Žiga Vaupot's Blog

In my previous post , I have described how "out-of-the-box" analytical functions in Oracle Data Visualisation Desktop or Oracle Data Visualisation Cloud Service could be used very easily and efficiently. In this blog, we will explore how to create new measures using standard analytical functions that are available in Formula Builder. Like "out-of-the-box", you can use the following analytical functions: Trendline : Fits a linear or exponential model and returns the fitted values or model. The numeric expr represents the Y value for the trend and the series (time columns) represent the X value. Cluster : Collects a set of records into groups based on one or more input expressions using K-Means or Hierarchical Clustering. Outlier : This function classifies a record as Outlier based on one or more input expressions using K-Means or Hierarchical Clustering or Multi-Variate Outlier detection Algorithms. Regr : Fits a linear model and returns the fitted val

It's been quite a while since my last post as I've been engaged in some interesting project around the world. Now I'm back and I hope I will catch up with my posts on this blog. In the last couple of month Oracle has significantly improved it's data visualisation flagship products Data Visualisation Desktop and Data Visualisation Cloud Service. One of the topics I particularly like with the new versions of these two products - by the way they have more or less same functionality, therefore I will not specifically focus on any of the two - is it's advanced analytics functionality. There are "out-of-the-box" functionalities that are ready to be used when visualising data. For example, when you are analysing your time series data, only by clicking on a button, you can add a trend line to your graph, and with another click you can add forecast as well. In this post I'm focusing on available Advanced Analytics function that are "out-of-the-box