What is Data Engineering?
📌 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.
🔹 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 inconsistent—making it difficult to use for analytics. Data Engineers ensure that data is:
✔ Collected from multiple sources (APIs, IoT devices, logs, databases)
✔ Cleaned and transformed into a usable format
✔ Stored efficiently in databases, data lakes, or warehouses
✔ Delivered to analysts & AI/ML models for business insights
Without Data Engineering, companies cannot harness the full potential of their data.
📌 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.
📍 Course Details
✅ Duration: 4 to 6 weeks (Flexible: Online/On-site)
✅ Format: Instructor-led training with hands-on projects
✅ 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
📚 Course Modules & Content
Module 1: Introduction to Data Engineering
📌 Understanding Data Engineering & its role in AI & analytics
📌 Data Engineer vs. Data Scientist vs. Data Analyst
📌 Overview of modern data architectures (OLTP, OLAP, Data Lakes, Data Warehouses)
Module 2: Data Modeling & Database Systems
📌 Relational Databases (MySQL, PostgreSQL, SQL Server)
📌 NoSQL Databases (MongoDB, Cassandra, DynamoDB)
📌 Data modeling techniques (ER models, star/snowflake schema)
📌 Query optimization & indexing
Module 3: ETL (Extract, Transform, Load) & Data Pipelines
📌 ETL vs. ELT – Key differences & best practices
📌 Building data pipelines using Apache Airflow, dbt, Talend
📌 Handling structured & unstructured data
📌 Data cleansing, transformation, and normalization
Module 4: Big Data Processing Frameworks
📌 Introduction to Big Data & Distributed Computing
📌 Apache Hadoop & MapReduce Fundamentals
📌 Apache Spark for real-time data processing
📌 Streaming Data Processing (Kafka, Flink, Spark Streaming)
Module 5: Cloud Data Engineering
📌 Cloud platforms: AWS, Google Cloud, Azure for Data Engineering
📌 AWS Redshift, Google BigQuery, Azure Synapse Analytics
📌 Serverless data processing with AWS Lambda & Google Cloud Functions
Module 6: Data Warehousing & Data Lakes
📌 Difference between Data Warehouses & Data Lakes
📌 Implementing data warehousing with Snowflake & Amazon Redshift
📌 Managing data lakes with Apache Iceberg, Delta Lake
Module 7: Scalable Data Engineering with DevOps & CI/CD
📌 Infrastructure as Code (IaC) for Data Pipelines
📌 CI/CD for data workflows (GitHub Actions, Jenkins)
📌 Data versioning & monitoring
Module 8: Security, Compliance, and Data Governance
📌 Data privacy laws (GDPR, CCPA)
📌 Role-Based Access Control (RBAC) & Data Encryption
📌 Auditing & logging best practices
🎓 Learning Outcomes
✔️ Master SQL, NoSQL, ETL, and data pipelines
✔️ Build scalable, real-time big data applications
✔️ Work with cloud data platforms like AWS, GCP, and Azure
✔️ Apply DevOps practices in data engineering workflows
✔️ Implement secure & compliant data solutions
💡 Why Join This Training?
🚀 Hands-on experience with industry-standard tools
🚀 Instructor-led sessions + mentorship
🚀 Project-based learning for real-world applications
🚀 Career support & certification upon completion
Are you ready to become a Data Engineer? Enroll today!
CONTACT
mail@global-skills-academy.com
