From e6a57a5dc96ae5be8520f3b580fabd5dd4483d1e Mon Sep 17 00:00:00 2001 From: Kristen Lavavej Date: Thu, 19 Dec 2024 08:43:43 -0800 Subject: [PATCH 1/4] initial changes --- .../expectation_images/dynamic_parameters.png | Bin 136294 -> 0 bytes .../cloud/expectations/manage_expectations.md | 106 +++++++++--------- .../data_quality_use_cases/distribution.md | 2 +- .../learn/data_quality_use_cases/integrity.md | 2 +- .../data_quality_use_cases/uniqueness.md | 2 +- 5 files changed, 56 insertions(+), 56 deletions(-) delete mode 100644 docs/docusaurus/docs/cloud/expectations/expectation_images/dynamic_parameters.png diff --git a/docs/docusaurus/docs/cloud/expectations/expectation_images/dynamic_parameters.png b/docs/docusaurus/docs/cloud/expectations/expectation_images/dynamic_parameters.png deleted file mode 100644 index 9fa923abba06d5315ba65365ed18ad963f7996a9..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 136294 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RwN4oLp_*Bl7E@fp{{s{d)C2$k diff --git a/docs/docusaurus/docs/cloud/expectations/manage_expectations.md b/docs/docusaurus/docs/cloud/expectations/manage_expectations.md index 26eb5557147c..cd5058ecab0f 100644 --- a/docs/docusaurus/docs/cloud/expectations/manage_expectations.md +++ b/docs/docusaurus/docs/cloud/expectations/manage_expectations.md @@ -16,52 +16,53 @@ An Expectation is a verifiable assertion about your data. They make implicit ass 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 | +| Data quality issue | Expectation | Description | Dynamic Parameters? | +|:------------------:|:----------------------------------------------------:|:--------------------------------------------------------------------------------------------------------------------------------------:|:-------------------:| +| Completeness | **column values to be null** | Expect the column values to be null. | Coming soon | +| Completeness | **column values to not be null** | Expect the column values to not be null. | Coming soon | +| Numeric | **column max to be between** | Expect the column maximum to be between a minimum and a maximum value. | Yes | +| Numeric | **column mean to be between** | Expect the column mean to be between a minimum and a maximum value. | Yes | +| Numeric | **column median to be between** | Expect the column median to be between a minimum and a maximum value. | Yes | +| Numeric | **column min to be between** | Expect the column minimum to be between a minimum value and a maximum value. | Yes | +| Numeric | **column pair values A to be greater than B** | Expect the values in column A to be greater than column B. | No | +| Numeric | **column stdev to be between** | Expect the column standard deviation to be between a minimum value and a maximum value. | Yes | +| Numeric | **column sum to be between** | Expect the column sum to be between a minimum value and a maximum value. | Yes | +| Numeric | **column values to be between** | Expect the column entries to be between a minimum value and a maximum value. | No | +| Numeric | **column z scores to be less than** | Expect the Z-scores of a column's values to be less than a given threshold. | No | +| Numeric | **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 | +| Numeric, Validity | **column most common value to be in set** | Expect the most common value to be within the designated value set. | No | +| Numeric, Validity | **column pair values to be equal** | Expect the values in column A to be the same as column B. | No | +| Numeric, Validity | **column values to be in set** | Expect each column value to be in a given set. | No | +| Numeric, Validity | **column values to not be in set** | Expect column entries to not be in the set. | No | +| Schema | **column to exist** | Checks for the existence of a specified column within a table. | No | +| Schema | **column values to be in type list** | Expect a column to contain values from a specified type list. | No | +| Schema | **column values to be of type** | Expect a column to contain values of a specified data type. | No | +| Schema | **table column count to be between** | Expect the number of columns in a table to be between two values. | Yes | +| Schema | **table column count to equal** | Expect the number of columns in a table to equal a value. | No | +| Schema | **table columns to match ordered list** | Expect the columns in a table to exactly match a specified list. | No | +| Schema | **table columns to match set** | Expect the columns in a table to match an unordered set. | No | +| Uniqueness | **column distinct values to be in set** | Expect the set of distinct column values to be contained by a given set. | No | +| Uniqueness | **column distinct values to contain set** | Expect the set of distinct column values to contain a given set. | No | +| Uniqueness | **column distinct values to equal set** | Expect the set of distinct column values to equal a given set. | No | +| Uniqueness | **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 | +| Uniqueness | **column unique value count to be between** | Expect the number of unique values to be between a minimum value and a maximum value. | Yes | +| Uniqueness | **column values to be unique** | Expect each column value to be unique. | No | +| Uniqueness | **compound columns to be unique** | Expect the compound columns to be unique. | No | +| Uniqueness | **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 | +| Validity | **column value length to be between** | Expect the column entries to be strings with length between a minimum value and a maximum value. | No | +| Validity | **column value length to equal** | Expect the column entries to be strings with length equal to the provided value. | No | +| Validity | **column values to match like pattern** | Expect the column entries to be strings that match a given like pattern expression. | No | +| Validity | **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 | +| Validity | **column values to match regex** | Expect the column entries to be strings that match a given regular expression. | No | +| Validity | **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 | +| Validity | **column values to not match like pattern** | Expect the column entries to be strings that do NOT match a given like pattern expression. | No | +| Validity | **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 | +| Validity | **column values to not match regex** | Expect the column entries to be strings that do NOT match a given regular expression. | No | +| Validity | **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 | +| Volume | **table row count to be between** | Expect the number of rows to be between two values. | Yes | +| Volume | **table row count to equal** | Expect the number of rows to equal a value. | No | +| Volume | **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 @@ -97,9 +98,6 @@ When you select your `n` run count, and: - There are `>n` runs, the Expectation will take the last `n` runs into account. - -![GX Cloud dynamic parameters](./expectation_images/dynamic_parameters.png) - ## Expectation condition The Expectation condition is an optional field that applies to any Expectation validating row-level data. This condition allows you to filter your data so that only a specific subset of your Batch is validated. Rows will be validated only when the condition is true. @@ -126,13 +124,15 @@ To clear the Expectation condition, click the clear button located on the right- 3. Click **New Expectation**. -4. Select an Expectation type. See [Available Expectations](#available-expectations). +4. Select a data quality issue to test for + +5. Select an Expectation type. -5. Complete the mandatory and optional fields for the Expectation. A recurring [validation schedule](/cloud/schedules/manage_schedules.md) will be applied automatically to your Expectation. +6. Complete the mandatory and optional fields for the Expectation. A recurring [validation schedule](/cloud/schedules/manage_schedules.md) will be applied automatically to your Expectation. -6. Click **Save** or click **Save & Add More** and then repeat steps 3 through 6 to add additional Expectations. +7. Click **Save** or click **Save & Add More** and then repeat steps 4 through 7 to add additional Expectations. -7. Optional. Run a Validation. See [Run a Validation](/cloud/validations/manage_validations.md#run-a-validation). +8. Optional. Run a Validation. See [Run a Validation](/cloud/validations/manage_validations.md#run-a-validation). :::tip Automate rules for schema change detection When you [create a new Data Asset](/cloud/data_assets/manage_data_assets.md#add-a-data-asset-from-an-existing-data-source), you can choose to automatically generate Expectations that detect column changes in that Data Asset. diff --git a/docs/docusaurus/docs/reference/learn/data_quality_use_cases/distribution.md b/docs/docusaurus/docs/reference/learn/data_quality_use_cases/distribution.md index 61049161a054..5196e419100e 100644 --- a/docs/docusaurus/docs/reference/learn/data_quality_use_cases/distribution.md +++ b/docs/docusaurus/docs/reference/learn/data_quality_use_cases/distribution.md @@ -202,7 +202,7 @@ expect_column_median_to_be_between: True - **Assuming static distributions**: Data distributions often evolve over time due to seasonality, trends, or changes in data collection. It is crucial to regularly update reference distributions and Expectations to reflect the current state of the data. -- **Overlooking data quality issues**: Data entry errors, missing values, or outliers can significantly distort the distribution. Comprehensive data quality checks, including handling missing data and outliers, is an essential complement to distribution analysis and validation. +- **Overlooking data quality problems**: Data entry errors, missing values, or outliers can significantly distort the distribution. Comprehensive data quality checks, including handling missing data and outliers, is an essential complement to distribution analysis and validation. - **Not accounting for multimodal distributions**: Some datasets may have multiple peaks, requiring appropriate methods and Expectations that can handle multimodal distributions. Ignoring multimodality can lead to inaccurate interpretations of the data. diff --git a/docs/docusaurus/docs/reference/learn/data_quality_use_cases/integrity.md b/docs/docusaurus/docs/reference/learn/data_quality_use_cases/integrity.md index 8375eaafd3a8..4b2be4c0a08e 100644 --- a/docs/docusaurus/docs/reference/learn/data_quality_use_cases/integrity.md +++ b/docs/docusaurus/docs/reference/learn/data_quality_use_cases/integrity.md @@ -227,7 +227,7 @@ Run the following GX Core workflow. ## Scenarios -The following scenarios provide insight into how Great Expectations can help enforce data integrity across various domains. By combining built-in Expectations with custom SQL checks, organizations can create comprehensive validation frameworks that catch inconsistencies, prevent data quality issues, and ensure compliance with business rules and regulations. +The following scenarios provide insight into how Great Expectations can help enforce data integrity across various domains. By combining built-in Expectations with custom SQL checks, organizations can create comprehensive validation frameworks that catch inconsistencies, prevent data quality problems, and ensure compliance with business rules and regulations. ### Cross-system financial reconciliation diff --git a/docs/docusaurus/docs/reference/learn/data_quality_use_cases/uniqueness.md b/docs/docusaurus/docs/reference/learn/data_quality_use_cases/uniqueness.md index 0660c32dd6e6..996bdb68e321 100644 --- a/docs/docusaurus/docs/reference/learn/data_quality_use_cases/uniqueness.md +++ b/docs/docusaurus/docs/reference/learn/data_quality_use_cases/uniqueness.md @@ -8,7 +8,7 @@ import TabItem from '@theme/TabItem'; Data uniqueness is a fundamental aspect of data quality that ensures distinct values are present only once where expected in a dataset. Uniqueness constraints are often applied to columns that serve as primary keys, composite keys, or other unique identifiers. Validating uniqueness is critical for maintaining data integrity, preventing duplication, and enabling accurate analysis. -Failing to validate uniqueness can lead to various data quality issues: +Failing to validate uniqueness can lead to various data quality problems: * Duplicates can skew analytics, leading to incorrect conclusions and flawed decision-making. For example, duplicate transactions could overstate revenue. * Non-unique identifiers can cause data corruption when merging or joining datasets, resulting in lost data or mismatched records. From de96465383a8eb94432c0822c0c52b9aa10b7375 Mon Sep 17 00:00:00 2001 From: Kristen Lavavej Date: Fri, 20 Dec 2024 11:09:22 -0800 Subject: [PATCH 2/4] self-review --- .../docusaurus/docs/cloud/expectations/manage_expectations.md | 4 ++-- .../reference/learn/data_quality_use_cases/dq_use_cases_lp.md | 2 +- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/docs/docusaurus/docs/cloud/expectations/manage_expectations.md b/docs/docusaurus/docs/cloud/expectations/manage_expectations.md index cd5058ecab0f..b261de7dbd4c 100644 --- a/docs/docusaurus/docs/cloud/expectations/manage_expectations.md +++ b/docs/docusaurus/docs/cloud/expectations/manage_expectations.md @@ -30,7 +30,7 @@ The following table lists the available GX Cloud Expectations. | Numeric | **column values to be between** | Expect the column entries to be between a minimum value and a maximum value. | No | | Numeric | **column z scores to be less than** | Expect the Z-scores of a column's values to be less than a given threshold. | No | | Numeric | **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 | -| Numeric, Validity | **column most common value to be in set** | Expect the most common value to be within the designated value set. | No | +| Numeric, Validity | **column most common value to be in set** | Expect the most common value to be within the designated value set. | No | | Numeric, Validity | **column pair values to be equal** | Expect the values in column A to be the same as column B. | No | | Numeric, Validity | **column values to be in set** | Expect each column value to be in a given set. | No | | Numeric, Validity | **column values to not be in set** | Expect column entries to not be in the set. | No | @@ -124,7 +124,7 @@ To clear the Expectation condition, click the clear button located on the right- 3. Click **New Expectation**. -4. Select a data quality issue to test for +4. Select a data quality issue to test for. 5. Select an Expectation type. diff --git a/docs/docusaurus/docs/reference/learn/data_quality_use_cases/dq_use_cases_lp.md b/docs/docusaurus/docs/reference/learn/data_quality_use_cases/dq_use_cases_lp.md index 55b3d670f73f..60c9b260f081 100644 --- a/docs/docusaurus/docs/reference/learn/data_quality_use_cases/dq_use_cases_lp.md +++ b/docs/docusaurus/docs/reference/learn/data_quality_use_cases/dq_use_cases_lp.md @@ -13,7 +13,7 @@ import LinkCard from '@site/src/components/LinkCard'; import OverviewCard from '@site/src/components/OverviewCard'; - Learn how to use GX to address key data quality issues. + Learn how to use GX to address key data quality scenarios. A comprehensive data quality strategy relies on a multidimensional approach to achieving and maintaining high-quality data. GX enables you to define and validate data quality checks across a variety of data quality and observability dimensions. From f3b6e0dcceda84ce5d86a2ba1d9d64a42ef24952 Mon Sep 17 00:00:00 2001 From: Kristen Lavavej Date: Fri, 20 Dec 2024 11:18:48 -0800 Subject: [PATCH 3/4] alignment --- docs/docusaurus/docs/cloud/expectations/manage_expectations.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/docusaurus/docs/cloud/expectations/manage_expectations.md b/docs/docusaurus/docs/cloud/expectations/manage_expectations.md index b261de7dbd4c..a58e0b3f9406 100644 --- a/docs/docusaurus/docs/cloud/expectations/manage_expectations.md +++ b/docs/docusaurus/docs/cloud/expectations/manage_expectations.md @@ -17,7 +17,7 @@ An Expectation is a verifiable assertion about your data. They make implicit ass The following table lists the available GX Cloud Expectations. | Data quality issue | Expectation | Description | Dynamic Parameters? | -|:------------------:|:----------------------------------------------------:|:--------------------------------------------------------------------------------------------------------------------------------------:|:-------------------:| +|------------------|----------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------|-------------------| | Completeness | **column values to be null** | Expect the column values to be null. | Coming soon | | Completeness | **column values to not be null** | Expect the column values to not be null. | Coming soon | | Numeric | **column max to be between** | Expect the column maximum to be between a minimum and a maximum value. | Yes | From 66c7fdebac6d48c4ffc486cd41ab3e5d05a2d4fa Mon Sep 17 00:00:00 2001 From: Kristen Lavavej Date: Fri, 20 Dec 2024 13:11:35 -0800 Subject: [PATCH 4/4] plural --- .../docusaurus/docs/cloud/expectations/manage_expectations.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/docs/docusaurus/docs/cloud/expectations/manage_expectations.md b/docs/docusaurus/docs/cloud/expectations/manage_expectations.md index a58e0b3f9406..af82e186d108 100644 --- a/docs/docusaurus/docs/cloud/expectations/manage_expectations.md +++ b/docs/docusaurus/docs/cloud/expectations/manage_expectations.md @@ -49,8 +49,8 @@ The following table lists the available GX Cloud Expectations. | Uniqueness | **column values to be unique** | Expect each column value to be unique. | No | | Uniqueness | **compound columns to be unique** | Expect the compound columns to be unique. | No | | Uniqueness | **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 | -| Validity | **column value length to be between** | Expect the column entries to be strings with length between a minimum value and a maximum value. | No | -| Validity | **column value length to equal** | Expect the column entries to be strings with length equal to the provided value. | No | +| Validity | **column value lengths to be between** | Expect the column entries to be strings with length between a minimum value and a maximum value. | No | +| Validity | **column value lengths to equal** | Expect the column entries to be strings with length equal to the provided value. | No | | Validity | **column values to match like pattern** | Expect the column entries to be strings that match a given like pattern expression. | No | | Validity | **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 | | Validity | **column values to match regex** | Expect the column entries to be strings that match a given regular expression. | No |