TABLEAU PREP AGGREGATE HOW TO
TABLEAU PREP AGGREGATE FULL

What dimensions do you need to keep, what time granularity (or otherwise) do you roll up to, etc.

TABLEAU PREP AGGREGATE HOW TO

Determining what to keep when aggregatingĭeciding how to aggregate is something you’ll have to put some thought into. And given that your data is big enough, using a Cube as a source for overview dashboards might well be part of your solution. But the truth is you don’t need to pre-calculate everything, the way that OLAP does you just need to aggregate enough to lessen the load on your database. If this true, why not just pre-calculate everything ahead of time? And isn’t that what OLAP cubes were doing back in the day? I’m sure you’ve heard someone from Tableau tell you cubes are the past and are unnecessary. It’s a win for both the database and Tableau. When the results come back more quickly from the data base, Tableau can start rendering the beautiful vizes more quickly. Keep in mind that retrieval and working from long-term storage is the physically slowest thing in all of computing.

If you were to aggregate up to the weekly level (or perhaps even just the DAILY LEVEL), you would be reducing the amount of work that has to be performed each time by the database of simply reading through extraneous lines. Unless you are worried about the transactions for the current day, it is unlikely that the data from the previous days will be changing appreciably from one query to the next. Now, Tableau does a good job of caching, but if people are using filters, or you have any sort of personalization / row level security built in, Tableau will be forced to issue fresh queries for each user. But think about what you are doing - you are asking the database to go back and re-add all of those individual transactions EVERY SINGLE TIME you show this dashboard. You certainly can connect directly to the transactional tables, and Tableau will ask the database to do all the right aggregations.

TABLEAU PREP AGGREGATE FULL

You are starting with transactional data that records each purchase at the item level with a recording of the full date and time to the second level. Here’s a quick thought experiment: You need to build an overview dashboard with several filters, that goes down to the weekly level of granularity at best. Why pre-aggregation is good for your database and good for Tableau Tableau’s abilities to filter between two data sources (actions & cross-datasource filters in Tableau 10) make this an excellent strategy, and one that I have seen massively improve performance over and over. When dealing with massive amounts of data, a better solution is to have two data sources: (1) A pre-aggregated data set for overviews, which I’ll call the Overview data source (2) The row-level data set, which I’ll call the Granular data source. But “can” is not “should” - what is possible may not be the BEST way, particularly if you want to scale up. You CAN get started with analysis on top of just about any data in Tableau.

Then you’ll publish and share with your whole organization.” It’s a great line, because it’s true. Have you heard this one before? “Just connect to your data in Tableau and start visualizing.

Tableau prep aggregate