PIVOT IN TABLEAU PREP SOFTWARE

(And then, of course, there’s the initial way I came up with in response to a question here, that is a bit more tedious. But until then, there is a way to accomplish it that is fairly painless. Tableau Prep (Maestro) was just released and is an amazing tool, even in version 1! I truly hope to see an unpivot feature soon that allows everything to be done with a few mouse clicks and drag-and-drop. Aggregations and calculations will also be quite a bit easier with the second table. In the second table, I can assign a different format to each field. For example, if you only have the Value field, then what format do you give it? In some cases above, it’s a percent while in others it’s a whole number. But if you truly have different measures, then having an individual field or column for each one will make your life a lot easier. Now, in many cases, having the taller, narrower data is actually better – if it’s all the same measure. Then, I want to take the list of metrics and have a column for each, like this:

PIVOT IN TABLEAU PREP SOFTWARE

What do I mean by “unpivot”? The term is actually used in different ways in different software packages, but here I mean taking rows of data and translating or transposing them to columns. Tableau fans are welcome too.Given the right tools, Scotty could solve just about anything! Unpivot Data – Rows to Columns I shared more thoughts about Tableau vs Power BI in my blogs Power BI vs.

While testing the tool, I couldn’t help but ask myself “Why pay hundreds of dollars per user/per year for Tableau Creator when Power BI Desktop is better and free?” But you have pretty icons…without much behind. While it does help visualizing the flow I’m not sure how much value it really adds given that the steps are sequential, and the tool doesn’t support conditional constraints and branches. I’ve noticed people excited about the Tableau Prep graphical interface. Tableau’s mentality remains “one dataset at the time”. And to me the biggest limitation of the tool, which stems from the limitation in the Tableau modeling capabilities, is that everything falls apart when you need multiple tables in your data model. Then, to reflect the changes in the data source, such as when you get a new file with the same spec, you just refresh to re-import and transform the data. In Power BI Desktop and Excel, you can conveniently load the transformed data directly into the data model. In my opinion, Power Query is by far more user friendly than Tableau Prep.Īfter enough wrangling to do what’s simple in Power Query but complicated in Tableau Prep, I wanted to save the results. I also couldn’t find a feature to quickly promote column headers. So much about “a drag-and-drop visual experience” and “no scripting required”. I had to use a column filter (requires an expression) to filter out the top three rows. There wasn’t such a feature in Tableau Prep. In Power Query, you can quickly filter out top or bottom rows. These rows needs to be removed and the labels in the forth row needs to be promoted as column headers.

The geo table has a small (but common) issue because it has some extra rows that appear before the main dataset. The goal was to cleanse the geo table in the bi_dimensions Excel file that Microsoft provides as sample data for Dashboard in a Day (DIAD) workshops. I took Tableau Prep for a quick ride to do simple data prep. It’s clear that Tableau Prep is far behind the Power Query capabilities and has a lot of catching up to do. One output from Tableau Prep file (Tableau model can’t handle multiple tables) One table in the model per query (typically) Save as TDE, Hyper, CSV, preview in Desktop Script (all transformations in one place)ĭirectly into PBI data model, Excel sheet (Power Query in Excel only) Keep rows, remove rows, remove duplicates, promote headers, group by, merge, append, pivot, transpose, combine filesĬopy, remove, duplicate, column from example, calculated column, remove, remove duplicates, remove errors, change type, rename, transform (lower, upper, trim, etc.), replace values, replace errors, split column, index column, group by, fill, pivot, move, format, extract, number column (statistics, standard, scientific, math), date and time column, R scriptįilter (formula required), group and replace, clean (upper, lower, trim, remove characters), split, rename, remove, calculated fieldĭetect and expand relationships in data source Stand-alone (with preview in Tableau Desktop)

Pivot in tableau prep