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Professional Certificate in Cloud Data Engineering Tools
-- ViewingNowThe Professional Certificate in Cloud Data Engineering Tools is a comprehensive course that equips learners with essential skills for career advancement in the data engineering field. This program focuses on teaching the latest tools and technologies used in cloud data engineering, making it highly relevant in today's tech-driven industry.
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In this course, learners will gain hands-on experience with popular cloud platforms such as AWS, Google Cloud, and Microsoft Azure. They will also learn how to use big data tools like Hadoop, Spark, and Kafka to process and analyze large datasets. Moreover, the course covers essential data engineering concepts such as data pipelines, data warehousing, and data lake architectures.
With the increasing demand for data engineering professionals, this course offers a great opportunity for learners to upskill and stand out in a competitive job market. By the end of the program, learners will have a solid understanding of cloud data engineering tools and how to use them to solve real-world business problems.
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CourseDetails
- Cloud Data Engineering Tools Fundamentals: Introduction to cloud data engineering tools, benefits, and use cases. Overview of popular cloud data engineering platforms like AWS Glue, Azure Data Factory, and Google Cloud Dataflow.
- AWS Glue Basics: Hands-on experience with AWS Glue, including creating and managing Glue databases, tables, and crawlers. Understanding of ETL (Extract, Transform, Load) jobs in Glue.
- Azure Data Factory (ADF) Essentials: Learning ADF components, developing data pipelines, and implementing data flows. Integration with various data stores and services like Azure SQL Database, Azure Cosmos DB, and Azure Blob Storage.
- Google Cloud Dataflow for Data Processing: Overview of Apache Beam and Google Cloud Dataflow. Streaming and batch data processing, creating and managing Dataflow pipelines, and integrating with other Google Cloud services.
- Cloud Data Engineering Tools Security and Compliance: Best practices for securing cloud data engineering tools, data encryption, and access management. Compliance considerations and strategies for data governance.
- Cloud Data Engineering Tools Orchestration: Using Apache Airflow and other tools for workflow orchestration, including designing, scheduling, and monitoring data pipelines.
- Cloud Data Engineering Tools for Real-time Streaming: Hands-on experience with cloud data engineering tools for real-time streaming, including Apache Kafka, Apache Kinesis, and cloud-native solutions like AWS Kinesis Data Firehose and Azure Event Hubs.
- Cloud Data Engineering Tools Monitoring and Optimization: Monitoring and optimizing cloud data engineering tools using observability, logging, and tracing. Best practices for diagnosing issues, improving performance, and reducing costs.
- Please note that this is a high-level outline, and each unit may include several lessons or modules to provide comprehensive learning.
CareerPath
- Data Engineer — in-demand career path aligned with this qualification (35%)
- Cloud Solutions Architect — in-demand career path aligned with this qualification (25%)
- DevOps Engineer — in-demand career path aligned with this qualification (20%)
- Big Data Analyst — in-demand career path aligned with this qualification (15%)
- Data Scientist — in-demand career path aligned with this qualification (5%)
EntryRequirements
- BasicUnderstandingSubject
- ProficiencyEnglish
- ComputerInternetAccess
- BasicComputerSkills
- DedicationCompleteCourse
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- NotRegulatedAuthorized
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£149
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- ThreeFourHoursPerWeek
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£99
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- TwoThreeHoursPerWeek
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PROFESSIONAL CERTIFICATE IN CLOUD DATA ENGINEERING TOOLS
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London School of Planning and Management (LSPM)
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05 May 2025
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