#Tableau prep automate refresh software#

Other new features including a new вЂњdata highlighterвЂќ thatвЂ™s designed to make it easy to view insights while keeping other data in view for context, and a new вЂњcustom territoriesвЂќ feature that simplifies advanced geographic analysis. ThereвЂ™s also a new cross-database filtering function that lets a single filter be applied to more than one data source, and a new wildcard union that will simplify the process of joining multiple Excel workbooks, including cloud-based sources like Google Sheets.

Version 10 simplifies this process with a new cross-database join function that can be saved and reused as an extract. Tableau users often pull data from different databases, such as Oracle (NYSE: ORCL), SQL Server, and Postgres. In addition to numerical fields, the function can support categorical fields. The function allows the user to continually add more variables until the data is sorted in a meaningful way. A user can call the clustering function by simply dragging it from the Tableau menu onto the screen, where it will automatically sort the data and differentiate their values by color.Д«y playing with the clustering function, a user can explore patterns in the data that would be tough to pick out with the naked eye. TableausвЂ™ new drag and drop clustering function, for example, automatically finds patterns in data using a k-means function.

#Tableau prep automate refresh software#

The Seattle, Washington company is looking to change that perception by focusing on making it easier for customers to use the upcoming version 10 release of its popular analytics and visualization software for desktops and servers. But that power comes at a cost, including a steep learning curve for some of the more advanced Tableau features. Tableau (NYSE: DATA) is renowned for putting powerful analytic and visualization capabilities into the hands of its users. The upcoming release of Tableau 10 will introduce new features aimed at simplifying how customers use advanced analytic functions upon their data, such as a new k-means clustering algorithm that works in drag-and-drop fashion.