![]() ![]() Discover how Tableau Prep helps you access your data and turn it into valuable information. Self-service data preparation reduces the time it takes to complete data projects and improves the quality of your analyses. Carl Allchin, from The Information Lab in London, gets you up to speed on Tableau Prep through a series of practical lessons that include methods for preparing, cleaning, automating, organizing, and outputting your datasets.īased on Allchin’s popular blog, Preppin’ Data, this practical guide takes you step-by-step through Tableau Prep’s fundamentals. It remains to be seen if a fuzzy join between tables was possible.For self-service data preparation, Tableau Prep is relatively easy to use-as long as you know how to clean and organize your datasets. I have highlighted in yellow the ones I was talking about above. The advantage of Tableau Prep Builder is that the ETL process is graphical and problems are evident (see below, Tableau Prep automatically puts them in red). But I needed a more elegant solution.Īs I intended to visualise my data in Tableau, the first solution I tried was to use Tableau Prep Builder. In short, as you will have understood, I could have spent a few hours cleaning my database and having the entries “checked” so that the join could work. “Central African Republic” and “Central African Rep.”īefore I was hounded by the “search and replace” fanatics in Excel, I was looking for a solution that would be more economical in terms of transformations.“Antigua and Barbuda” in one file, “Antigua & Brabuba” in the other.“Cabo Verde” in the national language of the country, “Cap Verde” in English.The problem is that a country name is far from being a constant. I found this database on the website of the World Trade Organisation. I preferred to look for a database of the different countries and the “official” region to which they are attached. I could have made groups of countries directly in Tableau, but when you have 200 entries, it is tedious (and not necessarily error-free). ![]() It, therefore, seemed appropriate to me to visualise these flows at a higher level of granularity: the region of origin. So, on one side, you have about 200 countries of origin, and on the other side about 30 countries of destination. This technology improves productivity by. The database details the number of migrants according to their country of origin and their country of destination. Tableau Prep is a data preparation software that enables the user to efficiently combine, shape and clean data.
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