String Value Matching

The String Value Matching in data quality involves comparing and validating text data to ensure accuracy and consistency across datasets. You use methods like exact matching, contains, and pattern recognition to detect discrepancies or variations. This process helps you maintain reliable and standardized data for analysis and reporting.

Rule configuration

A value is marked as a success when it matches the expected distinct set and complies with the match type. If the value is unique and fits within the defined set, the rule is considered passed.

Match type This configuration defines how the values in the dataset should be compared. It sets the criteria or condition under which a match is considered valid, such as exact matching, partial matching, or pattern-based matching.

• Exact Match
• Starts and Ends with
• Contains

Pattern string A pattern string is a sequence of characters that defines a specific format or structure. It is often used for searching, matching, or validating text based on predefined rules or patterns.

Success criteria

• The success condition depends on how the Match Type is configured.
• For example, “Alice” should be distinct. This means no two names in the database can have the same “Alice” value.

Configuration fields

• Operator options

  Greater than

  Less than

  Equal to

  Between (requires specifying a start and end range)

• Operator defines the comparison operation. You can select Greater Than, Less Than, Equal To, or Between.

• Value is the threshold value used for success criteria. It is required for the Greater than, Less than, and Equal to operators.

• Value range is required only when the Between operator is selected. You must specify the start and end range.

• Threshold type indicates whether the Value or Value Range should be considered as a percentage or an absolute count.

• Allow null values determines if null values are permitted.

• Check for match determines if data values align with predefined standards, formats, or reference values to ensure accuracy, consistency, and integrity.

Sample Input

ID	Customer	Country
1	Fallon	Great Britain
2	Franklyn Fryer	France
3	Kathleen	United States
4	Judie Green	France
5	John Doe

Sample rule configuration

• Match type Starts and Ends With
• Starts and Ends string Customer = Fallon,John Doe Country =Britain,United States,France
• Case sensitive True

Sample success criteria configuration

• Operator Greater than
• Value 50%
• Threshold type Absolute Count
• Allow null values True
• Check for match False

Sample Output

Column Name	Rule Name	Success Count	Failure Count	Within Threshold	Null Count
Customer	Distinct Value Set check	2	3	No	0
Country	Distinct Value Set check	4	1	Yes	1