Combine monthly CSVs without counting twice.

Append means stacking records from compatible tables. Join means attaching columns through a matching key. Monthly transactions are often appended; transactions and a customer lookup are usually joined. Confusing the two can either multiply records or create a sparse table with repeated month-specific columns.

State the grain in one sentence: one row is one transaction, one order line, or one account-month. An order ID may legitimately repeat in an order-line export. Check both the grain and schema before using an ID as a duplicate-removal key.

List the filename, export date, covered period, row count, currency, time zone, and source total for each file. Keep the untouched downloads in a separate folder. Include a source_file field in the combined table so an unusual result can be traced to the originating export.

Watch for full-history exports masquerading as monthly files. A file downloaded in February may contain all transactions since January. Filenames are clues, not evidence of the date range. Inspect the actual dates and record the source system's filter settings.

Excel's From Folder workflow can combine a selected collection of files. Filter the folder listing first so temporary workbooks, previous combined outputs, and unrelated CSVs are excluded. Use a representative sample file, then check that the remaining files follow the same structural contract.

Map by column name and set types explicitly. A reordered column is different from a renamed or missing column. Do not make an unexpected schema change disappear by skipping errors. Retain an exception list that identifies which file failed and why, then fix the source or document the deliberate mapping.

Consider synthetic exports with 100 rows totaling $10,000 and 120 rows totaling $12,000. An append produces 220 rows and $22,000. Investigation finds ten identical transactions totaling $1,000 in both files because the reporting windows overlap. Removing one verified copy of each gives 210 rows and $21,000.

The arithmetic is only valid after confirming that the ten rows are repeated exports of the same events. Ten purchases by the same customer are not duplicates merely because the amounts match. Use an authoritative transaction key, or a documented composite key that distinguishes legitimate repeated events.

A later file may contain a corrected version of an earlier transaction. Keeping the first record blindly preserves stale data; summing both versions can double-count activity. Decide whether the source emits replacement snapshots, adjustment events, or an append-only ledger.

For replacement snapshots, retain version metadata and use an authoritative update timestamp under a clear rule. For adjustment events, preserve both original and adjustment with their signs. A negative amount is not automatically a mistake. The duplicate-checking method helps separate repeated records from valid repeated business activity.

Reconcile accepted rows plus excluded rows to the source manifest. Check the combined amount against the sum of source totals minus documented overlap adjustments. Group by source_file as well as reporting month; a sudden change isolated to one file often points to an extraction problem.

• Mark missing months instead of drawing a continuous line through absent data.
• Separate incomplete current periods from complete historical periods.
• Keep currencies separate until a documented conversion is applied.
• Show unmapped categories and rejected rows beside the result.

Data Analysis App can inspect a prepared export and help turn it into findings and report outputs. This workflow does not require a live connection to your source system, and uploading separate files should not be taken as a promise of automatic reconciliation.

Prepare the combined table with its provenance fields, then start a project. Ask a focused question such as which complete months changed most, and review the coverage and exclusions before paying for downloadable outputs. A polished trend is useful only when the underlying periods are comparable.