diff --git a/content/docs/start/index.md b/content/docs/start/index.md
index e7786735b5..c55f1f1caf 100644
--- a/content/docs/start/index.md
+++ b/content/docs/start/index.md
@@ -46,15 +46,20 @@ $ git commit -m "Initialize DVC"
 DVC functionality can be split into layers and we'll explore them one by one in
 the next few sections:
 
-- [**Data management**](/doc/tutorials/get-started/data-pipelines) is the core
+- [**Data versioning**](/doc/start/data-versioning) is the core
   part of DVC for large files, datasets, ML models versioning and efficient
   sharing. We'll show how to use a regular Git workflow, without storing large
   files with Git. Think "Git for data".
 
-- [**Data pipelines**](/doc/tutorials/get-started/data-pipelines) describe how
+- [**Data access**](/doc/start/data-access) shows how to use data artifacts
+  from outside of the project and how to import data artifacts from another DVC
+  projects. This can help to download a specific version of an ML model to a
+  deployment server or import a model to another project.
+
+- [**Data pipelines**](/doc//start/data-pipelines) describe how
   models and other data artifacts are built, and provide an efficient way to
   reproduce them. Think "Makefiles for data and ML projects" done right.
 
-- [**Experiments**](/doc/tutorials/get-started/experiments) attach parameters,
+- [**Experiments**](/doc/start/experiments) attach parameters,
   metrics, plots. You can capture and navigate experiments not leaving Git.
   Think "Git for ML".