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Introduction to NoSQL

GrundläggandeKunskapsnivå

Uppdaterad 2025-12

Conquer NoSQL and supercharge data workflows. Learn Snowflake to work with big data, Postgres JSON for handling document data, and Redis for key-value data.

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SQLData Engineering

4 tim

15 videor

59 Övningar

4,450 XP

10,093

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Kursbeskrivning

In recent years, NoSQL databases have seen a surge in popularity due to their ability to handle large volumes of unstructured data. Learning to leverage NoSQL tools such as column-oriented, document, key-value, and graph databases allows data engineers, analysts, and scientists to interact with a wider breadth of data. These NoSQL databases bring additional functionality to data storage and retrieval that isn’t available in traditional relational databases.

Column-oriented databases

Dive into the world of column-oriented databases and their role in the evolution of data warehouses. Practice working with Snowflake to create and update column-oriented tables, as well as optimize table design for performance. Explore Snowflake’s advanced functionality to work with semi-structured data.

Document databases

Learn to use Postgres JSON as a tool to query document and object-oriented databases and the variety of data types that this technology supports. Hone your skills working with data stored in an array, as well as nested data.

Key-value and graph databases

Grow comfortable working with key-value databases and learn when this NoSQL data store is best applied. Practice using Redis to load and query data and experience the lightning-fast performance of in-memory databases. Explore graph databases and their use cases in data workflows.

Förkunskapskrav

Database Design

1

Introduction to NoSQL databases

Explore the basics of NoSQL databases, and how they're used in a modern data architecture. Learn to identify the pros and cons of using column-oriented, document, key-value, and graph databases to make data available to downstream processes and data consumers.

Introduction to NoSQL

Querying NoSQL databases

Exploring document data

NoSQL use-cases and applications

Tabular NoSQL data stores

Column-oriented databases

Querying a column-oriented database

Filtering a column-oriented database

Non-tabular NoSQL data stores

Identifying tabular and non-tabular NoSQL data stores

Querying document databases

Querying nested documents with Postgres JSON

2

Column-oriented Databases

Dive into column-oriented databases with the help of Snowflake. Learn to populate Snowflake tables using a number of tools, and uncover the fundamentals of micro-partitioning and data clustering to optimize query performance with query pruning. Leverage common table expressions, materialized and non-materialized views to streamline analytics workflows. Step into semi-structured data with Snowflake's VARIANT types.

Populating column-oriented databases

CREATE TABLE with Snowflake

Populating Snowflake tables

COPY INTO and CREATE TABLE ... AS with Snowflake

Advanced column-oriented database techniques

Micro-partitioning and data clustering with Snowflake

Query pruning with micro-partitioning

Leveraging micro-partitions and data clustering

Analytics workflows for column-oriented databases

Common table expressions with Snowflake

Building an analytics workflow with Snowflake

Materialized vs. non-materialized VIEWs

Working with semi-structured data in Snowflake

Semi-structured Snowflake data types

Querying semi-structured data in Snowflake

Querying nested semi-structured data

3

Document Databases

Dive deep into the world of document data with Postgres JSON, and explore the intricacies of semi-structured data. Learn how to extract and transform top-level and nested document data using a number of built-in operators and functions.

Understanding JSON data in Postgres

JSON and JSONB data in Postgres

Executing queries with sqlalchemy and pandas

Querying JSON and JSONB data from Postgres

Storing JSON data in Postgres

Loading Postgres with semi-structured data

Converting tabular data to JSON

Extracting keys from JSON objects with Postgres

Querying JSON data using Postgres

Querying top-level JSON data

Finding the type of JSON data

Working with nested JSON objects

Filtering document databases with Postgres JSON

Advanced Postgres JSON query techniques

Arrow and hash arrow operators

Extracting document data

Manipulating document data

4

Key-value and Graph Databases

Take your NoSQL skills to the next level by mastering the fundamentals of key-value databases. Explore common use-cases for key-value data, and learn how to use Redis and Python to read and write data. Wrap up with a basic overview of graph databases, and their place in the modern data stack.

Introduction to key-value databases

Key-value databases

Key-value vs. document databases

Connecting to a Redis cluster

Storing and retrieving key-value data

Storing key-value data with Redis

Retrieving key-value data with Redis

Storing Python dictionaries with Redis

Graph databases

Understanding graph databases

Graph database providers

Using graph databases

Wrapping up!

Introduction to NoSQL

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