qcoder VS worldcup

Because we're on a statistics subreddit, I have to mention there are a handful of packages for doing qualitative work in R - RQDA, Q-Coder, some others - but I would not recommend it if you're not already familiar with R, or at least some programming language. There are graphical interfaces that will serve you well.

qcoder is also out there. It's still under active maintenance, but it's not on CRAN. It has a handy user interface, but you can obviously insert the qual tags yourself.

Hi guys, I have a school project for building a Data warehouse using an open-source dataset. I currently dive into one dataset which is The Fjelstul World Cup Database (Github: https://github.com/jfjelstul/worldcup). This dataset has multiple tables which combine a variety of properties. It's hard to figure out the whole following process to build a Dataware house from scratch. I just get some ideas and make out a sample of this. Can you guys help me examine that? What are the best ways to build Fact and Dimension tables from this generous dataset? What properties and table I should put in that case?

Source: Fjelstul World Cup Database

let Source = Web.BrowserContents("https://github.com/jfjelstul/worldcup/tree/master/data-csv"), #"Extracted Table From Html" = Html.Table( Source, {{"FileName", ".js-navigation-open.Link\-\-primary"}}, [RowSelector = ".Box-row + *"] ), fxCSVs = (FileName as text) as table => let Source = Csv.Document( Web.Contents( "https://raw.githubusercontent.com/jfjelstul/worldcup/master/data-csv/" & FileName ), [Delimiter = ",", Encoding = 65001, QuoteStyle = QuoteStyle.None] ), #"Promoted Headers" = Table.PromoteHeaders(Source, [PromoteAllScalars = true]) in #"Promoted Headers", #"Invoked Custom Function" = Table.AddColumn( #"Extracted Table From Html", "CSV_Data", each fxCSVs([FileName]) ) in #"Invoked Custom Function"

= Csv.Document(Web.Contents("https://github.com/jfjelstul/worldcup/blob/master/data-csv/award_winners.csv"),[Delimiter=",", Encoding=65001, QuoteStyle=QuoteStyle.None])