- Welcome to This Course
- Course Structure & Coverage
- How To Get Maximum Value From This Course
Online
₹ 649 3,499
Quick facts
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Medium of instructions
English
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Mode of learning
Self study
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Mode of Delivery
Video and Text Based
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Course overview
Data Engineering for Beginner using Google Cloud & Python online certification was developed by Timotius Pamungkas - Java Software Engineer & Architect and is available on Udemy, which is intended for applicants looking for a comprehensive training program that will assist them in acquiring knowledge of the foundational concepts and strategies associated with Google Cloud Platform (GPC) and Python programming for data engineering activities to become professionals.
Data Engineering for Beginner using Google Cloud & Python online course involves 8 hours of comprehensive lectures supported by 2 articles and downloadable resources, that are designed to provide applicants with an overview of the fundamentals of data engineering. Data Engineering for Beginner using Google Cloud & Python online training discusses strategies and techniques associated with topics like the relational database, database modeling, data lake, NoSQL database, and data warehousing as well as teaches about the tools like Hadoop, Pandas, Spark, Python, PostgreSQL, and more.
The highlights
- Certificate of completion
- Self-paced course
- 8 hours of pre-recorded video content
- 2 articles
- 1 downloadable resource
Program offerings
- Online course
- Learning resources
- 30-day money-back guarantee
- Unlimited access
- Accessible on mobile devices and tv
Course and certificate fees
Fees information
certificate availability
certificate providing authority
What you will learn
After completing the Data Engineering for Beginner using Google Cloud & Python certification course, applicants will acquire a solid understanding of the functionalities of the google cloud platform and Python for data engineering activities. In this data engineering course, applicants will learn the fundamentals involved with Pandas, Spark, Hadoop, and PostgreSQL for database modeling and relational database modeling as well as will acquire an understanding of the concepts associated with relational databases and NoSQL databases. In this data engineering certification, applicants will learn about strategies involved with data warehousing, normalization, denormalization, Elasticsearch, data lake, and Spark cluster.
The syllabus
Introduction
Introduction to Data Engineering
- What is Data Engineering?
- Data Engineering Example
- What is Data Modelling?
Database
- What is Database
- Relational Database
- When Not To Use Relational Database?
- NoSQL Database
- Demo : Postgresql
- Demo : Python for Postgresql
- Demo : Elasticsearch
- Demo : Python for Elasticsearch
Relational Database Model
- The Importance of Relational Data Model
- OLTP vs OLAP
- Database Normalization
- First Normal Form (1NF)
- Second Normal Form (2NF)
- Third Normal Form (3NF)
- Normalization Python Demo
- Normalization Tips
- Database Denormalization
- Denormalization Python Demo
- Fact & Dimension Tables
- Star Schema
- Star Schema Python Demo
- Snowflake Schema
- Galaxy Schema
- Extract Transform Load (ETL) & Staging Tables
- ETL & Staging Tables - Demo Overview
- ETL & Staging Tables - Python Demo 1
- ETL & Staging Tables - Python Demo 2
- To Insert or To Update?
- ETL & Staging Tables - Python Demo 3
- ETL & Staging Tables - Python Demo 4
- ETL & Staging Tables - Tips
NoSQL Database Model
- Basic NoSQL Concept
- CAP Theorem
- Denormalization on Elasticsearch
- Elasticsearch Basic Usage
- Elasticsearch Index & Document
- Elasticsearch ETL - Overview
- Elasticsearch Query DSL
- Elasticsearch ETL - Python Demo
Data Warehouse
- Business Perspective
- Technical Perspective
- More Fact & Dimension Table
- OLAP Cube
- On-Premise or Cloud?
- Various Techniques
- Demo Overview
- Demo 1 - PostgreSQL Data Warehouse
- Demo 2 - BigQuery Data Warehouse
- Demo 3 - Data Warehouse Operations
Numbers Every Engineer Should Know
- Numbers Every Engineer Should Know
- Small Numbers
- Big Numbers
Hadoop & Spark
- Hadoop Ecosystem
- Introducing Spark
- Spark Programming
- Data Formats
- Hello Spark
- Spark Demo - Dataframe
- Spark Demo - Spark SQL
- Spark & BigQuery - Setting Environment
- Spark & BigQuery - ETL Movies
- Spark & BigQuery - Lesson Learned
Spark Cluster on Google Cloud (Dataproc)
- Spark Cluster - Overview
- Demo : Big Data
- Google Dataproc
Data Lake
- Data Lake Overview
- Schema On Read
- Lake, not Swamp
- Google Data Catalog
Resources & References
- Source Code & Datasets Download
- Bonus & Discount Codes
Instructors
Mr Timotius Pamungkas
Java Software Engineer, Architect
Freelancer