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IBM Skills Network

About this Course

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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.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

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Start instantly and learn at your own schedule.

Beginner Level

Approx. 14 hours to complete

English

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What you will learn

List basic skills required for an entry-level data engineering role.
Discuss various stages and concepts in the data engineering lifecycle.
Describe and provide examples of data engineering technologies such as Relational Databases, NoSQL Data Stores, Big Data Engines, and others.
Summarize concepts in data security, governance, and compliance.

Skills you will gain

Data Science
Database (DBMS)
NoSQL
SQL

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Beginner Level

Approx. 14 hours to complete

English

Could your company benefit from training employees on in-demand skills?

Try Coursera for Business

Instructors

Instructor rating

4.75/5 (613 Ratings)

Rav Ahuja

Global Program Director

IBM Skills Network

1,545,313 Learners

35 Courses

Priya Kapoor

Senior Instructional Designer & Content Developer

Skill-up Technologies

74,389 Learners

1 Course

Offered by

IBM Skills Network

IBM is the global leader in business transformation through an open hybrid cloud platform and AI, serving clients in more than 170 countries around the world. Today 47 of the Fortune 50 Companies rely on the IBM Cloud to run their business, and IBM Watson enterprise AI is hard at work in more than 30,000 engagements. IBM is also one of the world’s most vital corporate research organizations, with 28 consecutive years of patent leadership. Above all, guided by principles for trust and transparency and support for a more inclusive society, IBM is committed to being a responsible technology innovator and a force for good in the world.

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Syllabus - What you will learn from this course

Content Rating94%(8,093 ratings)

Week1

Week 1

3 hours to complete

What is Data Engineering?

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. At the end of the module, you will be guided to create a Lite account on IBM Cloud.

3 hours to complete

9 videos (Total 46 min), 2 readings, 5 quizzes

9 videos

Welcome to Introduction to Data Engineering3mModern Data Ecosystem 4mKey Players in the Data Ecosystem5mWhat is Data Engineering?4mViewpoints: Defining Data Engineering 4mViewpoints: Evolution of Data Engineering 7mResponsibilities and Skillsets of a Data Engineer5mViewpoints: Skills and Qualities to be a Data Engineer6mA Day in the Life of a Data Engineer3m

2 readings

Summary and Highlights10mSummary and Highlights10m

4 practice exercises

Practice Quiz6mGraded Quiz10mPractice Quiz5mGraded Quiz10m

Week2

Week 2

3 hours to complete

The Data Engineering Ecosystem

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. During the course of this module, you will be guided to provision an instance of IBM Db2 using the Cloud Lite account you created in the previous module.

3 hours to complete

17 videos (Total 104 min), 3 readings, 6 quizzes

17 videos

Overview of the Data Engineering Ecosystem4mTypes of Data4mUnderstanding Different Types of File Formats 4mSources of Data7mLanguages for Data Professionals8mViewpoints: Working with Varied Data Sources and Types6mOverview of Data Repositories4mRDBMS7mNoSQL7mData Warehouses, Data Marts, and Data Lakes7mViewpoints: Considerations for Choice of Data Repository6mETL, ELT, and Data Pipelines6mData Integration Platforms4mViewpoints: Tools, Databases, and Data Repositories of Choice6mFoundations of Big Data5mBig Data Processing Tools: Hadoop, HDFS, Hive, and Spark6mViewpoints: Impact of Big Data on Data Engineering3m

3 readings

Summary and Highlights10mSummary and Highlights10mSummary and Highlights10m

6 practice exercises

Practice Quiz10mGraded Quiz10mPractice Quiz12mGraded Quiz10mPractice Quiz5mGraded Quiz10m

Week3

Week 3

5 hours to complete

Data Engineering Lifecycle

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.

5 hours to complete

10 videos (Total 64 min), 5 readings, 10 quizzes

10 videos

Architecting the Data Platform7mFactors for Selecting and Designing Data Stores6mSecurity6mViewpoints: Importance of Data Security4mHow to Gather and Import Data6mData Wrangling7mTools for Data Wrangling5mQuerying and Analyzing Data5mPerformance Tuning and Troubleshooting7mGovernance and Compliance7m

5 readings

Summary and Highlights10mSummary and Highlights10mSummary and Highlights10mSummary and Highlights10mOptional: Overview of the DataOps Methodology10m

8 practice exercises

Practice Quiz6mGraded Quiz10mPractice Quiz6mGraded Quiz10mPractice Quiz5mGraded Quiz10mPractice Quiz2mGraded Quiz5m

Week4

Week 4

3 hours to complete

Career Opportunities and Data Engineering in Action

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.

3 hours to complete

6 videos (Total 36 min), 2 readings, 4 quizzes

6 videos

Career Opportunities in Data Engineering5mViewpoints: Get into Data Engineering7mData Engineering Learning Path3mViewpoints: What Do Employers Look for in a Data Engineer6mViewpoints: The Many Paths to Data Engineering5mViewpoints: Advice to Aspiring Data Engineers6m

2 readings

Summary and Highlights10mCongratulations and Next Steps2m

3 practice exercises

Practice Quiz5mGraded Quiz20mFinal Quiz 50m

Reviews

4.7

358 reviews

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3 stars
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2 stars
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1 star
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TOP REVIEWS FROM INTRODUCTION TO DATA ENGINEERING

by BHJan 19, 2022

Very informative and I like the usage of the IBM DB2 services as hands on labs. Although the instructions could use an update, the experience using the tool is great.

by MFMar 25, 2022

This course is optimal for the foundations and understanding of Data Engineering. Please take it and absorb all the knowledge and be amazed about your future with the Data Engineer certification.

by DFOct 20, 2021

This course was well made and informative. I went in knowing little about data engineering and now I have a much better understanding of what data engineering is all about.

by RPApr 16, 2022

This was an excellent introduction into data. It makes me excited to be learning about something that is very important in today's world and to be seeing it from a new perspective.

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Introduction to Data Engineering

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