Join Dan Sullivan for an in-depth discussion in this video Next Steps, part of Advanced NoSQL for Data Science.
- [Instructor] Now that we've concluded…the main content of this course,…I'd like to offer some further resources.…If you're interested in NoSQL databases…and would like to delve more…into their structure and organization,…I suggest my book, NoSQL for Mere Mortals.…If you are interested in learning more about MongoDB,…the online community at mongodb.com…is an excellent resource.…If Cassandra is of interest to you,…Planet Cassandra at planetcassandra.org…is an excellent resource, and finally,…the neo4j community has a portal supporting it,…at neo4j.com/community.…
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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