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Data checklist: Vendor analysis

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Summary

Learn which fields are required to leverage the existing configuration and control points for vendor analytics.

Data checklist

Columns Currently used in analysis Missing values allowed Description
Vendor ID Yes No

Each vendor's unique identifier.

This label is used in various graphs, so if the code itself is not informational, you can concatenate this with a description.
Cost center code Yes No

The relevant cost center code, such as:

  • Cost center
  • Business unit

This label is used in various graphs, so if the code itself is not informational you may want to concatenate this with a description.
Cost center description No Yes Optional description of the cost center (used for filtering).
Amount Yes No

The monetary value associated with the entry or invoice. Each entry will be analyzed, and can be rolled to the invoice level — reach out to your CSM for details.

Note: All amounts in an analysis use the same currency.
Account ID Yes No

General ledger account number.

This label is used in various graphs, so if the code itself is not informational, you can concatenate this with a description.
Account description No  Yes Optional description of the GL account (used for filtering).
Date Yes No The date on which the amount was posted.
Fund description No Yes Can be used for filtering.
Fund code No Yes Can be used for filtering.
Note: Blanks are not allowed in the base configuration. If a row is missing a required field, that row of data will be excluded from the analysis.

General data expectations

Data must be/contain...

  • In .xlsx, .csv, or another supported format (.pdfs are not supported)
  • Entry based
  • Densely populated (limited blank cells)
  • At least 200,000 entries (rows)
    • Larger data sets are preferred (1+ million rows preferred)
    • MindBridge can analyze smaller datasets (20,000 rows), but some algorithms will not be as effective. Leveraging multiple years of data could add to the data volume.
  • In a consistent format across columns 
  • A healthy variety of values, including:
    • Numerous values for any categorical columns to allow richer categorization and pivoting of visuals
    • Limited synthetic, fake or columnar data

Assumptions

  • There are no missing values for the required fields: Vendor Name, Amount, Date, etc.
  • Each row represents one unique monetary flow (i.e., the details about one unique invoice or payment)

Anything else on your mind? Chat with us or submit a request for further assistance.

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