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NoSQL入門

基礎スキルレベル

更新日 2025/12

NoSQLを習得しデータ基盤を強化。Snowflakeでビッグデータを扱い、PostgresのJSONでドキュメントを処理し、Redisでキー値データを管理。

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SQLData Engineering

4時間

15 ビデオ

59 演習

4,450 XP

10,093

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コース説明

前提条件

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

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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

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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

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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!

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NoSQL入門

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