DATA IMPORT REVIEW · Workflow idea
Take a selected CSV file, check its columns, and prepare the rows for an existing database table. Surface missing or malformed values and show the expected changes to a data owner before anything is imported.
01 / The starting point
A data owner selects a CSV file prepared for a specific database table
“Read and validate the selected rows, map their fields to the intended table, and wait for approval before adding or changing database records.”
02 / The work
Helps teams move structured data from a CSV file into an existing database while keeping the import scope reviewable.
Confirm the selected CSV, its source, and which records are meant to be included.
Compare the file’s columns with the destination table and flag missing, unexpected, or ambiguous fields.
Look for empty required values, inconsistent dates, unexpected formats, and duplicate rows without guessing corrections.
Show the destination, field mapping, number of rows, and representative records for the data owner to inspect.
Require an authorized reviewer to confirm the exact data set and an appropriate recovery option before writing records.
Report what was imported and keep incomplete or rejected records available for correction and follow-up.
03 / The result
A checked import preview with row counts, field mapping, and exceptions ready for an authorized reviewer.
Reviews & approvals · Example outcome
A checked import preview with row counts, field mapping, and exceptions ready for an authorized reviewer.
A mistaken import can overwrite, duplicate, or expose records. Verify the destination, field mapping, row count, and sensitive values; use a backup or approved recovery plan and require a data owner to approve the exact import before it runs.
04 / Make it yours
A few choices shape the work around your team.
Select where import files are prepared and limit access to the people responsible for handling the data.
Confirm the existing table, required columns, value formats, and rules for new or matching records.
Name the data owner who approves imports and confirm how a mistaken or partial import can be recovered.
Use a small sample with missing, duplicate, and incorrectly formatted values and verify that no write occurs before approval.
Keep exploring
Prepare rows from a CSV for an analytics warehouse and require a data owner to check the mapping and record scope before anything is added.