Join Dan Sullivan for an in-depth discussion in this video Install Neo4j, part of Advanced NoSQL for Data Science.
- [Dan] We're going to use a graph database called Neo4j.…So, I've opened the browser…and gone to the Neo4j.com download site.…I'm going to select download community edition…by clicking on the button and it's detected…that I'm running a MAC, so I'm going to download…the MAC OS installation image by clicking on that…and that starts the download.…Okay, now that that's completely downloaded,…I'm going to click and select open on the image,…and now, as with other MAC applications,…I'm going to drag the icon to the application folder,…there we are.…
Now, I will start Neo4j,…and it's just prompted me and I will say yes…I want to open this.…There, now this the opening dialog box for Neo4j.…It indicates a database location,…I'm just going to accept the defaults…and now I'm going to start the server.…Now, it looks like Neo4j has started,…but just to make sure I'm going to click on this URL…which indicates that the Neo4j is running on the local host…and listening on port 7474.…And there we have it!…Now, when you first login to Neo4j,…
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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