Merge pull request #6522 from AdobeDocs/pre-migration-cleanup-2

pre-migration-cleanup-2

Author: bbringhu

help/access-control/abac/end-to-end-guide.md

@@ -231,7 +231,7 @@ Select **[!UICONTROL The following being false]** and then select **[!UICONTROL
 
 Select **[!UICONTROL Activate]** to activate the policy, and a dialog appears which prompts you to confirm activation. Select **[!UICONTROL Confirm]** and then select **[!UICONTROL Close]**.
 
-![Image showing the Policy being activated ](../images/abac-end-to-end-user-guide/abac-create-policy-activation.png) -->
+![Image showing the Policy being activated](../images/abac-end-to-end-user-guide/abac-create-policy-activation.png) -->
 
 ## Next steps
 

help/assurance/views/validation-summary.md

@@ -51,7 +51,7 @@ The validation function is expected to return an object that contains the follow
 | :--- | :--- | :--- |
 | `message` | String | The validation message to display in the summary results. |
 | `events` | Array | An array of event uuids to be reported as matched or not matched. |
-| `links` | Array | An array of `ValidationResultLink` objects to reference documentation and other resources `{( type: 'doc'|'product', url: String )}`  |
+| `links` | Array | An array of `ValidationResultLink` objects to reference documentation and other resources `{( type: 'doc'`|`'product', url: String )}`  |
 | `result` | String | This is the validation result and is expected to be one of the enumerated strings: "matched", "not matched", "unknown" |
 
 ## View the validation results

help/dashboards/insights-use-cases/consent-analysis.md

@@ -124,7 +124,7 @@ After the widget composer is populated with data from your chosen table, perform
 ![The widget composer with the add-icon and dropdown menu highlighted.](../images/standard-dashboards/attributes-dropdown.png)
 - Search [!UICONTROL Attributes] for `[!UICONTROL count_of_profiles]`, then use the + icon to add the `[!UICONTROL count_of_profiles]` attribute to the Y-axis from the dropdown menu.
 - Select the `...` (ellipses) icon in the [!UICONTROL Y-axis] field, then select the [!UICONTROL SUM] aggregate function from the dropdown menu.
-![The widget composer Consent trends widget with the data model, table, and the Y-axis dropdown menu and SUM feature highlighted. ](../images/insights-use-cases/consent-analysis/y-axis-sum-function.png)
+![The widget composer Consent trends widget with the data model, table, and the Y-axis dropdown menu and SUM feature highlighted.](../images/insights-use-cases/consent-analysis/y-axis-sum-function.png)
 - Select the [!UICONTROL Marks] dropdown menu, and change the chart type to [!UICONTROL Line]. 
 - Search [!UICONTROL Attributes] for the `[!UICONTROL segment_name]`, then use the + icon to add the `segment_name` as a [!UICONTROL Filter] from the dropdown menu. The [!UICONTROL Filter: Segment_name] dialog appears. Select the audiences created earlier that relate to consent. For this example, select **[!UICONTROL Users Consented to Calls]**, **[!UICONTROL Users Consented to SMS]**, and **[!UICONTROL Users Consented to Email]**, followed by **[!UICONTROL Apply]**.
 - Search [!UICONTROL Attributes] for `[!UICONTROL segment_name]`, then select the + icon to add `segment_name` as a [!UICONTROL Color] from the dropdown menu. 

help/data-access/tutorials/dataset-data.md

@@ -422,7 +422,7 @@ GET /files/{FILE_ID}?path={FILE_NAME}
 
 | Property | Description |
 | -------- | ----------- |
-| `{FILE_ID} `| The file's identifier. |
+| `{FILE_ID}`| The file's identifier. |
 | `{FILE_NAME}` | The file name (for example, profiles.parquet) |
 
 **Request**

help/data-prep/functions.md

@@ -148,8 +148,8 @@ The following tables list all supported mapping functions, including sample expr
 | map_has_keys | If one or more input keys are provided, then the function returns true. If a string array is provided as input, then the function returns true on the first key that is found. | <ul><li>MAP:  **Required** The input map data</li><li>KEY:  **Required** The key can be a single string or a string array. If any other primitive type (data / number) is provided, then it is treated as a string.</li></ul> | map_has_keys(MAP, KEY) | Please see the [appendix](#map_has_keys) for a code sample. | |
 | add_to_map | Accepts at least two inputs. Any number of maps can be provided as inputs. Data Prep returns a single map that has all key-value pairs from all the inputs. If one or more keys are repeated (in the same map or across maps), Data Prep de-duplicates the keys so that the first key-value pair persists in the order that they were passed in the input. | MAP: **Required** The input map data. | add_to_map(MAP 1, MAP 2, MAP 3, ...) | Please see the [appendix](#add_to_map) for a code sample. | |
 | object_to_map (Syntax 1) | Use this function to create Map data types. |<ul><li>KEY: **Required** Keys must be a string. If any other primitive values such as integers or dates are provided, then they are auto-converted to strings and are treated as strings.</li><li>ANY_TYPE: **Required** Refers to any supported XDM data type except Maps.</li></ul> | object_to_map(KEY, ANY_TYPE, KEY, ANY_TYPE, ... )| Please see the [appendix](#object_to_map) for a code sample. | | 
-| object_to_map (Syntax 2) | Use this function to create Map data types.| <ul><li>OBJECT: **Required** You can provide an incoming object or object array and point to an attribute inside the object as key.</li></ul> | object_to_map(OBJECT) | Please see the [appendix](#object_to_map) for a code sample. |
-| object_to_map (Syntax 3) | Use this function to create Map data types.| <ul><li>OBJECT: **Required** You can provide an incoming object or object array and point to an attribute inside the object as key.</li></ul> | object_to_map(OBJECT_ARRAY, ATTRIBUTE_IN_OBJECT_TO_BE_USED_AS_A_KEY) | Please see the [appendix](#object_to_map) for a code sample. |
+| object_to_map (Syntax 2) | Use this function to create Map data types.| <ul><li>OBJECT: **Required** You can provide an incoming object or object array and point to an attribute inside the object as key.</li></ul> | object_to_map(OBJECT) | Please see the [appendix](#object_to_map) for a code sample. ||
+| object_to_map (Syntax 3) | Use this function to create Map data types.| <ul><li>OBJECT: **Required** You can provide an incoming object or object array and point to an attribute inside the object as key.</li></ul> | object_to_map(OBJECT_ARRAY, ATTRIBUTE_IN_OBJECT_TO_BE_USED_AS_A_KEY) | Please see the [appendix](#object_to_map) for a code sample. ||
 
 {style="table-layout:auto"}
 
@@ -174,7 +174,7 @@ For information on the object copy feature, see the section [below](#object-copy
 | upsert_array_replace | This function is used to replace elements in an array. This function is **only** applicable during updates. If used in the context of inserts, this function returns the input as is. | <ul><li>ARRAY: **Required** The array to replace the array in the Profile.</li></li> | upsert_array_replace(ARRAY) | `upsert_array_replace([123, 456], 1)` | [123, 456] |
 | [!BADGE Destinations only]{type=Informative} array_to_string | Joins the string representations of the elements in an array using the specified separator. If the array is multidimensional, it is flattened before being joined. **Note**: This function is used in destinations. Read the [documentation](../destinations/ui/export-arrays-maps-objects.md) for more information.  | <ul><li>SEPARATOR: **Required** The separator used to join the elements in the array.</li><li>ARRAY: **Required** The array that be joined (after flattening).</li></ul> | array_to_string(SEPARATOR, ARRAY) | `array_to_string(";", ["Hello", "world"])` | "Hello;world" |
 | [!BADGE Destinations only]{type=Informative} filterArray* | Filters the given array based on a predicate. **Note**: This function is used in destinations. Read the [documentation](../destinations/ui/export-arrays-maps-objects.md) for more information. | <ul><li>ARRAY: **Required** The array to be filtered</li><li>PREDICATE: **Required** The predicate to be applied on each element of the given array. | filterArray(ARRAY, PREDICATE) | `filterArray([5, -6, 0, 7], x -> x > 0)` | [5, 7] |
-| [!BADGE Destinations only]{type=Informative} transformArray* | Transforms the given array based on a predicate. **Note**: This function is used in destinations. Read the [documentation](../destinations/ui/export-arrays-maps-objects.md) for more information. | <ul><li>ARRAY: **Required** The array to be transformed.</li><li>PREDICATE: **Required** The predicate to be applied on each element of the given array. | transformArray(ARRAY, PREDICATE) | ` transformArray([5, 6, 7], x -> x + 1)` |  [6, 7, 8] |
+| [!BADGE Destinations only]{type=Informative} transformArray* | Transforms the given array based on a predicate. **Note**: This function is used in destinations. Read the [documentation](../destinations/ui/export-arrays-maps-objects.md) for more information. | <ul><li>ARRAY: **Required** The array to be transformed.</li><li>PREDICATE: **Required** The predicate to be applied on each element of the given array. | transformArray(ARRAY, PREDICATE) | `transformArray([5, 6, 7], x -> x + 1)` |  [6, 7, 8] |
 | [!BADGE Destinations only]{type=Informative} flattenArray* | Flattens the given (multidimensional) array to a unidimensional array. **Note**: This function is used in destinations. Read the [documentation](../destinations/ui/export-arrays-maps-objects.md) for more information. | <ul><li>ARRAY: **Required** The array to be flattened.</li></ul> | flattenArray(ARRAY) | flattenArray([[['a', 'b'], ['c', 'd']], [['e'], ['f']]]) | ['a', 'b', 'c', 'd', 'e', 'f'] |
 
 {style="table-layout:auto"}
@@ -187,7 +187,7 @@ For information on the object copy feature, see the section [below](#object-copy
 
 | Function | Description | Parameters | Syntax | Expression | Sample output |
 | -------- | ----------- | ---------- | -------| ---------- | ------------- |
-| array_to_map | This function takes an object array and a key as input and returns a map of key's field with the value as key and the array element as value. | <ul><li>INPUT: **Required** The object array you want to find the first non-null object of.</li><li>KEY:  **Required** The key must be a field name in the object array and the object as value.</li></ul> |array_to_map(OBJECT[] INPUTS, KEY) | Read the [appendix](#object_to_map) for a code sample. |
+| array_to_map | This function takes an object array and a key as input and returns a map of key's field with the value as key and the array element as value. | <ul><li>INPUT: **Required** The object array you want to find the first non-null object of.</li><li>KEY:  **Required** The key must be a field name in the object array and the object as value.</li></ul> |array_to_map(OBJECT[] INPUTS, KEY) | Read the [appendix](#object_to_map) for a code sample. ||
 | object_to_map | This function takes an object as an argument and returns a map of key-value pairs. | <ul><li>INPUT: **Required** The object array you want to find the first non-null object of.</li></ul>  | object_to_map(OBJECT_INPUT) | "object_to_map(address) where input is " + "address: {line1 : \"345 park ave\",line2: \"bldg 2\",City : \"san jose\",State : \"CA\",type: \"office\"}" | Returns a map with given field name and value pairs or null if input is null. For example: `"{line1 : \"345 park ave\",line2: \"bldg 2\",City : \"san jose\",State : \"CA\",type: \"office\"}"` |
 | to_map | This function takes a list of ke-value pairs and returns a map of key-value pairs. | | to_map(OBJECT_INPUT) | "to_map(\"firstName\", \"John\", \"lastName\", \"Doe\")" | Returns a map with given field name and value pairs or null if input is null. For example: `"{\"firstName\" : \"John\", \"lastName\": \"Doe\"}"` |
 
@@ -255,7 +255,7 @@ For information on the object copy feature, see the section [below](#object-copy
 | Function | Description | Parameters | Syntax | Expression | Sample output |
 | -------- | ----------- | ---------- | -------| ---------- | ------------- |
 | uuid /<br>guid | Generates a pseudo-random ID. | | uuid()<br>guid() | uuid()<br>guid() | 7c0267d2-bb74-4e1a-9275-3bf4fccda5f4<br>c7016dc7-3163-43f7-afc7-2e1c9c206333 |
-| `fpid_to_ecid `| This function takes an FPID string and converts it into an ECID to be used in Adobe Experience Platform and Adobe Experience Cloud applications. | <ul><li>STRING: **Required** The FPID string to be converted into ECID.</li></ul> | `fpid_to_ecid(STRING)` | `fpid_to_ecid("4ed70bee-b654-420a-a3fd-b58b6b65e991")` | `"28880788470263023831040523038280731744"` |
+| `fpid_to_ecid`| This function takes an FPID string and converts it into an ECID to be used in Adobe Experience Platform and Adobe Experience Cloud applications. | <ul><li>STRING: **Required** The FPID string to be converted into ECID.</li></ul> | `fpid_to_ecid(STRING)` | `fpid_to_ecid("4ed70bee-b654-420a-a3fd-b58b6b65e991")` | `"28880788470263023831040523038280731744"` |
 
 {style="table-layout:auto"}
 

help/data-science-workspace/authoring/platform-sdk.md

@@ -155,7 +155,7 @@ The new [!DNL Experience Platform] SDK supports the following operations:
 | Less than (`<`) | `lt()` |
 | Less than or equal to (`<=`) | `le()` |
 | And (`&`) | `And()` |
-| Or (`|`) | `Or()` |
+| Or ( &vert; ) | `Or()` |
 
 ## Filter by selected columns {#filter-by-selected-columns}
 

help/data-science-workspace/jupyterlab/create-a-model.md

@@ -87,7 +87,7 @@ For the Luma propensity model notebook, the requirements do not need to be updat
 
 The configuration files, `training.conf` and `scoring.conf`, are used to specify the datasets you wish to use for training and scoring as well as adding hyperparameters. There are separate configurations for training and scoring. 
 
-In order for a model to run training, you must provide the `trainingDataSetId`, `ACP_DSW_TRAINING_XDM_SCHEMA`, and `tenantId`. Additionally for scoring, you must provide the `scoringDataSetId`, `tenantId`, and `scoringResultsDataSetId `.
+In order for a model to run training, you must provide the `trainingDataSetId`, `ACP_DSW_TRAINING_XDM_SCHEMA`, and `tenantId`. Additionally for scoring, you must provide the `scoringDataSetId`, `tenantId`, and `scoringResultsDataSetId`.
 
 To find the dataset and schema IDs, go to the data tab ![Data tab](../images/jupyterlab/create-recipe/dataset-tab.png) within notebooks on the left navigation bar (under the folder icon). Three different dataset ID's need to be provided. The `scoringResultsDataSetId` is used to store the model scoring results and should be an empty dataset. These datasets were made previously in the [Required assets](#assets) step.
 

help/dataflows/ui/monitor-streaming-profile.md

@@ -85,7 +85,7 @@ Use the metrics table for information specific to your dataflows. Refer to the f
 | Request throughput | This metric represents the number of events entering the ingestion system per second. |Sandbox/Dataflow | Real-time monitoring with a data refresh every 60 seconds. |
 | Processing throughput | This metric represents the number of events that are successfully ingested by the system each second. |Sandbox/Dataflow | Real-time monitoring with a data refresh every 60 seconds. |
 | P95 ingestion latency | This metric measures the 95th percentile latency from the moment an event arrives in Experience Platform to when it is successfully ingested into the Profile store. | Sandbox/Dataflow | Real-time monitoring with a data refresh every 60 seconds. |
-| Max throughput | This metric represents the maximum number of inbound requests per second entering streaming profile ingestion | <ul><li>Sandbox/Dataflow</li><li>Dataflow run</li></ul> |
+| Max throughput | This metric represents the maximum number of inbound requests per second entering streaming profile ingestion | <ul><li>Sandbox/Dataflow</li><li>Dataflow run</li></ul> ||
 | Records ingested | This metric represents the total number of records ingested to the Profile store within a configured time window. | <ul><li>Sandbox/Dataflow</li><li>Dataflow run</li></ul> | <ul><li>Sandbox/Dataflow: Real-time monitoring with a data refresh every 60 seconds.</li><li>Dataflow run: Grouped in 15 minutes.</li></ul>  |
 | Records failed | This metric represents the total number of records that failed ingestion into the Profile store, within a configured time window, due to errors. | <ul><li>Sandbox/Dataflow</li><li>Dataflow run</li></ul> |<ul><li>Sandbox/Dataflow: Real-time monitoring with a data refresh every 60 seconds.</li><li>Dataflow run: Grouped in 15 minutes.</li></ul>  |
 | Records skipped | This metric represents the total number of records that were dropped within a configured time window, due to configuration or capacity breaches. | <ul><li>Sandbox/Dataflow</li><li>Dataflow run</li></ul> | <ul><li>Sandbox/Dataflow: Real-time monitoring with a data refresh every 60 seconds.</li><li>Dataflow run: Grouped in 15 minutes.</li></ul>  |

help/datastreams/configure.md

@@ -95,7 +95,7 @@ To reveal advanced configration options, select **[!UICONTROL Advanced Options]*
 | [!UICONTROL Third Party ID Sync Container ID] | The numeric ID of the container to be used for third party ID sync. |
 | [!UICONTROL Container ID Overrides] | In this section, you can define additional third party ID sync container IDs which you can use to override the default one. |
 | [!UICONTROL Access Type] | Defines the authentication type that the Edge Network accepts for the datastream. <ul><li>**[!UICONTROL Mixed Authentication]**: When this option is selected, the Edge Network accepts both authenticated and unauthenticated requests. Select this option when you plan to use the Web SDK or [Mobile SDK](https://developer.adobe.com/client-sdks/home/), along with the [Edge Network API](https://developer.adobe.com/data-collection-apis/docs/api/). </li><li>**[!UICONTROL Authenticated Only]**: When this option is selected, the Edge Network only accepts authenticated requests. Select this option when you plan to use only the Edge Network API and want to prevent any unauthenticated requests from being processed by the Edge Network.</li></ul> |
-[!UICONTROL Media Analytics] | Enables processing of streaming tracking data for Edge Network integration via Experience Platform SDKs or [Media Edge API](https://developer.adobe.com/cja-apis/docs/endpoints/media-edge/getting-started/). Learn about Media Analytics from the [documentation](https://experienceleague.adobe.com/docs/media-analytics/using/media-overview.html).  |
+| [!UICONTROL Media Analytics] | Enables processing of streaming tracking data for Edge Network integration via Experience Platform SDKs or [Media Edge API](https://developer.adobe.com/cja-apis/docs/endpoints/media-edge/getting-started/). Learn about Media Analytics from the [documentation](https://experienceleague.adobe.com/docs/media-analytics/using/media-overview.html).  |
 
 From here, if you are configuring your datastream for Experience Platform, follow the tutorial on [Data Prep for Data Collection](./data-prep.md) to map your data to an Experience Platform event schema before returning to this guide. Otherwise, select **[!UICONTROL Save]** and continue to the next section.