Join Dan Sullivan for an in-depth discussion in this video Install MongoDB, part of Advanced NoSQL for Data Science.
- [Instructor] In this video, we will…install MongoDB Community Edition.…I'm starting at the MongoDB Download Center…for the Community Edition.…Now I'm going to scroll down, and we'll notice…the webpage has detected that I am running on a Mac.…So I have the option of downloading…a compressed file to install MongoDB.…I'm going to use a different installation method,…using the Homebrew Package Manager.…To do that, I'm going to go to…the Homebrew main page, which I have listed here.…I'm going to install Homebrew,…which is a package manager for the Mac OS X.…
I'm going to copy this link, and then I'm going…to open a terminal, and I'm going to paste that command.…Just enter in my password.…And this process is installing…the Homebrew Package Manager for me.…Now if you'll look just several lines up from the bottom,…it indicates that installation was successful.…Now if you ran into any problems,…for example, with permissions,…there would be additional information here.…So, I'm just going to clear this screen.…Now Homebrew should be up to date,…
The course begins with an introduction to NoSQL, and then delves into the specifics of document, wide-column, and graph databases. Learn key details for performing data preparation, exploration, and extraction for each type of NoSQL database. Review case studies that show how to use various NoSQL databases with popular data science tools, including the document database MongoDB, the wide-column database Cassandra, and the graph database Neo4j.
- NoSQL compared to traditional relational databases
- Performing common data science tasks
- Preparing data with document databases
- Manipulating data in NoSQL
- Preparing, exploring, extracting, and model building
- Working with document, wide-column, and graph databases
- Reviewing case studies using MongoDB, Cassandra, and Neo4j
Skill Level Advanced
1. Why NoSQL?
Types of NoSQL databases2m 20s
2. Perform Common Data Science Tasks with NoSQL Databases
3. Document Databases for Data Science
4. Wide-Column Databases for Data Science
5. Graph Databases for Data Science
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