Fix some broken links (#1524)

* fix some broken links

* a couple more

pages/changelogs/2023-11-07-lookup-tables-warehouse-connectors.mdx

@@ -6,6 +6,6 @@ createdAt: "2023-11-07T14:59:02.165Z"
 updatedAt: "2023-11-07T14:59:02.165Z"
 date: "2023-11-07"
 ---
-Today, all customers can use Warehouse Connectors to import Lookup Tables from their warehouse. For a list of supported warehouses, check out this [list](https://docs.mixpanel.com/docs/tracking-methods/data-warehouse/overview). This capability allows you to periodically enrich Mixpanel with data from your source-of-truth. 
+Today, all customers can use Warehouse Connectors to import Lookup Tables from their warehouse. For a list of supported warehouses, check out this [list](/docs/tracking-methods/data-warehouse). This capability allows you to periodically enrich Mixpanel with data from your source-of-truth. 
 
-For more information, check out our [docs](https://docs.mixpanel.com/docs/tracking-methods/data-warehouse/sending-lookup-table).
+For more information, check out our [docs](/docs/tracking-methods/data-warehouse#lookup-tables).

pages/docs/access-security/single-sign-on.mdx

@@ -21,7 +21,7 @@ Claiming a domain will add security to an SSO implementation by allowing only me
 To claim a domain, add a TXT record to your domain's DNS records with a verification key provided by Mixpanel. The verification key is available after you submit to claim a domain in your Organization Settings.
 
 <Callout type="info">
-  A single domain can be claimed by only one single Mixpanel organization. If you have multiple Mixpanel organizations with separate billing accounts but need to share SSO settings and email domains for login, please see the [documentation for the Shared SSO beta](docs/access-security/single-sign-on/shared-sso) to see how you can share those settings with an "Admin" Organization.
+  A single domain can be claimed by only one single Mixpanel organization. If you have multiple Mixpanel organizations with separate billing accounts but need to share SSO settings and email domains for login, please see the [documentation for the Shared SSO beta](/docs/access-security/single-sign-on/shared-sso) to see how you can share those settings with an "Admin" Organization.
 </Callout>
 
 ### Generate Verification Key by Claiming Domain

pages/docs/access-security/single-sign-on/azure.md

@@ -3,7 +3,7 @@
 
 ## Overview
 
-You can set up Microsoft Azure Single Sign-On to use with your Mixpanel account. Before using this document, read the [general Mixpanel SSO set-up instructions]((https://docs.microsoft.com/en-us/azure/active-directory/saas-apps/mixpanel-provisioning-tutorial)) as well as [Azure's documentation on setting up a new application](https://docs.microsoft.com/en-us/azure/active-directory/saas-apps/mixpanel-provisioning-tutorial). 
+You can set up Microsoft Azure Single Sign-On to use with your Mixpanel account. Before using this document, read the [general Mixpanel SSO set-up instructions](/docs/access-security/single-sign-on) as well as [Azure's documentation on setting up a new application](https://docs.microsoft.com/en-us/azure/active-directory/saas-apps/mixpanel-provisioning-tutorial). 
 
 ### Add Mixpanel as a New Application
 

pages/docs/cohort-sync/integrations.mdx

@@ -6,7 +6,7 @@ import { Callout, Cards } from 'nextra/components'
 This page highlights integrations that sends Mixpanel Cohorts to external destinations. Learn more about [integrations that imports data from other destinations into Mixpanel](/docs/tracking-methods/integrations) and [integrations that exports data from Mixpanel to data warehouses](/docs/data-pipelines/integrations/).
 </Callout>
 
-These integrations allow you to send your [Cohorts](docs/users/cohorts) to other destinations for audience targeting. You may review our complete integrations directory [here](https://mixpanel.com/partners/integrations). If you don't see what you're looking for [reach out to us](https://mixpanel.com/get-support).
+These integrations allow you to send your [Cohorts](/docs/users/cohorts) to other destinations for audience targeting. You may review our complete integrations directory [here](https://mixpanel.com/partners/integrations). If you don't see what you're looking for [reach out to us](https://mixpanel.com/get-support).
 
 ## Featured Integrations
 <Cards>
@@ -28,7 +28,7 @@ These integrations allow you to send your [Cohorts](docs/users/cohorts) to other
   <Cards.Card icon title="MoEngage" href="/docs/cohort-sync/integrations/moengage" />
   <Cards.Card icon title="OneSignal" href="/docs/cohort-sync/integrations/onesignal" />
   <Cards.Card icon title="Salesforce Marketing Cloud" href="/docs/cohort-sync/integrations/salesforce-marketing-cloud" />
-  <Cards.Card icon title="Segment" href="/docs/cohort-sync/integrations/Segment" />
+  <Cards.Card icon title="Segment" href="/docs/cohort-sync/integrations/segment" />
   <Cards.Card icon title="Taplytics" href="/docs/cohort-sync/integrations/taplytics" />
   <Cards.Card icon title="VWO" href="/docs/cohort-sync/integrations/vwo" />
   <Cards.Card icon title="WebEngage" href="/docs/cohort-sync/integrations/webengage" />

pages/docs/data-pipelines/old-pipelines/integrations.mdx

@@ -6,7 +6,7 @@ import { Callout, Cards } from "nextra/components";
   This page highlights integrations that send Mixpanel data to data warehouses.
   Learn more about [integrations that import data from other destinations into
   Mixpanel](/docs/tracking-methods/integrations) and [integrations that export
-  cohorts for audience targeting](docs/cohort-sync/integrations).
+  cohorts for audience targeting](/docs/cohort-sync/integrations).
 </Callout>
 
 These integrations allow you to send your [raw data](/docs/data-pipelines#raw) and [schematized data](/docs/data-pipelines#schematized) to your cloud storage bucket or data warehouse. You may review our complete integrations directory [here](https://mixpanel.com/partners/integrations). If you don't see what you're looking for [reach out to us](https://mixpanel.com/get-support).

pages/docs/data-pipelines/old-pipelines/integrations/schematized-aws-pipeline.md

@@ -1,11 +1,11 @@
 # Schematized AWS Pipeline
 
-Mixpanel's [Schematized Export Pipeline](/docs/data-pipelines/schematized-export-pipeline) lets you export your Mixpanel data directly into an S3 bucket, allowing the use of Glue to query it. To set up the Mixpanel AWS pipeline, you must configure AWS to receive the exported data, then [create a pipeline](https://developer.mixpanel.com/reference/create-warehouse-pipeline) to export the data.
+Mixpanel's [Schematized Export Pipeline](/docs/data-pipelines/old-pipelines/schematized-export-pipeline) lets you export your Mixpanel data directly into an S3 bucket, allowing the use of Glue to query it. To set up the Mixpanel AWS pipeline, you must configure AWS to receive the exported data, then [create a pipeline](https://developer.mixpanel.com/reference/create-warehouse-pipeline) to export the data.
 
 ## Design
 ![image](/230698348-abb2656e-fe2a-4d9c-ad61-8f80793e9c07.png)
 
-Mixpanel applies [transformation rules](/docs/data-pipelines/schematized-export-pipeline#transformation-rules) to make the data compatible with data warehouses and then transfers the transformed data to your S3 bucket. You can then choose to use a Glue crawler to create the schema out of the transformed data or let Mixpanel to directly create the schema in your glue database. Having the data and the glue schema in place, you can use SQL with multiple AWS products, including [Amazon Athena](https://aws.amazon.com/athena/) and [Redshift Spectrum](https://docs.aws.amazon.com/redshift/latest/dg/c-getting-started-using-spectrum.html), to query the imported data. 
+Mixpanel applies [transformation rules](/docs/data-pipelines/old-pipelines/schematized-export-pipeline#transformation-rules) to make the data compatible with data warehouses and then transfers the transformed data to your S3 bucket. You can then choose to use a Glue crawler to create the schema out of the transformed data or let Mixpanel to directly create the schema in your glue database. Having the data and the glue schema in place, you can use SQL with multiple AWS products, including [Amazon Athena](https://aws.amazon.com/athena/) and [Redshift Spectrum](https://docs.aws.amazon.com/redshift/latest/dg/c-getting-started-using-spectrum.html), to query the imported data. 
 
 We recommend the use of [Spectrum](https://docs.aws.amazon.com/redshift/latest/dg/c-getting-started-using-spectrum.html) and [Glue](https://aws.amazon.com/glue/) to query the imported data. 
 
@@ -164,7 +164,7 @@ Note: If you use Athena with Glue and want to enable partitioning, you must choo
 
 ##### Configuring Glue for Mixpanel Direct Export 
 
-Mixpanel can write and update a schema in your Glue instance as soon as new data is available. To get more information about the table schemas, please see [Schema](/docs/data-pipelines/schematized-export-pipeline#schema). To set this up:
+Mixpanel can write and update a schema in your Glue instance as soon as new data is available. To get more information about the table schemas, please see [Schema](/docs/data-pipelines/old-pipelines/schematized-export-pipeline#schema). To set this up:
 
 1. Create a Glue database. 
   * In the AWS console, go to "Glue". (Make sure you are in the same region as your S3 exported data).
@@ -265,7 +265,7 @@ This convenience, however, can also pose issues, such as:
 * The time column is interpreted as an integer. As a result, it is more difficult to perform timestamp operations. 
 * When using the one table per event schema option, Glue crawlers can merge data from multiple events in one table based on similarity.
 
-To avoid these issues, Mixpanel can write and update a schema in your Glue instance as soon as new data is available. Follow [these instructions](/docs/data-pipelines/integrations/amazon-s3#section-configuring-glue-for-mixpanel-direct-export) to enable Mixpanel to write your data catalog to AWS Glue.
+To avoid these issues, Mixpanel can write and update a schema in your Glue instance as soon as new data is available. Follow [these instructions](/docs/data-pipelines/old-pipelines/integrations/schematized-aws-pipeline#configuring-glue-for-mixpanel-direct-export) to enable Mixpanel to write your data catalog to AWS Glue.
 
 To use crawlers, you must point the crawler to the top level folder with your Mixpanel project ID. 
 
@@ -292,7 +292,7 @@ You only need to connect Redshift to Glue once. As the Mixpanel pipeline exports
 You can also join data stored in Redshift with Mixpanel data available in S3 through the external schema.
 
 ## Queries
-You can query data with a single table schema or with a multiple table schema in Redshift Spectrum. To get more information about the table schemas, please see [Schema](/docs/data-pipelines/schematized-export-pipeline#schema).
+You can query data with a single table schema or with a multiple table schema in Redshift Spectrum. To get more information about the table schemas, please see [Schema](/docs/data-pipelines/old-pipelines/schematized-export-pipeline#schema).
 
 To query a single table schema, use this snippet.
 ```sql
@@ -308,7 +308,7 @@ FROM mixpanel.mp_master_event
 WHERE mp_event_name = “<CLEANED_EVENT_NAME>”
 ```
 
-`CLEANED_EVENT_NAME` is the transformed event name based on [transformation rules](/docs/data-pipelines/schematized-export-pipeline#transformation-rules).
+`CLEANED_EVENT_NAME` is the transformed event name based on [transformation rules](/docs/data-pipelines/old-pipelines/schematized-export-pipeline#transformation-rules).
 
 #### Nested and Repeated Fields
 

pages/docs/data-pipelines/old-pipelines/integrations/schematized-azure-pipeline.md

@@ -1,12 +1,12 @@
 # Schematized Azure Pipeline
 
-Mixpanel’s Azure Blob Export is one type of [Schematized Export Pipeline](/docs/data-pipelines/schematized-export-pipeline) that exports Mixpanel events and people data and imports them into an Azure Blob storage instance. 
+Mixpanel’s Azure Blob Export is one type of [Schematized Export Pipeline](/docs/data-pipelines/old-pipelines/schematized-export-pipeline) that exports Mixpanel events and people data and imports them into an Azure Blob storage instance. 
 
 Azure Export enables the use of SQL to query your event data, either for expressing new types of queries or for joining against other data already present in your data environment.
 
 ## Integration Set Up
 
-In order to export data to Azure Blob Storage, you must first give Mixpanel permission to write to Azure. Next you can [create a pipeline](https://developer.mixpanel.com/reference/create-warehouse-pipeline) to export the data. Mixpanel then uploads the data to Azure Blob Storage on a recurring basis. The data is a slightly transformed version of the raw data stored in Mixpanel. Please see [transformation rules](/docs/data-pipelines/schematized-export-pipeline#transformation-rules) to understand how the data is transformed.
+In order to export data to Azure Blob Storage, you must first give Mixpanel permission to write to Azure. Next you can [create a pipeline](https://developer.mixpanel.com/reference/create-warehouse-pipeline) to export the data. Mixpanel then uploads the data to Azure Blob Storage on a recurring basis. The data is a slightly transformed version of the raw data stored in Mixpanel. Please see [transformation rules](/docs/data-pipelines/old-pipelines/schematized-export-pipeline#transformation-rules) to understand how the data is transformed.
 
 ## Edit Mixpanel Permission
 

pages/docs/data-pipelines/old-pipelines/integrations/schematized-bigquery-pipeline.md

@@ -10,7 +10,7 @@ There are currently two ways to export mixpanel data into big.
 ![image](/230698685-c02cb9a1-d66f-42a7-8063-8e78b79e7b1f.png)
 
 
-As part of the export pipeline, a new dataset `mixpanel_nessie_day_partitioned_<PROJECT_ID>` will be created if the customer chose to export into Mixpanel managed BigQuery or a dataset should be created with appropriate permissions on customer-managed BigQuery and provide us with a name. We also apply [transformation rules](/docs/data-pipelines/schematized-export-pipeline#transformation-rules) to make the data compatible with data warehouses. 
+As part of the export pipeline, a new dataset `mixpanel_nessie_day_partitioned_<PROJECT_ID>` will be created if the customer chose to export into Mixpanel managed BigQuery or a dataset should be created with appropriate permissions on customer-managed BigQuery and provide us with a name. We also apply [transformation rules](/docs/data-pipelines/old-pipelines/schematized-export-pipeline#transformation-rules) to make the data compatible with data warehouses. 
 
 For user profile and identity mappings tables, we create a new table with a random suffix every time and then will update the `mp_people` and `mp_identity_mappings` views accordingly to use the latest table. You should always use the views and should refrain from using the actual tables as we don't delete the old tables immediately and you may be using an old table.
 
@@ -22,7 +22,7 @@ The data in the tables is partitioned based on [`_PARTITIONTIME` pseudo column](
 Note: TIMEPARITIONING shouldn't be updated on the table. It will fail your export jobs. Create a new table/view from this table for custom partitioning.
 
 ## Queries
-You can query data with a single table schema or with a multiple table schema in BigQuery. To get more information about the table schemas, please see [Schema](/docs/data-pipelines/schematized-export-pipeline#schema).
+You can query data with a single table schema or with a multiple table schema in BigQuery. To get more information about the table schemas, please see [Schema](/docs/data-pipelines/old-pipelines/schematized-export-pipeline#schema).
 
 To query a single table schema, use this snippet.
 ```sql
@@ -37,7 +37,7 @@ SELECT count(*)
 FROM mixpanel_nessie_day_partitioned_<PROJECT_ID>.<CLEANED_EVENT_NAME>
 ```
 
-`CLEANED_EVENT_NAME` is the transformed event name based on [transformation rules](/docs/data-pipelines/schematized-export-pipeline#transformation-rules).
+`CLEANED_EVENT_NAME` is the transformed event name based on [transformation rules](/docs/data-pipelines/old-pipelines/schematized-export-pipeline#transformation-rules).
 
 #### Getting the number of events in each day
 You will need this if you suspect the export process is not exporting all the events you want. As the tables are partitions using  [`_PARTITIONTIME` pseudo column](https://cloud.google.com/bigquery/docs/querying-partitioned-tables#ingestion-time_partitioned_table_pseudo_columns) and in project timezone, you can use to following query to get the number of events per day in an easy and fast way:

pages/docs/data-pipelines/old-pipelines/integrations/schematized-gcs-pipeline.md

@@ -1,6 +1,6 @@
 # Schematized GCS Pipeline
 
-The Google Cloud Storage schema pipeline exports [transformed data](/docs/data-pipelines/schematized-export-pipeline#transformation-rules) to a GCS bucket. This can be useful in case you want to export Mixpanel data into your own BigQuery instance.
+The Google Cloud Storage schema pipeline exports [transformed data](/docs/data-pipelines/old-pipelines/schematized-export-pipeline#transformation-rules) to a GCS bucket. This can be useful in case you want to export Mixpanel data into your own BigQuery instance.
 
 To set up a schematized export pipeline to Google Cloud Storage (GCS) from Mixpanel, you must configure GCS to receive the exported data, then [create a pipeline](https://developer.mixpanel.com/reference/create-warehouse-pipeline) to export the data.
 

pages/docs/data-pipelines/old-pipelines/integrations/schematized-snowflake-pipeline.md

@@ -6,15 +6,15 @@ This guide describes how Mixpanel data is exported into a [Snowflake](https://do
 
 Mixpanel exports data to its own Snowflake account and gives your Snowflake account access to read the data. As a result, you will need a Snowflake account to be able to use the exported data. For more information on how to use your shared data, see [Sharing Data in Snowflake](https://docs.snowflake.net/manuals/user-guide-data-share.html). 
 
-For Snowflake export, we first load the data into a single-column raw (VARIANT type) data table. This data will be a [transformed version](/docs/data-pipelines/schematized-export-pipeline#section-transformation-rules) of the raw data stored in Mixpanel. Then, we create a view to expose all properties as columns. The view name is the cleaned version of the event name and the raw table name is always the view name suffixed with `_raw`. For example, for `signup` event, you will have a `signup_raw` table and a `signup` view. Please see [Schema](/docs/data-pipelines/schematized-export-pipeline#schema) for general information about the schemas in Schematized Export Pipelines. 
+For Snowflake export, we first load the data into a single-column raw (VARIANT type) data table. This data will be a [transformed version](/docs/data-pipelines/old-pipelines/schematized-export-pipeline#section-transformation-rules) of the raw data stored in Mixpanel. Then, we create a view to expose all properties as columns. The view name is the cleaned version of the event name and the raw table name is always the view name suffixed with `_raw`. For example, for `signup` event, you will have a `signup_raw` table and a `signup` view. Please see [Schema](/docs/data-pipelines/old-pipelines/schematized-export-pipeline#schema) for general information about the schemas in Schematized Export Pipelines. 
 
 ## Partitioning
 
 The data in the raw tables is clustered based on `time` column but in project's timezone. To be exact, we use `CLUSTER BY (TO_DATE(CONVERT_TIMEZONE('UTC','<TIMEZONE>', TO_TIMESTAMP(DATA:time::NUMBER)))` where `TIMEZONE` is the Mixpanel project's timezone.
 
 ## Queries
 
-Mixpanel recommends you place all events into a single table to make querying easier. To get more information about the table schemas, please see [Schema](/docs/data-pipelines/schematized-export-pipeline#schema). 
+Mixpanel recommends you place all events into a single table to make querying easier. To get more information about the table schemas, please see [Schema](/docs/data-pipelines/old-pipelines/schematized-export-pipeline#schema). 
 
 A query is a request for data results. You can perform actions on the data, such as combine data from different tables; add, change, or delete table data; and perform calculations.