![]() ![]() If the data source is something like one of the OLAP/cube sources that can’t be extracted and can’t do a cross data source joins then you’re out of luck and can’t use this technique Union via Cross Join Technique Overview If it doesn’t support cross data source joins (I’m looking at you, OData) there’s a workaround using a Tableau data extract where you connect to the raw source, extract if necessary (OData sources automatically create extracts), then use the technique on the extract. If your source is not one of those then to use the union via cross join technique that I’m going to demonstrate here the source must support cross data source joins. If all your data is located in a single Excel file, a single Google Sheets workbook, a single folder of text files, a single SQL Server, MySQL, Oracle, Postgres, Redshift, or HP Vertica database, then you can use Tableau’s existing union functionality in v10.2 (or earlier in the case of Excel workbooks, text documents, and Google Sheets workbooks) and skip this post. (Did you know you could do cross data source joins to extracts? That capability came with v10.0, and we can have all sorts of fun with that using join calculations!) ![]() This post goes through examples of all three using a combination of text files and superstore, and Rody Zakovich will be doing a post sometime soon on unions and joins with Tableau data extracts. Union customer & store/facility data sets so you can draw both on the same map.Union actual sales data from transactional systems and budget data that might come from an Excel spreadsheet.Union data that is coming from different systems, for example when different subsidiaries of an organization are using different databases but you want a single view of the company.Here are some use cases for unions across data sources: With the join calculations we can now do unions and cross/cartesian joins within or across almost any data source without needing Custom SQL or linked databases and without waiting for Tableau to implement more union support, read on to learn how! ![]() Pivot in version 9.0, the first batch of union support in v9.3, support for ad hoc groups in calculations, cross data source joins and filters in v10.0, and more in-database unions and join calculations in v10.2. Since Tableau v9.0 or so every new release has come with new features that simplify and reduce the amount of data prep I have to do outside of Tableau. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |