[ddj] SQL Vs Excel Vs Refine

[Stephen Doig]

A main reason to learn SQL is to handle relational data — datasets that come with several tables that may need to be linked. A simple example would be a large main table that uses codes for categorical variables like race, type of crime, hospital diagnosis, etc., then separate lookup tables that translate the codes into something readable. SQL also will handle large datasets beyond the one million or so records that is the current Excel limit. SQL also will do complicated queries that involve conditional statements.

With that said, Excel will handle the majority of data problems most likely to be faced by most data journalists. It's a good idea to start learning SQL so as to be ready when that big project comes up, but skills with Excel (or Fusion Tables) will take you a long way.

Steve Doig



From: Andrew Duffy <andrewjamesduffy at gmail.com<mailto:andrewjamesduffy at gmail.com>>
Reply-To: "List about Data Driven Journalism and Open Data in Journalism." <data-driven-journalism at lists.okfn.org<mailto:data-driven-journalism at lists.okfn.org>>
Date: Mon, 29 Apr 2013 14:37:51 +1000
To: <data-driven-journalism at lists.okfn.org<mailto:data-driven-journalism at lists.okfn.org>>
Subject: [ddj] SQL Vs Excel Vs Refine

Question:

Are there any data journalists/devs out there that can advise as to whether it's worth learning SQL? So far a combination of Excel/Google Refine has been more than enough for dumping, organising, and cleaning my data projects, but I have only worked with spreadsheets up to ~500 rows.

What can SQL do that refine/excel can't?

--

Andrew Duffy - Journalist


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