Reorder sidebar

docs/website/docs/reference/performance.md

@@ -1,10 +1,10 @@
 ---
-title: Performance
+title: Optimizing dlt
 description: Scale-up, parallelize and finetune dlt pipelines
 keywords: [scaling, parallelism, finetuning]
 ---
 
-# Performance
+# Optimizing dlt
 
 ## Yield pages instead of rows
 

docs/website/docs/tutorial/load-data-from-an-api.md

@@ -574,9 +574,8 @@ Interested in learning more? Here are some suggestions:
     - [Run in production: inspecting, tracing, retry policies and cleaning up](../running-in-production/running).
     - [Run resources in parallel, optimize buffers and local storage](../reference/performance.md)
     - [Use REST API client helpers](../general-usage/http/rest-client.md) to simplify working with REST APIs.
-3. Check out our [how-to guides](../walkthroughs) to get answers to some common questions.
-4. Explore [destinations](../dlt-ecosystem/destinations/) and [sources](../dlt-ecosystem/verified-sources/) provided by us and community.
-5. Explore the [Examples](../examples) section to see how dlt can be used in real-world scenarios
+3. Explore [destinations](../dlt-ecosystem/destinations/) and [sources](../dlt-ecosystem/verified-sources/) provided by us and community.
+4. Explore the [Examples](../examples) section to see how dlt can be used in real-world scenarios
 
 
 

docs/website/docs/walkthroughs/share-a-dataset.md

@@ -1,10 +1,10 @@
 ---
-title: 'Share a dataset: DuckDB -> BigQuery'
+title: 'Moving from local to production'
 description: Share a local dataset by moving it to BigQuery
 keywords: [how to, share a dataset]
 ---
 
-# Share a dataset: DuckDB -> BigQuery
+# Moving from local to production
 
 In previous how-to guides you used the local stack to create and run your pipeline. This saved you
 the headache of setting up cloud account, credentials and often also money. Our choice for local