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Data Validation: Overview

Article author
Tasha Kociszewski
  • Updated

Summary

The Data Validation step provides you with high-level information to help you decide whether or not you should proceed with the import process.

Learn about the various data validation checks, and how to resolve issues.

If the data appears in a grouped format, MindBridge will not be able to analyze it. Select Format data to automatically format the data into an ungrouped format, then proceed with the import process. 

Note: If the file contains multiple sheets, MindBridge will only analyze data on the first sheet in the file. Move all the data you want analyzed onto the first sheet of your file, then re-import the file.

File details

These high-level file details can help you be sure that the imported data meets your expectations at a glance.

  • Type: Displays the type of file you have imported, such as a general ledger, or accounts payable.
  • Name: Displays the name of the file you have imported.
  • # of rows: Displays the number of rows detected in the data.
  • # of numeric columns: Displays the number of columns that contain only numeric data.
  • # of date columns: Displays the number of columns that contain dates.
  • # of text columns: Displays the number of columns that contain text, which may include a combination of letters, numbers, and symbols.

Integrity checks

These checks include detailed information on every column within the data. They may indicate issues with the file, but will not prevent you from continuing the import process.

What MindBridge looks for

Why?

The presence of numeric columns.

The data must contain at least 1 column with numeric values, otherwise MindBridge will not have enough data to perform an analysis.

Learn about numeric columns.

Whether the file contains multiple sheets.

MindBridge will only analyze data from the first sheet in the file. Consolidate the relevant data into the first sheet, then re-import the data.

If you need assistance with getting the relevant data onto the first sheet of the file, learn about submitting a data formatting request.

An inconsistent number of columns across the rows.

If 700 rows have 6 columns, and 1 row has 5 columns, it could indicate missing or erroneous information in the data.

Learn about column inconsistency.

The presence of abnormally large cells.

This could indicate erroneous data, merged cells, or 

Learn about abnormally large cells.

Whether any columns contain over 50% blank cells.

This could indicate that there is data missing from the file.

The presence of NULL values in the data.

MindBridge is unable to analyze cells that contain the word "NULL" instead of a value.

Remove the word “NULL” from the data, or replace it with the appropriate data.

Whether values are expressed in scientific notations.

MindBridge will automatically convert scientific notations to numeric values. Because scientific notations often appear as a number below 10 with 2 decimal points and a power of 10, the calculation may be less precise than the actual data.

For example, the scientific notation of 4,354,765,455 is 4.35E9. MindBridge would calculate this as 4.35 x 10^9 = 4,350,000, which is much less than the original value.

The presence of special characters.

MindBridge cannot analyze some special characters, including extended character sets (such as copyright symbols), non-printable and control characters (such as formatting marks), and characters outside of the modern English alphabet.

Inconsistent or unsupported date formats.

Dates appearing in the same column must be formatted consistently and correctly.

Learn about supported date formats.

 


Column preview

These statistics can help verify your expectations at a glance, and may assist you in finding anomalous data right away.

Column name

Description and value

Name

The column header as it appears in the original file.

Refer to this when viewing the statistics in each row.

Data type

Indicates the type of data detected in each column of the original file. These may be:

  • Dates (such as 01/19/2020)
  • Numeric (numbers only)
  • Text (a combination of letters, numbers, and special characters)

Some columns are expected to have certain data types. For example, if MindBridge detects text in the "Entered date" column, it may be indicative of erroneous data.

Lowest value

The lowest numeric value found in a cell within each column.

If the value falls outside of the expected range, it may be indicative of anomalous data.

Highest value

The highest numeric value found in a cell within each column.

If the value falls outside of the expected range, it may be indicative of anomalous data.

# of unique values

An estimate of the number of unique values in each column.

Some columns are expected to have certain values. For example, if MindBridge detects that the "Entered date" has 365 unique values, but the "Effective date" column has 400, it may be indicative of additional out of period data.

Sum

The total amount, resulting from the summation of all numeric values in each column.

Refer to this to check whether debits and credits balance.

Lowest # of characters

The lowest number of characters found in a cell within each column.

Refer to this column to verify your expectations. For example, if MindBridge detects a cell with only 2 characters in the "Debit" column, it may be indicative of erroneous or missing data.

Highest # of characters

The highest number of characters found in a cell within each column.

Refer to this column to verify your expectations. For example, if MindBridge detects a cell with 10,000 characters in the "Debit" column, it may be indicative of erroneous data, or improper escaping.

# of blank cells

The number of blank cells that appear in each column.

If you notice that a required column such as Debit contains blank cells, it may be indicative of missing data.

 


Example

General_ledger_analysis_-_Data_Validation.png


Anything else on your mind?
Log in to MindBridge to chat with us, submit a request, or reach out to your assigned Customer Success Manager.


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