Start your journey in one of the fastest growing professions today with this beginner-friendly Data Engineering course! You will be introduced to the core concepts, processes, and tools you need to know in order to get a foundational knowledge of data engineering. as well as the roles that Data Engineers, Data Scientists, and Data Analysts play in the ecosystem.
Introduction to Data Engineering
Introduction to Data Engineering
This course is part of multiple programs.
Instructors: Rav Ahuja
Sponsored by Southeastern University
163,446 already enrolled
Gain insight into a topic and learn the fundamentals.
4.7
(2,803 reviews)
Beginner level
Recommended experience
Flexible schedule
Approx. 13 hours
Learn at your own pace
95%
Most learners liked this course
What you'll learn
List basic skills required for an entry-level data engineering role.
Discuss various stages and concepts in the data engineering lifecycle.
Describe data engineering technologies such as Relational Databases, NoSQL Data Stores, and Big Data Engines.
Summarize concepts in data security, governance, and compliance.
Details to know
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Assessments
21 assignments
Taught in English
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There are 4 modules in this course
In this module, you will learn about the different entities that come together to form a modern data ecosystem and the role Data Engineers, Data Scientists, Data Analysts, Business Analysts, and Business Intelligence Analysts play in this ecosystem. You will learn what data engineering is and the key tasks in a data engineering lifecycle. You will also gain an understanding of the responsibilities of a data engineer, the skillsets they need in order to be successful, and what a typical day in the life of a data engineer looks like.
What's included
9 videos2 readings4 assignments
In this module, you will learn about the data engineering ecosystem, the different types of data structures, file formats, sources of data, and the languages data professionals use in their day-to-day tasks. You will gain an understanding of several different types of data repositories such as relational and non-relational databases, data warehouses, data marts, and data lakes. You will learn about ETL and ELT processes, data pipelines, and data integration platforms. You will also gain an understanding of what big data is, and the tools used for processing and storing big data. At the end of this module, you will be guided to create an IBM Cloud account, and provision an instance of IBM Db2.
What's included
18 videos4 readings6 assignments1 app item3 plugins
In this module, we will walk you through the data engineering lifecycle. You will learn about the architecture of a data platform, factors for selecting and designing data stores, and the different facets of security as it applies to data platforms and data lifecycle management. You will also learn about the process, steps, and tools used for gathering, importing, wrangling, and querying data. You will gain an understanding of performance monitoring and the steps you can take to troubleshoot performance issues. We will also talk about governance regulations, why we need them, and how technology enables compliance to regulations. During the course of this module, you will be guided to load data from a CSV file into the IBM Db2 instance you created in the previous module. You will also be guided to explore your dataset using some basic SQL queries that will be provided to you.
What's included
10 videos5 readings8 assignments2 app items2 plugins
In this module, you will learn about career opportunities in the field of Data Engineering and the different paths that you can take for getting skilled as a Data Engineer. At the end of the module, you will be presented with the final graded assignment which is divided into two parts. The first part of the final assignment includes a couple of quiz questions and the second part includes open-ended questions that will be reviewed and graded by a peer.
What's included
6 videos2 readings3 assignments1 peer review2 plugins
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