Using Steps

You build data flows using steps to curate your data. Steps are functions that change your data in a specific way. For example, steps can aggregate values, perform time series analysis, or perform machine learning algorithms.

Step Use this step to: More Information
Add Columns Add a new output data column to your data flow using a wide range of functions, conditional expressions, and SQL operators. Add Columns in a Data Flow
Add Data Add a data source to your data flow. Add Data in a Data Flow
Aggregate Apply aggregate functions to group data in a data flow. Add Aggregates to a Data Flow
Analyze Sentiment Detect sentiment for a text column by applying a sentiment analysis to the data flow. Add a Sentiment Analysis to a Data Flow
Apply Model Apply a machine learning model to your data (also known as scoring a data model). Apply a Predictive Model to a Data Set
Bin Assign your data values into categories, such as high, low, or medium. Create a Bin Column in a Data Flow
Branch Creates multiple outputs from a data flow using a branch. Create Multiple Pipelines in a Data Flow Using a Branch
Create Essbase Cube Create an Essbase cube from a data set. Create and Customize an Essbase Cube in a Data Flow
Cumulative Value Group data by applying cumulative aggregate functions in a data flow. Add Cumulative Values to a Data Flow
Filters Use filters to limit the data in a data flow output. Filter Your Data in a Data Flow
Group Create a group column of attribute values in a data set. Create a Group in a Data Flow
Join Join multiple tables or data sets. Add a Join in a Data Flow
Merge Columns Combine two or more columns in your data flow.

Merge Columns in a Data Flow

Merge Rows Combine two or more rows in your data flow.

Merge Rows in a Data Flow

Rename Columns Change the name of data columns to something more meaningful. Rename Columns in a Data Flow
Save Data Before running a data flow, modify or select the database name, attribute or measure, and aggregation rules for each columns of the output data set. Save Output Data from a Data Flow
Save Model Change the default model name (untitled) and provide a description. Save Model
Select Columns Specify which data columns to include in your data flow. Select Columns to Include in a Data Flow
Split Columns Extract useful data from within data columns. Split Columns in a Data Flow
Time Series Forecast Apply a time series forecast calculation to a data set to create additional rows. Add a Time Series Forecast to a Data Flow
Train Binary-Classifier Train a machine learning model to classify your data into one of two predefined categories. Train a Binary Classifier Model in a Data Flow
Train Clustering Train a machine learning model to segregate groups with similar traits and assign them into clusters. Train a Clustering Model in a Data Flow
Train Multi-Classifier Train a machine learning model to classify your data into three or more predefined categories. Train a Multi-Classifier Model in a Data Flow
Train Numeric Prediction Train a machine learning model to predict a numeric value based on known data values. Train a Numeric Prediction Model in a Data Flow
Transform Column Modify data in a column using a wide range of functions, conditional expressions, and SQL operators. Transform Data in a Data Flow