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Data Engineering Training Course

Home Β» Blog Β» Data Engineering Training Course
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What is Data Engineering

Data Engineering Training Course

  • March 31, 2025
  • Com 0
Global Skills Academy

What is Data Engineering?

πŸ“Œ Definition

Data Engineering is the field of designing, building, and managing the infrastructure and systems that allow organizations to collect, store, process, and analyze large amounts of data efficiently. It focuses on the development of data pipelines, databases, and big data frameworks to ensure that data is accessible, reliable, and optimized for analysis and decision-making.


πŸ”Ή Why is Data Engineering Important?

In the era of big data, AI, and machine learning, organizations generate and process massive volumes of data. Raw data is often messy, unstructured, and inconsistentβ€”making it difficult to use for analytics. Data Engineers ensure that data is:

βœ” Collected from multiple sources (APIs, IoT devices, logs, databases)
βœ” Cleaned and transformed into a usable format
βœ” Stored efficiently in databases, data lakes, or warehouses
βœ” Delivered to analysts & AI/ML models for business insights

Without Data Engineering, companies cannot harness the full potential of their data.

πŸ“Œ Data Engineering Training Course

🎯 Course Objective:

This training program equips participants with the fundamentals of data engineering, focusing on data pipelines, ETL processes, big data frameworks, cloud data solutions, and real-world applications in AI, machine learning, and business intelligence.


πŸ“ Course Details

βœ… Duration: 4 to 6 weeks (Flexible: Online/On-site)
βœ… Format: Instructor-led training with hands-on projects
βœ… Who Should Attend?

  • Data Analysts looking to transition into Data Engineering
  • Software Engineers & Developers working with data-driven applications
  • IT Professionals & Database Administrators
  • AI & ML Engineers needing strong data foundations
  • Business Intelligence (BI) Professionals
  • Fresh graduates & students interested in data engineering careers

πŸ“š Course Modules & Content

Module 1: Introduction to Data Engineering

πŸ“Œ Understanding Data Engineering & its role in AI & analytics
πŸ“Œ Data Engineer vs. Data Scientist vs. Data Analyst
πŸ“Œ Overview of modern data architectures (OLTP, OLAP, Data Lakes, Data Warehouses)

Module 2: Data Modeling & Database Systems

πŸ“Œ Relational Databases (MySQL, PostgreSQL, SQL Server)
πŸ“Œ NoSQL Databases (MongoDB, Cassandra, DynamoDB)
πŸ“Œ Data modeling techniques (ER models, star/snowflake schema)
πŸ“Œ Query optimization & indexing

Module 3: ETL (Extract, Transform, Load) & Data Pipelines

πŸ“Œ ETL vs. ELT – Key differences & best practices
πŸ“Œ Building data pipelines using Apache Airflow, dbt, Talend
πŸ“Œ Handling structured & unstructured data
πŸ“Œ Data cleansing, transformation, and normalization

Module 4: Big Data Processing Frameworks

πŸ“Œ Introduction to Big Data & Distributed Computing
πŸ“Œ Apache Hadoop & MapReduce Fundamentals
πŸ“Œ Apache Spark for real-time data processing
πŸ“Œ Streaming Data Processing (Kafka, Flink, Spark Streaming)

Module 5: Cloud Data Engineering

πŸ“Œ Cloud platforms: AWS, Google Cloud, Azure for Data Engineering
πŸ“Œ AWS Redshift, Google BigQuery, Azure Synapse Analytics
πŸ“Œ Serverless data processing with AWS Lambda & Google Cloud Functions

Module 6: Data Warehousing & Data Lakes

πŸ“Œ Difference between Data Warehouses & Data Lakes
πŸ“Œ Implementing data warehousing with Snowflake & Amazon Redshift
πŸ“Œ Managing data lakes with Apache Iceberg, Delta Lake

Module 7: Scalable Data Engineering with DevOps & CI/CD

πŸ“Œ Infrastructure as Code (IaC) for Data Pipelines
πŸ“Œ CI/CD for data workflows (GitHub Actions, Jenkins)
πŸ“Œ Data versioning & monitoring

Module 8: Security, Compliance, and Data Governance

πŸ“Œ Data privacy laws (GDPR, CCPA)
πŸ“Œ Role-Based Access Control (RBAC) & Data Encryption
πŸ“Œ Auditing & logging best practices

πŸŽ“ Learning Outcomes

βœ”οΈ Master SQL, NoSQL, ETL, and data pipelines
βœ”οΈ Build scalable, real-time big data applications
βœ”οΈ Work with cloud data platforms like AWS, GCP, and Azure
βœ”οΈ Apply DevOps practices in data engineering workflows
βœ”οΈ Implement secure & compliant data solutions


πŸ’‘ Why Join This Training?

πŸš€ Hands-on experience with industry-standard tools
πŸš€ Instructor-led sessions + mentorship
πŸš€ Project-based learning for real-world applications
πŸš€ Career support & certification upon completion

Are you ready to become a Data Engineer? Enroll today!

CONTACT

mail@thegreensamanshop.com


Tags:
Cloud Data EngineeringData Engineer training courseData Engineering Training CourseData Modeling & Database SystemsData Warehousing & Data LakesIntroduction to Data EngineeringWhat is Data Engineering
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