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Importing data

Covers the two ways to bring existing data into an RLV Scribe table instead of typing it in row by row: uploading an Excel file, or importing from another Qlik table object (which also sets a baseline you can reset back to later).

Excel bulk import

Section titled “Excel bulk import”
  1. Select Import and upload an .xlsx file.
  2. Map Columns - RLV Scribe infers each column’s type from a sample of the data and shows a preview of the first 5 rows. Review and adjust the mapping if anything looks wrong.
  3. Choose how to import:
    • Merge - adds new rows and updates matching ones, leaving the rest of the table alone.
    • Replace all - clears the existing table first. A warning and a confirmation checkbox are required before this proceeds.

Preparing your .xlsx file

Section titled “Preparing your .xlsx file”

A little care with the file before you upload avoids most import problems:

  • .xlsx only. Older .xls and .csv files are rejected. Save as .xlsx.
  • One sheet, headers on row 1. Only the first sheet is read, and its first row must be the column headers - no title rows, logos, or blank rows above them. The file needs at least one row of data below the headers.
  • Key (dimension) columns must match exactly. Every dimension that identifies a row must appear as a column whose header is an exact, case-sensitive match of the dimension name in Qlik (trailing spaces count too). If a key column is missing, the import stops with an error.
  • Every row needs its key values filled in. Rows with a blank cell in any key column are skipped. Avoid merged cells - a merged cell leaves the other rows empty, so they drop out.
  • Key values must match Qlik exactly to update existing rows. In Merge mode a row is matched to an existing one by its key values, so "North " (with a space) or 1,000 formatted as text won’t match "North" or 1000 in the app - they’ll be added as new rows instead of updating. Duplicate keys within the file overwrite each other.
  • At least one non-key column. Any column that isn’t a dimension becomes an input column. Two headers that differ only by spaces, case, or punctuation (for example Q1 Sales and Q1-Sales) collapse to the same column - give them distinct names.
  • Type inference only samples the first 5 rows. If those rows aren’t representative (blank, or a number column that has text further down), the guessed type can be wrong - always check and fix it in the Map Columns step.

How each column type should be stored

Section titled “How each column type should be stored”

Keep each value in a real, correctly-typed Excel cell rather than as text - that’s what lets RLV Scribe read it reliably. See Custom columns for what each type is.

Column type Store it in Excel as
Number / Slider / Rating A real numeric cell. No thousands separators, currency symbols, or % typed as text. A cell formatted as a percentage arrives as its decimal value (50% → 0.5). Empty cells import as 0.
Date A real Excel date cell (any date display format), or text in exactly YYYY-MM-DD. See below.
Time Text in 24-hour HH:mm (e.g. 14:30). A numeric Excel time cell will not import - it comes in empty.
Checkbox / Switch TRUE/FALSE or 1/0. (0, false, and blank become off; anything else becomes on.)
Text / Textbox / Dropdown / Tags Plain text.

Worked example

Section titled “Worked example”

A regional planner receives a colleague’s forecast as an Excel file with Product, Region, and Quantity columns. They open Import, upload the file, confirm Quantity was correctly inferred as a number, and choose Merge - the file’s rows are added without wiping out the other regions’ rows already in the table.

Importing from a Qlik table (and resetting to baseline)

Section titled “Importing from a Qlik table (and resetting to baseline)”
  1. Select the source Qlik table object and a row limit.
  2. Map the key dimensions that identify each row.
  3. Map the remaining columns.
  4. Import - progress is shown as data comes in; large tables are pulled in batches to respect Qlik’s 10,000-cell fetch limit per request.

The mapping you choose is saved, so afterward a one-click Reset to Baseline restores the table to that imported snapshot, discarding anything entered since - this is what powers versioning’s From baseline option and scenario simulation.

Worked example

Section titled “Worked example”

Before opening a headcount-planning sheet to the wider team, an HR analyst imports the current approved headcount from a published Qlik table as the baseline, mapping Department as the key dimension. Weeks later, after several planners have made speculative edits across the table, the analyst selects Reset to Baseline once to discard every speculative change and start the next planning round from the same approved figures again.

What can go wrong

Section titled “What can go wrong”