Database Access in R | dplyR, NoSQL, MongoDB, Cassandra & More

Working with Databases in R: RDBMS with RODBC; Using dplyr; R with NoSQL, MongoDB, Cassandra & More

TTDS6687

Intermediate

2 Days

Course Overview

Mining data in R requires access to multiple data stores. In this course, we'll cover dataframe manipulation, accessing common file formats, traditional Relational Databases, and NOSQL stores like MongoDB and Cassandra.  After completing the course, students will be able to work with data from a myriad of data sources they're likely to encounter in data science, manipulating, transforming, and joining disparate data sets to be able to extract profound insights.

Course Objectives

Working in a hands-on learning, environment students will explore:

  • Data Frames and Data Files in R
  • Relational Databases
  • RDBMS with RODBC
  • Using dplyr
  • Working with NOSQL Databases
  • R and MongoDB
  • R and Cassandra and DataFrames from Cassandra

Course Prerequisites

This is an intermediate level course, geared for data scientists. Incoming students should have prior experience working with R.

 

Take Before: Students should have attended the course(s) below, or should have practical hands-on skills in these areas:

TTDS6681             R Essentials for Data Scientists

Course Agenda

 

Please note that this list of topics is based on our standard course offering, evolved from typical industry uses and trends. We’ll work with you to tune this course and level of coverage to target the skills you need most. Topics, agenda and labs are subject to change, and may adjust during live delivery based on audience needs and skill-level.

 

 

Data Frames and Data Files in R

  • Reading and Writing Tab and CSV files
  • Excel Spreadsheets
  • MS Access Files
  • Working with DataFrames
  • DataFrame tools
  • Merging and Joining DataFrames

 

Relational Databases Overview

  • Database CLIs with R (DBI, R/ODBC, R/JDBC)
  • SQLite
  • dplyr

 

RDBMS with RODBC

  • ODBC drivers and the CLI
  • SELECT statements
  • INSERT statements
  • DELETE statements
  • UPDATE statements
  • DDL statements
  • DB Transactions

 

Using dplyr

  • dplyr Features
  • Table verbs
  • Operations
  • Piping

 

NOSQL Databases

  • RDBMS (SQL-based)
  • Document Databases
  • Key-Value Databases
  • Columnar Databases

 

R and MongoDB

  • MongoDB Overview
  • MongoDB and R
  • Mongo Queries

 

R and Cassandra

  • Cassandra Overview
  • Accessing Cassandra
  • DataFrames from Cassandra

Course Materials

Each student will receive a Student Guide with course notes, code samples, software tutorials, diagrams and related reference materials and links (as applicable). Our courses also include step by step hands-on lab instructions and and solutions, clearly illustrated for users to complete hands-on work in class, and to revisit to review or refresh skills at any time. Students will also receive the project files (or code, if applicable) and solutions required for the hands-on work.

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