Introduction

Much of the data you work with will be spreadsheet-like data: This lecture teaches you about professional data cleaning and exploration tools like OpenRefine, Tableau Prep, Microsoft Access, Tableau Desktop, and Redcap.
To varying degrees, all of these tools offer support for relational database structures, like relational joins. This lesson explains the principles of relational databases and why they are important.

Table Formats

Most (all?) data table tools happily accept csv (comma separated values) or tsv (tab separated values) files. You may choose to view and manipulate csv or tsv files in Excel or Tableau or R or OpenRefine or Access or Python or Matlab or Redcap (and probably many other tools).
Excel had its own proprietary *.xlsx or *.xls format and that may also be supported by some tools, but the simple text formats, like csv and tsv, are maximally portable.

Goals To make you aware of professional data cleaning and exploration tools

Learning Objectives This lesson contributes to the objective to "expand your options for manipulating table data" by "exploring tools for manipulating table data" and "explaining relational database concepts".

Table of Contents

Data Cleaning
● Open Refine
● Tableau Prep

Databases (Redcap, MS Access)
● One-to-Many Problem
● Relational Tables
● Queries

● Tableau Desktop

Data Tables 1 (10 pts)