In this chapter, you’ll learn what data engineering is and why demand for them is increasing. You’ll then discover where data engineering sits in relation to the data science lifecycle, how data engineers differ from data scientists, and have an introduction to your first complete data pipeline.

Data engineering and big data

Go with the flow

Not responsible

Big time

Data engineers vs. data scientists

Tell me the truth

Who is it

The data pipeline

It's not true

Pipeline

What is data engineering?

It’s time to talk about data storage—one of the main responsibilities for a data engineer. In this chapter, you’ll learn how data engineers manage different data structures, work in SQL—the programming language of choice for querying and storing data, and implement appropriate data storage solutions with data lakes and data warehouses.

Data structures

Structures

Options

Structured

Semi-structured

Unstructured

What's the difference

SQL databases

We can work it out

Columns

Data engineers

Data scientist

Different breeds

Data warehouses and data lakes

Tell the truth

A data lake

A data warehouse

Our warehouse (in the middle of our street)

Storing data

Data engineers make life easy for data scientists by preparing raw data for analysis using different processing techniques at different steps. These steps need to be combined to create pipelines, which is when automation comes into play. Finally, data engineers use parallel and cloud computing to keep pipelines flowing smoothly.

Processing data

Connect the dots

Scheduling data

Schedules

One or the other

Parallel computing

Whenever, whenever

Parallel universe

Cloud computing

Obscured by clouds

Somewhere I belong

We are the champions

Moving and processing data

Lexicon

Course Glossary: Understanding Data Engineering

In 2019, the average salary for data engineers overtook data scientists. How did this happen? Companies wanting to find the gold within their data realized it wasn’t possible if they hadn’t yet built the mine. Data engineers lay the foundations that make data science possible.
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In this course, you’ll learn about a data engineer’s core responsibilities, how they differ from data scientists, and facilitate the flow of data through an organization. Through hands-on exercises you’ll follow Spotflix, a fictional music streaming company, to understand how their data engineers collect, clean, and catalog their data. By the end of the course, you’ll understand what your company's data engineers do, be ready to have a conversation with a data engineer, and have a solid foundation to start your own data engineer journey.

The videos contain live transcripts, which can be accessed by clicking "Show transcript" at the bottom left of the videos.

The course glossary can be found on the right in the resources section.

To obtain CPE credits you need to complete the course and reach a score of 70% on the qualified assessment. You can navigate to the assessment by clicking on the CPE credits callout on the right.

<h2> Understand the Basics of Data Engineering </h2>
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In this course, you’ll learn about a data engineer’s core responsibilities, how they differ from data scientists, and facilitate the flow of data through an organization. Through hands-on exercises you’ll follow Spotflix, a fictional music streaming company, to understand how their data engineers collect, clean, and catalog their data. 
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<h2> Apply in Personal Cases</h2>
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By the end of the course, you’ll understand what your company's data engineers do, be ready to have a conversation with a data engineer, and have a solid foundation to start your own data engineer journey.

Discover how data engineers lay the groundwork that makes data science possible. No coding involved!

Data Engineering for Everyone

Understanding Data Engineering

Yardımcı Veri Mühendisi SQL içinde

Veri Analisti Databricks'te

Veri Konularını Anlama

Creating a new table to store the songs customers listened to the most over the past year.

Updating an artist's table after they edited their biography.

Modifying the whole songs table to remove trailing spaces entered by mistake in front of the title.

Querying the top songs of the past year to identify which genre dominated.

Querying the lyrics table to find all the songs that have 'data' in the title.

Querying the artist table to find all the bands that come from France.

Different breeds

Understanding Data Engineering

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