Analytics Functions

Analytics functions allow you to explore data using models such as trendline and cluster.

Function	Example	Description
Trendline	TRENDLINE(revenue, (calendar_year, calendar_quarter, calendar_month) BY (product), 'LINEAR', 'VALUE')	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	CLUSTER((product, company), (billed_quantity, revenue), 'clusterName', 'algorithm=k-means;numClusters=%1;maxIter=%2;useRandomSeed=FALSE;enablePartitioning=TRUE', 5, 10)	Collects a set of records into groups based on one or more input expressions using K-Means or Hierarchical Clustering.
Outlier	OUTLIER((product, company), (billed_quantity, revenue), 'isOutlier', 'algorithm=mvoutlier')	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	REGR(revenue, (discount_amount), (product_type, brand), 'fitted', '')	Fits a linear model and returns the fitted values or model. This function can be used to fit a linear curve on two measures.
Evaluate_Script	EVALUATE_SCRIPT('filerepo://obiee.Outliers.xml', 'isOutlier', 'algorithm=mvoutlier;id=%1;arg1=%2;arg2=%3;useRandomSeed=False;', customer_number, expected_revenue, customer_age)	Executes an R script as specified in the script_file_path, passing in one or more columns or literal expressions as input. The output of the function is determined by the output_column_name.