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Introduction to NoSQL

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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4 Hours15 Videos59 Exercises

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Course Description

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.
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  1. 1

    Introduction to NoSQL databases

    Free

    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.

    Play Chapter Now
    Introduction to NoSQL
    50 xp
    What is NoSQL?
    50 xp
    Identifying NoSQL data stores
    100 xp
    NoSQL use-cases and applications
    50 xp
    Tabular NoSQL data stores
    50 xp
    Column-oriented databases
    50 xp
    Querying a column-oriented database
    100 xp
    Filtering a column-oriented database
    100 xp
    Non-tabular NoSQL data stores
    50 xp
    Identifying tabular and non-tabular NoSQL data stores
    100 xp
    Building queries with Postgres JSON
    100 xp
    Querying document databases with Postgres JSON
    100 xp
  2. 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.

    Play Chapter Now
    Populating column-oriented databases
    50 xp
    CREATE TABLE with Snowflake
    100 xp
    Populating Snowflake tables
    50 xp
    COPY INTO and CREATE TABLE ... AS with Snowflake
    100 xp
    Advanced column-oriented database techniques
    50 xp
    Micro-partitioning and data clustering with Snowflake
    50 xp
    Query pruning with micro-partitioning
    50 xp
    Leveraging micro-partitions and data clustering
    100 xp
    Analytics workflows for column-oriented databases
    50 xp
    Common table expressions with Snowflake
    100 xp
    Building an analytics workflow with Snowflake
    50 xp
    Materialized vs. non-materialized VIEWs
    100 xp
    Working with semi-structured data in Snowflake
    50 xp
    Semi-structured Snowflake data types
    50 xp
    Querying semi-structured data in Snowflake
    100 xp
    Querying nested semi-structured data
    100 xp
  3. 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.

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    Understanding JSON data in Postgres
    50 xp
    JSON and JSONB data in Postgres
    50 xp
    Executing queries with sqlalchemy and pandas
    100 xp
    Querying JSON and JSONB data from Postgres
    100 xp
    Storing JSON data in Postgres
    50 xp
    Loading Postgres with semi-structured data
    50 xp
    Converting tabular data to JSON
    100 xp
    Extracting keys from JSON objects with Postgres
    100 xp
    Querying JSON data using Postgres
    50 xp
    Querying top-level JSON data
    100 xp
    Finding the type of JSON data
    100 xp
    Working with nested JSON objects
    100 xp
    Filtering document databases with Postgres JSON
    100 xp
    Advanced Postgres JSON query techniques
    50 xp
    Arrow and hash arrow operators
    50 xp
    #> and #>>
    100 xp
    Extracting document data
    100 xp
    Manipulating document data
    100 xp
  4. 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.

    Play Chapter Now
    Introduction to key-value databases
    50 xp
    Key-value databases
    50 xp
    Key-value vs. document databases
    100 xp
    Connecting to a Redis cluster
    100 xp
    Storing and retrieving key-value data
    50 xp
    Storing key-value data with Redis
    100 xp
    Retrieving key-value data with Redis
    100 xp
    Storing Python dictionaries with Redis
    100 xp
    Graph databases
    50 xp
    Understanding graph databases
    50 xp
    Graph database providers
    50 xp
    Using graph databases
    100 xp
    Wrapping up!
    50 xp
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Collaborators

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George Boorman
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Arne Warnke
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Katerina Zahradova

Prerequisites

Database Design
Jake Roach HeadshotJake Roach

Data Engineer

Jake is a Data Engineer at Delaware North, and DataCamp Instructor. He and his team are building a state-of-the-art data platform for a multi-billion dollar organization, powered by Astronomer, Airflow, AWS, and Databricks. Born and raised in Buffalo, NY, when he's not working with data, you can find him out at the golf course playing a quick nine holes before dark!
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