A: Hi there!

Both do a fine work, but there are significant differences at the detail and level of customization.

Automated Data Cleaning is included in your deal:

This feature is designed for self-serve users who want to quickly and efficiently prepare their data without extensive manual effort. It covers a broad set of common cleaning tasks such as:

- Putting semi-structure data into shape, e.g. merged headers, random comments, spaces etc.
- Semantic and topical analysis of comments
- Parsing of dates, currencies and units
- Removing duplicates and handling missing values
- Converting columns into proper formats such as Booleans to faciliate more powerful charts
- Basic corrections, typos etc.
- Renaming of long column names
- Grouping from multi-select questions in a questionnaire etc.
- Creatiion of new columns, such as geographic regions, numerical groups

Business subscription offer tailored onboarding and dashboards. With regards to data cleaning this means:

- Evaluation of your data lake
- Custom rule-based cleaning tailored to your business or industry needs
- Handling very large, multi-source, or “dirty” data lakes
- Specialty transformations and mapping
- AI-assisted error detection and correction
- Dedicated consultancy: our data experts work with you to design, implement, and sometimes even fully manage the data cleaning process for your projects
- Ongoing support for complex pipelines This is much more hands-on and personalized—your team can rely on both advanced technology and our data experts for best-in-class data preparation.

In Summary:

Self-serve/Gold Tier/AppSumo: Automated, fast, and easy—great for straightforward cleaning needs suitable for a wide array of data.

Business/Enterprise Tiers: Includes everything above plus custom and advanced data cleaning for organizations with more complex requirements.

Typically the business tier has been the mother of invention in new features for the consumer tier, that is, many of the features that have been developed come from business needs that were deemed suitable for seralisation at some point. Over time we have and continue to improve this feature with passion for data.

Hope this helps and let me know if you need more details. Thanks!