Join Dan Sullivan for an in-depth discussion in this video Install the Java Development Kit, part of Advanced NoSQL for Data Science.
- In preparation for installing Cassandra,…we're going to install Java JDK.…I'm at the Oracle Java download page,…and I'm just going to scroll down to Download JDK,…and I'm going to click on that.…This will bring me to a download page.…I'm going to select the latest version.…I'm going to first accept the license agreement,…and then I'm going to pick the version that I need.…I'm running Mac OSX, so I'm going to choose the Mac installer,…and I'm clicking on that, and that'll begin the download.…The download is complete, so I'm going to click…on the arrow button and select Open.…
I now have a Java Development Kit, or JDK, icon…for the installer.…I'm going to double click on that icon.…I'm going to choose all the default options for the installer…and enter my password,…and we have completed the installation.…I will close the installation application.…Now I'm just going to navigate to a terminal window…and type in the word Java space dash version…to verify that I have Java installed correctly, and I do.…
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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