CF

Choosing Data Stores

1h 25m 31s
English
Paid

Choosing Data Stores is a 16-lesson 1 hour 25 minutes self-paced course by Andreas Kretz. Choosing the right data storage is a fundamental task in creating a data platform and building pipelines.

Course facts

Lessons
16
Duration
1 hour 25 minutes
Level
All levels
Language
English
Updated
Instructor
Andreas Kretz
Price
Premium

Choosing the right data storage is a fundamental task in creating a data platform and building pipelines. This course is dedicated to guiding you through this important topic.

Overview of Data Storage Types

Throughout this course, we will explore different types of data storage solutions including relational and NoSQL databases, as well as data warehouses and data lakes. You will learn the appropriate scenarios for using each type of storage and how to effectively integrate them into your architecture.

Completing this course will equip you with the necessary knowledge to understand various data storage solutions and help you make informed decisions, enhancing your capabilities as a data engineer. Future courses will dive deeper into specific technologies within each category.

Basics of Data Warehousing

We begin by discussing foundational principles: the key differences between OLTP (Operational Transactional Systems) and OLAP (Analytical Systems), and their respective use cases. You will also learn about ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform), and how these processes influence the selection of data warehouses. At the end of this section, additional resources will be provided for further exploration and comparison of different data warehouse types.

Understanding Relational Databases

This section offers a step-by-step guide to selecting a suitable data storage solution for your projects. You will gain an in-depth understanding of relational databases, including CRUD operations and the ACID principles, along with examples from specific Database Management Systems (DBMS).

Exploring NoSQL Databases

In this part of the course, you will discover what NoSQL databases are, including various types such as document-based, columnar, temporal, and search databases. We will examine their unique characteristics and suitable applications. Additionally, we will discuss the trade-offs between read and write speeds and emphasize the importance of setting goals when selecting storage solutions.

Data Warehouses vs. Data Lakes

The course concludes with a detailed comparison of data warehouses and data lakes. You will learn about the differences between these storage solutions and the specific use cases where each excels. This knowledge will further aid in your decision-making process when architecting data platforms.

Who teaches Choosing Data Stores? Andreas Kretz

Andreas Kretz thumbnail

Andreas Kretz is a German data engineer and one of the most widely followed independent voices on data engineering as a career discipline. He runs the Plumbers of Data Science brand and has been publishing tutorial material continuously since the field consolidated around the modern lake-house stack (Spark, Kafka, Snowflake, Databricks, Airflow).

His CourseFlix listing is the largest single-author catalog under this source — over thirty courses spanning data-pipeline construction, streaming architectures, the cloud-native data stack on AWS / Azure / GCP, the Python and Scala tooling that dominates the field, and the soft-skills / career side of breaking into data engineering. Material is paid and aimed at engineers transitioning into data work or already-working data engineers picking up specific tools.

What lessons are included in Choosing Data Stores?

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#1: Introduction
All Course Lessons (16)
#Lesson TitleDurationAccess
1
Introduction Demo
02:10
2
OLTP vs OLAP
07:35
3
ETL vs ELT
05:46
4
Data Stores Ranking
04:06
5
How to Choose Data Stores
08:12
6
Relational Databases
06:35
7
NoSQL Basics
10:40
8
Document Stores
05:57
9
Time Series Databases
05:01
10
Search Engines
04:19
11
Wide Column Stores
04:23
12
Key Value Stores
05:00
13
Graph Databases
01:06
14
Data Warehouses
05:33
15
Data Lakes
07:11
16
Conclusion
01:57
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Frequently asked questions

What prerequisites should I have before taking this course?
Before enrolling, it's beneficial to have a foundational understanding of data engineering concepts. Familiarity with databases and data processing techniques will help you grasp the topics, such as OLTP and OLAP systems, ETL and ELT processes, and various data storage solutions including relational databases and NoSQL systems.
What types of data storage solutions are covered in the course?
The course covers a range of data storage solutions, including relational databases, NoSQL databases, data warehouses, and data lakes. Specific topics include document stores, time series databases, search engines, wide column stores, key-value stores, and graph databases. These lessons help you understand the appropriate scenarios for each type and how to integrate them into data architectures.
Who is the target audience for this course?
This course is designed for aspiring and current data engineers who need to make informed decisions about data storage solutions. It is also suitable for software engineers and IT professionals interested in understanding different data storage architectures and enhancing their capabilities in data platform creation and pipeline building.
How does the depth of this course compare to other courses on data storage?
This course provides a broad overview of various data storage solutions, focusing on when and how to use them effectively. It covers foundational concepts such as OLTP vs OLAP systems and ETL vs ELT processes. Future courses will delve deeper into specific technologies within each storage category, building on the foundational knowledge gained here.
What specific tools or platforms are discussed in the course?
While the course provides an overview of the types of data storage solutions, such as relational and NoSQL databases, it does not focus on specific tools or platforms. The emphasis is on understanding the characteristics and use cases of each type of data store, rather than the specifics of tools like PostgreSQL or MongoDB.
What topics are not covered in this course?
The course does not cover specific database management systems or advanced configuration and optimization of data stores. It also does not delve into the implementation details of specific technologies within each storage type, which will be addressed in future courses that focus on individual technologies.
How can the knowledge gained from this course benefit my career in data engineering?
By completing this course, you will gain a solid understanding of different data storage solutions and their appropriate use cases, enhancing your ability to design effective data architectures. This knowledge is crucial for data engineers tasked with building and optimizing data platforms and pipelines, and it lays the groundwork for further specialization in data storage technologies.