container usage for data performance.
- Integrate and transform data from multiple sources using AWS services like EMR, Glue, and Lambda.
- Convert data formats and debug transformation failures.
Choose and Configure Data Stores:
- Implement and configure storage solutions including Redshift, DynamoDB, and S3.
- Integrate AWS Transfer Family for data migration.
- Utilize advanced query and view capabilities with Redshift Federated Queries and Spectrum.
Data Cataloging and Management:
- Use Glue Data Catalog and Hive Metastore to build and reference data catalogs.
- Synchronize partitions and manage data lifecycle policies in S3 and DynamoDB.

(4.4 Ratings)

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Live Online Training (Duration : 24 Hours)

Guaranteed to run classes as per your convenient time zone

Industry experienced & certified trainers

Query Handling session by technical expert after 2 month completion of training

Career path counselling

Custom tailored training as per the requirement

Exam assistance

Exam Mock papers

100% Quality assurance with certified & industry experienced Trainer

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Download Course Contents

AWS Certified Data Engineer - Associate

Prerequisites:

Basic understanding of cloud computing concepts and AWS services.
Familiarity with data storage and ingestion processes.
Proficiency in SQL and database concepts.
Fundamental programming knowledge, preferably in Python or a similar language.
Experience with data manipulation and transformation.
Familiarity with core AWS services such as S3, Lambda, and IAM.

Target Audience:

Data Engineers
Data Architects
Database Administrators
ETL Developers
Cloud Solutions Architects
Big Data Professionals
DevOps Engineers
Machine Learning Engineers
IT Managers
Cloud Engineers
Data Analysts
System Administrators
Data Scientists
Software Engineers focusing on data operations
IT Professionals transitioning to cloud data management

Learning Objectives:

Data Ingestion:
- Read and ingest data from sources like Kinesis, MSK, and Redshift.
- Implement batch ingestion and configure schedulers and event triggers.
- Manage data distribution through throttling and fan-in/fan-out strategies.
Transform and Process Data:
- Optimize container usage for data performance.
- Integrate and transform data from multiple sources using AWS services like EMR, Glue, and Lambda.
- Convert data formats and debug transformation failures.
Choose and Configure Data Stores:
- Implement and configure storage solutions including Redshift, DynamoDB, and S3.
- Integrate AWS Transfer Family for data migration.
- Utilize advanced query and view capabilities with Redshift Federated Queries and Spectrum.
Data Cataloging and Management:
- Use Glue Data Catalog and Hive Metastore to build and reference data catalogs.
- Synchronize partitions and manage data lifecycle policies in S3 and DynamoDB.

SpireTec solutions is the latest technology enabled I.Tmanagement training company specialized in offering 1500+ courses with the state of art training facilities backed by a team of industry experts in various domains with assuring best quality services.

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Because SpireTec aims for the personal & professional growth of you as individual & corporate as a whole, providing training on the latest and updated versions in the designated domains.

It is preferable but not mandatory to have domain experience in the area of your interest in which you want to opt training, supported by good English communication skills, a good Wi-Fi and computer or laptop system in case you want remote training.

Spire Tec aims and ensure to offer finest and world-class training to the participants by giving them a proper counselling and a guided career path by our industry experts which leads guaranteed success for you in the corporate world.

We offer online training (1-1, Group training), Classroom training, Onsite training with state of art facilities.

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