Reference | Alteryx to Dataiku concept mapping#
New terminology can be a stumbling block when learning a new software tool. This table provides an overview mapping some of the key concepts in Alteryx to a similar feature in Dataiku.
Alteryx |
Dataiku |
Context |
---|---|---|
Workflow & Canvas |
Organize all components of an analytics activity — data, transformations, results, and documentation — into one project. Within a project, track how data moves through an analytical pipeline through the Flow’s visual grammar of datasets, recipes, and models. |
|
Container tool |
Manage large projects by dividing a complex Flow into multiple, smaller zones. |
|
Browse tool |
In the Explore tab of a dataset, open the Analyze window on a column for exploratory data analysis (EDA). |
|
Sample tool |
Work interactively on even very large datasets by adjusting the default sampling parameters as needed. |
|
Input data tool |
Access data through a consistent visual interface across disparate sources such as cloud storage, HDFS, SQL, NoSQL, and more. |
|
Text input tool |
Directly change the rows, columns, and values of a dataset. |
|
Comment tool |
Share knowledge among team members and onboard new users quickly with real-time collaboration in a browser as opposed to a desktop application. |
|
Select tool |
Add steps from the Prepare recipe’s processor library for the most common data wrangling operations such as selecting, renaming, and reordering columns. |
|
Formula tool |
In the Prepare recipe, write expressions in a spreadsheet-style syntax for calculations, string manipulation, and more. |
|
DateTime functions |
Parse dates, extract date components, compute time differences, and more using various processors in the Prepare recipe. |
|
Join and Append tools |
Visually run in-database a variety of dataset joins (left, right, inner, outer, anti, cross) without writing SQL. |
|
Spatial tools |
Create geopoints from lat-lon coordinates, along with many other geographic operations, in the Prepare recipe. Use the Geo join recipe for spatial joins. |
|
Union tool |
Equivalent to an SQL UNION ALL, combine multiple datasets in a number of ways with this visual recipe. |
|
Score tool |
Generate predictions by applying a machine learning model to unseen data. |
|
Filter tool |
Divide a dataset into multiple outputs based on a range of conditions, including mapping column values or defining filters. |
|
Results window |
Before running a Prepare recipe, preview a sample of results alongside the script. Before running other visual recipes, check the Output tab to see the new schema. |
|
Interactive chart tool |
Drag and drop data onto a variety of chart types to visualize trends and relationships in your data. |
|
Render tool |
Share results with business users by publishing insights, such as charts and key metrics, onto dashboards. |
|
Assisted Modeling |
Quickly create and iterate on predictive models using AutoML or expert mode. |
|
Data investigation tools |
For deeper dives beyond the Analyze window, see the Statistics tab of a dataset for computing a wide range of common statistical analyses. |
|
Schedule Workflows |
Automate the execution of a Flow — including building datasets and training models — according to triggers, such as a period of time (daily) or when a dataset changes. |
|
Analytic Apps |
Package projects behind customizable visual interfaces so consumers can independently reuse them for downstream tasks. |