Fundamentals of Data Engineering – Data Lakes and Data Warehouses Training

Fundamentals of Data Engineering – Data Lakes and Data Warehouses Training

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 2Month/20 Hour                                                   Price:85,000

                                                                                      80,000

Fundamentals of Data Engineering – Data Lakes and Data Warehouses Training

This course provides a comprehensive introduction to data engineering with a focus on data lakes and data warehouses. Over the span of two months, students will learn about the architecture, tools, and best practices used in managing large-scale data storage solutions. Through hands-on projects and real-world examples, participants will gain the skills needed to design, build, and maintain robust data systems.


Key Learnings:

Understand the concepts and architecture of data lakes and data warehouses.
Learn about different data storage technologies and their use cases.
Gain proficiency in data ingestion, ETL processes, and data transformation.
Explore data governance, security, and compliance practices.
Develop skills in data querying, analysis, and reporting.
Hands-on experience with industry-standard tools and platforms.

Course Outline:

Module 1: Introduction to Data Engineering 
Lesson 1.1: What is Data Engineering?
Lesson 1.2: Role of Data Engineers
Lesson 1.3: Overview of Data Storage Solutions

Module 2: Data Lakes Fundamentals 
Lesson 2.1: Introduction to Data Lakes
Lesson 2.2: Data Lake Architecture
Lesson 2.3: Data Lake Implementation
Lesson 2.4: Data Ingestion and Processing in Data Lakes
Lesson 2.5: Tools for Building Data Lakes (e.g., Apache Hadoop, Apache Spark)
Lesson 2.6: Hands-on Project: Setting Up a Data Lake

Module 3: Data Warehouses Fundamentals (Weeks 4-5)
Lesson 3.1: Introduction to Data Warehouses
Lesson 3.2: Data Warehouse Architecture
Lesson 3.3: Star Schema and Snowflake Schema
Lesson 3.4: ETL Processes in Data Warehouses
Lesson 3.5: Tools for Building Data Warehouses (e.g., Amazon Redshift, Google BigQuery)
Lesson 3.6: Hands-on Project: Designing a Data Warehouse

Module 4: Data Integration and ETL (Week 6)
Lesson 4.1: Data Integration Techniques
Lesson 4.2: ETL vs. ELT
Lesson 4.3: Popular ETL Tools (e.g., Apache NiFi, Talend)
Lesson 4.4: Hands-on Project: Building an ETL Pipeline

Module 5: Data Governance, Security, and Compliance
Lesson 5.1: Importance of Data Governance
Lesson 5.2: Data Security Best Practices
Lesson 5.3: Compliance and Legal Considerations (e.g., GDPR)
Lesson 5.4: Implementing Data Governance Frameworks

Module 6: Data Querying and Analysis 
Lesson 6.1: Query Languages (e.g., SQL, NoSQL)
Lesson 6.2: Data Analysis Techniques
Lesson 6.3: Reporting and Visualization Tools (e.g., Tableau, Power BI)
Lesson 6.4: Hands-on Project: Data Analysis and Reporting

International Student Fees: USD950$

Job Interview Preparation  (Soft Skills Questions & Answers)
Tough Open-Ended Job Interview Questions
What to Wear for Best Job Interview Attire
Job Interview Question- What are You Passionate About?
How to Prepare for a Job Promotion Interview

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Flexible Class Options
Week End Classes For Professionals  SAT | SUN
Corporate Group Training Available
Online Classes – Live Virtual Class (L.V.C), Online Training

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