This page is a directory as to how to import and prepare your data in Crunch. We've broken down the phases into 5 broad phases:

The amount of work you need to do depends on the type of data you're uploading and the quality and completeness of the metadata. If you're working with a direct survey import (eg: from Decipher, Qualtrics, SurveyMonkey, Confirmit) you may not need to do some of the steps below. On the other hand, if you have an SPSS datafile, then many of the steps involved in the setup phases will apply to you. This is because SPSS files lack the metadata you get from direct imports.
Note: Crunch's optimum workflow is not to use SPSS files, but to use one of our direct importers or to build-your-own exporter (from your data collection platform).
We highly recommend you read the following to understand how datasets should be set up and the types of things researchers will ask of you if you're a DP department.
The table below is a portal to the various tasks you may need to do in setting up a dataset, by phase.
Most tasks you can do via the web app. You may find scripting (Crunch Automation or perhaps R) more effective if you have bulk actions to accomplish. Some tasks require scripting (ie: can't be done in the web app). The Script Builder is Google spreadsheet app that can help generate Crunch Automation code and allow you to manipulate schema metadata (useful for bulk tasks).
Task |
GUI (web app) |
Crunch Automation |
Script Builder |
Importing |
Creating a dataset |
✓ |
✓ |
- |
Stacking / reshaping |
- |
- |
- |
Merging datafiles |
✓ |
- |
- |
Data cleaning (exclusions, recoding, converting) |
✓ |
✓ |
- |
Setup |
Setting variable titles, descriptions, notes |
✓ |
✓ |
✓ |
Organizing variables in folders |
✓ |
✓ |
✓ |
Grouping variables into arrays (categorical arrays, multiple response, numeric arrays) |
✓ |
✓ |
✓ |
Setting/changing variable types (converting) |
✓ |
✓ |
✓ |
Setting category numeric values & dates |
✓ |
✓ |
✓ |
Cleaning/relabelling categories |
✓ |
✓ |
✓ |
Reordering categories |
✓ |
✓ |
✓ |
Hiding or removing cases (rows) |
✓ |
✓ |
- |
Hiding or removing variables (columns) |
✓ |
✓ |
- |
Make |
Rebasing variables (setting missing values) |
- |
✓ |
- |
Banding numeric variables |
✓ |
✓ |
- |
Combining responses / collapsing scales |
✓ |
✓ |
✓ |
Capping numeric variables |
- |
✓ |
- |
Transforming multiple selections (fixed column) |
- |
✓ |
- |
Making 'Top 2 Box' and other summary variables |
✓ |
✓ |
✓ |
Calculating numeric variables (eg: age from year of both, summing variables, averaging variables) |
- |
✓ |
- |
Creating interactions (similar to ‘nesting’) |
✓ |
✓ |
- |
Depiping/delooping |
- |
✓ |
- |
Subtotals ('nets') on a categorical variable or array |
✓ |
✓ |
✓ |
Subtotals ('nets') on a multiple response variable |
✓ |
✓ |
- |
Note: it can be useful at this point to do another reorganizing of variables into folders |
Prepare |
Filters |
✓ |
✓ |
- |
Weights |
✓ |
✓ |
- |
Multitable (banner) |
✓ |
✓ |
- |
Creating decks |
✓ |
Coming soon |
- |
Creating and editing dashboards |
✓ |
Coming soon |
- |
Creating tab books |
✓ |
Coming soon |
- |
Generating (and updating) PowerPoints |
✓ |
Coming soon |
- |
Share |
Sharing datasets |
✓ |
- |
- |
Sharing dashboards |
✓ |
- |
- |
Sharing specific items in datasets - decks, filters, banners |
✓ |
- |
- |
Selective sharing (Views) |
Coming soon |
- |
- |
Creating teams |
✓ |
- |
- |