IBM - Introduction to Data Engineering
4.5 /5- Offered byCoursera
Introduction to Data Engineering at Coursera Overview
Duration | 10 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Beginner |
Official Website | Explore Free Course  |
Credential | Certificate |
Introduction to Data Engineering at Coursera Highlights
- Shareable Certificate Earn a Certificate upon completion
- 100% online Start instantly and learn at your own schedule.
- Course 1 of 5 in the Data Engineering Foundations Specialization
- Flexible deadlines Reset deadlines in accordance to your schedule.
- Beginner Level
- Approx. 10 hours to complete
- English Subtitles: English
Introduction to Data Engineering at Coursera Course details
- This course introduces you to the core concepts, processes, and tools you need to know in order to get a foundational knowledge of data engineering. You will gain an understanding of the modern data ecosystem and the role Data Engineers, Data Scientists, and Data Analysts play in this ecosystem.
- The Data Engineering Ecosystem includes several different components. It includes disparate data types, formats, and sources of data. Data Pipelines gather data from multiple sources, transform it into analytics-ready data, and make it available to data consumers for analytics and decision-making. Data repositories, such as relational and non-relational databases, data warehouses, data marts, data lakes, and big data stores process and store this data. Data Integration Platforms combine disparate data into a unified view for the data consumers. You will learn about each of these components in this course. You will also learn about Big Data and the use of some of the Big Data processing tools.
- A typical Data Engineering lifecycle includes architecting data platforms, designing data stores, and gathering, importing, wrangling, querying, and analyzing data. It also includes performance monitoring and finetuning to ensure systems are performing at optimal levels. In this course, you will learn about the data engineering lifecycle. You will also learn about security, governance, and compliance.
- Data Engineering is recognized as one of the fastest-growing fields today. The career opportunities available in the field and the different paths you can take to enter this field are discussed in the course.
- The course also includes hands-on labs that guide you to create your IBM Cloud Lite account, provision a database instance, load data into the database instance, and perform some basic querying operations that help you understand your dataset.
Introduction to Data Engineering at Coursera Curriculum
What is Data Engineering?
Welcome to Introduction to Data Engineering
Modern Data Ecosystem
Key Players in the Data Ecosystem
What is Data Engineering?
Viewpoints: Defining Data Engineering
Viewpoints: Evolution of Data Engineering
Responsibilities and Skillsets of a Data Engineer
Viewpoints: Skills and Qualities to be a Data Engineer
A Day in the Life of a Data Engineer
Summary and Highlights
Summary and Highlights
Practice Quiz
Graded Quiz
Practice Quiz
Graded Quiz
The Data Engineering Ecosystem
Overview of the Data Engineering Ecosystem
Types of Data
Understanding Different Types of File Formats
Sources of Data
Languages for Data Professionals
Viewpoints: Working with Varied Data Sources and Types
Overview of Data Repositories
RDBMS
NoSQL
Data Warehouses, Data Marts, and Data Lakes
Viewpoints: Considerations for Choice of Data Repository
ETL, ELT, and Data Pipelines
Data Integration Platforms
Viewpoints: Tools, Databases, and Data Repositories of Choice
Foundations of Big Data
Big Data Processing Tools: Hadoop, HDFS, Hive, and Spark
Viewpoints: Impact of Big Data on Data Engineering
Summary and Highlights
Summary and Highlights
Summary and Highlights
Practice Quiz
Graded Quiz
Practice Quiz
Graded Quiz
Practice Quiz
Graded Quiz
Data Engineering Lifecycle
Architecting the Data Platform
Factors for Selecting and Designing Data Stores
Security
Viewpoints: Importance of Data Security
How to Gather and Import Data
Data Wrangling
Tools for Data Wrangling
Querying and Analyzing Data
Performance Tuning and Troubleshooting
Governance and Compliance
Summary and Highlights
Summary and Highlights
Summary and Highlights
Summary and Highlights
Optional: Overview of the DataOps Methodology
Practice Quiz
Graded Quiz
Practice Quiz
Graded Quiz
Practice Quiz
Graded Quiz
Practice Quiz
Graded Quiz
Career Opportunities and Data Engineering in Action
Career Opportunities in Data Engineering
Viewpoints: Get into Data Engineering
Data Engineering Learning Path
Viewpoints: What Do Employers Look for in a Data Engineer
Viewpoints: The Many Paths to Data Engineering
Viewpoints: Advice to Aspiring Data Engineers
Summary and Highlights
Congratulations and Next Steps
Practice Quiz
Graded Quiz
Final Quiz
Introduction to Data Engineering at Coursera Admission Process
Important Dates
Other courses offered by Coursera
Student Forum
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