Manage Expectations
An Expectation is a verifiable assertion about your data. They make implicit assumptions about your data explicit, and they provide a flexible, declarative language for describing expected behavior. They can help you better understand your data and help you improve data quality. An Expectation Suite contains multiple Expectations.
Prerequisites
- You have a Data Asset.
Available Expectations
The following table lists the available GX Cloud Expectations.
Data Quality Issue | Expectation | Description | Dynamic Parameters? |
---|---|---|---|
Cardinality | expect_column_values_to_be_unique | Expect each column value to be unique. | No |
Cardinality | expect_compound_columns_to_be_unique | Expect the compound columns to be unique. | No |
Cardinality | expect_select_column_values_to_be_unique_within_record | Expect the values for each record to be unique across the columns listed. Note that records can be duplicated. | No |
Cardinality | expect_column_proportion_of_unique_values_to_be_between | Expect the proportion of unique values to be between a minimum value and a maximum value. | Yes |
Cardinality | expect_column_unique_value_count_to_be_between | Expect the number of unique values to be between a minimum value and a maximum value. | Yes |
Data Integrity | expect_column_pair_values_to_be_equal | Expect the values in column A to be the same as column B. | No |
Data Integrity | expect_multicolumn_sum_to_equal | Expect that the sum of row values in a specified column list is the same for each row, and equal to a specified sum total. | No |
Distribution | expect_column_pair_values_A_to_be_greater_than_B | Expect the values in column A to be greater than column B. | No |
Distribution | expect_column_values_to_be_between | Expect the column entries to be between a minimum value and a maximum value. | No |
Distribution | expect_column_z_scores_to_be_less_than | Expect the Z-scores of a column's values to be less than a given threshold. | No |
Distribution | expect_column_stdev_to_be_between | Expect the column standard deviation to be between a minimum value and a maximum value. | Yes |
Distribution | expect_column_sum_to_be_between | Expect the column sum to be between a minimum value and a maximum value. | Yes |
Missingness | expect_column_values_to_be_null | Expect the column values to be null. | Coming soon |
Missingness | expect_column_values_to_not_be_null | Expect the column values to not be null. | Coming soon |
Numerical Data | expect_column_max_to_be_between | Expect the column maximum to be between a minimum and a maximum value. | Yes |
Numerical Data | expect_column_mean_to_be_between | Expect the column mean to be between a minimum and a maximum value. | Yes |
Numerical Data | expect_column_median_to_be_between | Expect the column median to be between a minimum and a maximum value. | Yes |
Numerical Data | expect_column_min_to_be_between | Expect the column minimum to be between a minimum value and a maximum value. | Yes |
Pattern matching | expect_column_value_length_to_equal | Expect the column entries to be strings with length equal to the provided value. | No |
Pattern matching | expect_column_value_length_to_be_between | Expect the column entries to be strings with length between a minimum value and a maximum value. | No |
Pattern matching | expect_column_values_to_match_like_pattern | Expect the column entries to be strings that match a given like pattern expression. | No |
Pattern matching | expect_column_values_to_match_like_pattern_list | Expect the column entries to be strings that match any of a provided list of like pattern expressions. | No |
Pattern matching | expect_column_values_to_match_regex | Expect the column entries to be strings that match a given regular expression. | No |
Pattern matching | expect_column_values_to_match_regex_list | Expect the column entries to be strings that can be matched to either any of or all of a list of regular expressions. | No |
Pattern matching | expect_column_values_to_not_match_like_pattern | Expect the column entries to be strings that do NOT match a given like pattern expression. | No |
Pattern matching | expect_column_values_to_not_match_like_pattern_list | Expect the column entries to be strings that do NOT match any of a provided list of like pattern expressions. | No |
Pattern matching | expect_column_values_to_not_match_regex | Expect the column entries to be strings that do NOT match a given regular expression. | No |
Pattern matching | expect_column_values_to_not_match_regex_list | Expect the column entries to be strings that do not match any of a list of regular expressions. Matches can be anywhere in the string. | No |
Schema | expect_column_to_exist | Checks for the existence of a specified column within a table. | No |
Schema | expect_column_values_to_be_in_type_list | Expect a column to contain values from a specified type list. | No |
Schema | expect_column_values_to_be_of_type | Expect a column to contain values of a specified data type. | No |
Schema | expect_table_column_count_to_be_between | Expect the number of columns in a table to be between two values. | Yes |
Schema | expect_table_column_count_to_equal | Expect the number of columns in a table to equal a value. | No |
Schema | expect_table_columns_to_match_ordered_list | Expect the columns in a table to exactly match a specified list. | No |
Schema | expect_table_columns_to_match_set | Expect the columns in a table to match an unordered set. | No |
Sets | expect_column_values_to_be_in_set | Expect each column value to be in a given set. | No |
Sets | expect_column_values_to_not_be_in_set | Expect column entries to not be in the set. | No |
Sets | expect_column_distinct_values_to_be_in_set | Expect the set of distinct column values to be contained by a given set. | No |
Sets | expect_column_distinct_values_to_contain_set | Expect the set of distinct column values to contain a given set. | No |
Sets | expect_column_distinct_values_to_equal_set | Expect the set of distinct column values to equal a given set. | No |
Sets | expect_column_most_common_value_to_be_in_set | Expect the most common value to be within the designated value set. | No |
Volume | expect_table_row_count_to_be_between | Expect the number of rows to be between two values. | Yes |
Volume | expect_table_row_count_to_equal | Expect the number of rows to equal a value. | No |
Volume | expect_table_row_count_to_equal_other_table | Expect the number of rows to equal the number in another table within the same database. | No |
Custom SQL Expectations
GX Cloud also offers the ability to write a custom Expectation using SQL. It is designed to fail validation if the provided SQL query returns one or more rows.
The provided query should be written in the dialect of the Data Source in which a given Data Asset lives.
{batch}
named queryThe optional {batch}
named query references the Batch of data under test. When the Expectation is evaluated, the {batch}
named query will be replaced with the Batch of data that is validated.
Dynamic Parameters
Dynamic Parameters allow you to create Expectations whose parameters update based on new data. GX Cloud can populate new Expectation parameters at runtime using the last n
validation results. For example, you can define an Expectation to validate that the maximum value within a column does not exceed 20% above a previously recorded value.
You will be able to input:
-
Sensitivity:
X%
of the average of previous values -
Constraint:
Above
,below
, orabove and below
for the sensitivity threshold -
Run count:
n
previous validation results
When you select your n
run count, and:
-
There are
0
previous runs, the Expectation will always succeed. -
There are
<n
runs, the Expectation will take all previous runs into account. -
There are
n
runs, the Expectation will take the lastn
runs into account. -
There are
>n
runs, the Expectation will take the lastn
runs into account.
Add an Expectation
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In GX Cloud, click Data Assets.
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In the Data Assets list, click the Data Asset name.
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Click the Expectations tab.
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Click New Expectation.
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Select an Expectation type. See Available Expectations.
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If you are adding your first expectation on this data asset, you may be able to select a time-based Batch interval for that asset.
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A batch is a feature of the data asset, and allows you to validate your data incrementally. A batch interval can only be defined once per data asset; you cannot change it after setting it.
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In order to be able to select a batch interval, the data asset must have at least one DATE or DATETIME column.
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Select the Entire table tab to provide all Data Asset records to your Expectations and validations, or select the Yearly/Monthly/Daily tab to use subsets of Data Asset records for your Expectations and validations.
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Select Yearly to partition Data Asset records by year, select Monthly to partition Data Asset records by year and month, or select Daily to partition Data Asset records by year, month, and day.
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Batch column - Select a name column from a prefilled list of DATE and DATETIME columns containing the date and time data.
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Complete the mandatory and optional fields for the Expectation. A recurring validation schedule will be applied automatically to your Expectation, based on the settings of your Expectation Suite.
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Click Save or click Save & Add More and then repeat steps 5 and 7 to add additional Expectations.
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Optional. Run a Validation. See Run a Validation.
Edit an Expectation
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In GX Cloud, click Data Assets.
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In the Data Assets list, click the Data Asset name.
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Click the Expectations tab.
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Click Edit Expectation for the Expectation that you want to edit.
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Edit the Expectation configuration.
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Click Save.
View Expectation history
View the Expectation history to determine when an Expectation was changed and who made the change.
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In GX Cloud, click Expectation Suites.
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In the Expectation Suites list, click the Expectation Suite name.
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Click the Change Log tab.
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Optional. Select an Expectation in the Columns pane to view the change history for a specific Expectation.
The date, time, and email address of the users who created, edited, or deleted the Expectation appears below the Expectation name. Strikethrough text indicates an Expectation was deleted.
Delete an Expectation
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In GX Cloud, click Data Assets.
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In the Data Assets list, click the Data Asset name.
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Click the Expectations tab.
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Click Delete Expectation for the Expectation you want to delete.
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Click Yes, delete Expectation.