Data Aggregation and Quality
Full instructions and common questions
Data Aggregation and Quality
Summarize record counts and amounts by channel, team or another field, build pivot tables, and check blanks, duplicates and nonnumeric values. Confirm the calculation scope, export Excel, CSV or JSON, or split CSV files by a field.
How to use
- Import CSV, TSV, JSON or XLSX and check the working sheet, row count and grouping fields. If cleaning is needed, review and adopt its result first.
- Choose grouping and sum fields; leave the numeric field empty for counts only. Alternatively configure pivot rows, columns, and sum, count, average, minimum or maximum.
- Run summary or quality checks and review counts and values. Blank or nonnumeric amounts stop summation rather than silently becoming zero.
- Download Excel, CSV or JSON. Splitting uses current working data; adopt a generated result first if you want that result split into files.
Try an example
Load the sample, clean and confirm its three deduplicated rows, then sum by channel: community has two rows totaling 400 and email has one totaling 200. Summarizing the original four rows instead includes a duplicate.
Limits and privacy
Up to 50 files, 50 MB total, 100,000 rows, 300 fields and 2 million cells. Pivots allow up to 500 column groups and 20,000 row groups; splitting allows 500 groups. Record counts are not distinct-customer counts. Do not sum different currencies as one amount.
Common questions
Why can an amount stop the summary?
Blank and nonnumeric values need review; treating them as zero could conceal missing data. Correct or clean the source before retrying.
What becomes the next input after a quality check?
The check generates an issue list. Only explicit adoption makes it working data; review the source and row count before continuing.