fix(docs): fix some broken links in the docs

docs-website/generateDocsDir.ts

@@ -305,7 +305,7 @@ function markdown_sanitize_and_linkify(content: string): string {
   // Link to issues/pull requests.
   content = content.replace(
     /#(\d+)\b/g,
-    "[#$1](https://github.com/linkedin/datahub/issues/$1)"
+    "[#$1](https://github.com/linkedin/datahub/pull/$1)"
   );
 
   return content;

docs/how/build-metadata-service.md

@@ -161,7 +161,7 @@ public interface GraphBuilder<SNAPSHOT extends RecordTemplate> {
 [RecordTemplate]: https://github.com/linkedin/rest.li/blob/master/data/src/main/java/com/linkedin/data/template/RecordTemplate.java
 [GenericRecord]: https://github.com/apache/avro/blob/master/lang/java/avro/src/main/java/org/apache/avro/generic/GenericRecord.java
 [DAO]: https://en.wikipedia.org/wiki/Data_access_object
-[Pegasus]: https://linkedin.github.io/rest.li/DATA-Data-Schema-and-Templates
+[Pegasus]: https://linkedin.github.io/rest.li/pdl_schema
 [relationship]: ../what/relationship.md
 [entity]: ../what/entity.md
 [aspect]: ../what/aspect.md

docs/links.md

@@ -1,14 +1,14 @@
 # Articles & Talks
 
-## Articles
+## Related Articles
 * [DataHub: A Generalized Metadata Search & Discovery Tool](https://engineering.linkedin.com/blog/2019/data-hub)
 * [Open sourcing DataHub: LinkedIn’s metadata search and discovery platform](https://engineering.linkedin.com/blog/2020/open-sourcing-datahub--linkedins-metadata-search-and-discovery-p)
 * [Data Catalogue — Knowing your data](https://medium.com/albert-franzi/data-catalogue-knowing-your-data-15f7d0724900)
 * [LinkedIn Datahub Application Architecture Quick Understanding](https://medium.com/@liangjunjiang/linkedin-datahub-application-architecture-quick-understanding-a5b7868ee205)
 * [LinkIn Datahub Metadata Ingestion Scripts Unofficical Guide](https://medium.com/@liangjunjiang/linkin-datahub-etl-unofficical-guide-7c3949483f8b)
 * [Datahub - RPubs](https://rpubs.com/Priya_Shaji/dataHub)
 * [A Dive Into Metadata Hubs](https://www.holistics.io/blog/a-dive-into-metadata-hubs/)
-* [How LinkedIn, Uber, Lyft, Airbnb and Netflix are Solving Data Management and Discovery for Machine Learning Solutions](https://towardsdatascience.com/how-linkedin-uber-lyft-airbnb-and-netflix-are-solving-data-management-and-discovery-for-machine-9b79ee9184bb)
+* [How LinkedIn, Uber, Lyft, Airbnb and Netflix are Solving Data Management and Discovery for Machine Learning Solutions](https://www.kdnuggets.com/2019/08/linkedin-uber-lyft-airbnb-netflix-solving-data-management-discovery-machine-learning-solutions.html)
 * [Data Discovery in 2020](https://medium.com/@torokyle/data-discovery-in-2020-3c907383caa0)
 * [Work-Bench Snapshot: The Evolution of Data Discovery & Catalog](https://medium.com/work-bench/work-bench-snapshot-the-evolution-of-data-discovery-catalog-2f6c0425616b)
 * [In-house Data Discovery platforms](https://datastrategy.substack.com/p/in-house-data-discovery-platforms)

docs/modeling/extending-the-metadata-model.md

@@ -1,10 +1,8 @@
 ---
-title: Extending the metadata model
-sidebar_label: Extending the metadata model
 slug: /metadata-modeling/extending-the-metadata-model
 ---
 
-# How do I extend the Metadata model? 
+# Extending the Metadata Model
 
 You can extend the metadata model by either creating a new Entity or extending an existing one. Unsure if you need to
 create a new entity or add an aspect to an existing entity? Read [metadata-model](./metadata-model.md) to understand
@@ -15,9 +13,9 @@ Dashboard Entity. If you want to extend an existing Entity, you can skip directl
 
 At a high level, an entity is made up of
 
-1) a union of Aspects, or bundles of related metadata,
-2) a Key Aspect, which uniquely identifies an instance of an entity,
-3) A snapshot, which pairs a group of aspects with a serialized key, or urn.
+1. a union of Aspects, or bundles of related metadata,
+2. a Key Aspect, which uniquely identifies an instance of an entity,
+3. A snapshot, which pairs a group of aspects with a serialized key, or urn.
 
 ## Defining an Entity
 
@@ -62,7 +60,9 @@ record DashboardKey {
 
 The Urn representation of the Key shown above would be:
 
-```urn:li:dashboard:(<tool>,<id>)```
+```
+urn:li:dashboard:(<tool>,<id>)
+```
 
 Because they are aspects, keys need to be annotated with an @Aspect annotation, This instructs DataHub that this struct can be a part of.
 

docs/what/mxe.md

@@ -4,7 +4,7 @@ The models defined in [snapshot](snapshot.md) and [delta](delta.md) are used to
 
 We also model MXEs using [PDL](https://linkedin.github.io/rest.li/pdl_schema) and rely on the [pegasus gradle plugin](https://linkedin.github.io/rest.li/setup/gradle#generateavroschema) to convert them into [AVSC](https://avro.apache.org/docs/current/spec.html). However, we also need to rename all the namespaces of the generated AVSC to avoid namespace clashes for projects that depend on both the PDL models and MXEs. 
 
-As the AVSC and PDL model schemas are 100% compatible, it’d be very easy to convert the in-memory representation from one to another using [Pegasus’ DataTranslator](https://linkedin.github.io/rest.li/DATA-Data-Schema-and-Templates#translating-data-to-and-from-avro).
+As the AVSC and PDL model schemas are 100% compatible, it’d be very easy to convert the in-memory representation from one to another using [Pegasus’ DataTranslator](https://linkedin.github.io/rest.li/avro_translation).
 
 ## Metadata Change Event (MCE)