diff --git a/README.md b/README.md
index 61cf6b50..cc64ef01 100644
--- a/README.md
+++ b/README.md
@@ -116,6 +116,10 @@ $ docker cp /path/to/your/backup.json container_name:/path/inside/container/back
 $ docker-compose -f local.yml run --rm django python manage.py loaddata /path/inside/the/container/backup.json
 $ docker-compose -f local.yml run --rm django python manage.py migrate
 ```
+### Restoring the Database from a SQL Dump
+If the JSON file is particularly large (>1.5GB), Docker might struggle with this method. In such cases, you can use SQL dump and restore commands as an alternative, as described [here](./SQLDumpRestoration.md).
+
+
 
 ## Additional Commands
 
@@ -191,8 +195,7 @@ Documented [here](https://github.com/NASA-IMPACT/sde-indexing-helper/wiki/How-to
 
 ## Adding New Features/Fixes
 
-1. Start with a [GitHub issue](https://github.com/NASA-IMPACT/sde-indexing-helper/issues).
-2. Use the GitHub CLI to create branches and pull requests (`gh issue develop -c <issue_number>`).
+We welcome contributions to improve the project! Before you begin, please take a moment to review our [Contributing Guidelines](./CONTRIBUTING.md). These guidelines will help you understand the process for submitting new features, bug fixes, and other improvements.
 
 ## Job Creation
 
diff --git a/SQLDumpRestoration.md b/SQLDumpRestoration.md
new file mode 100644
index 00000000..6b4792be
--- /dev/null
+++ b/SQLDumpRestoration.md
@@ -0,0 +1,85 @@
+## Restoring the Database from SQL Dump
+
+We generally load a database backup from a JSON file by using the following command.
+
+```
+docker-compose -f local.yml run --rm django python manage.py loaddata backup.json
+```
+
+However, if the JSON file is particularly large (>1.5GB), Docker might struggle with this method. In such cases, you can use SQL dump and restore commands as an alternative.
+
+### Steps for Using SQL Dump and Restore
+
+1. Begin by starting only the PostgreSQL container. This prevents the Django container from making changes while the PostgreSQL container is starting up.
+
+```
+docker-compose -f local.yml up postgres
+```
+
+2. Find the container ID using `docker ps`, then enter the PostgreSQL container to execute commands.
+
+```
+$ docker ps
+CONTAINER ID   IMAGE                                     COMMAND
+23d33f22cc43   sde_indexing_helper_production_postgres   "docker-entrypoint.s…"
+
+$ docker exec -it 23d33f22cc43 bash
+```
+
+3. Create a connection to the database.
+
+```
+psql -U <POSTGRES_USER> -d <POSTGRES_DB>
+```
+
+**Note**:
+- For local deployment, refer to the `.envs/.local/.postgres` file for the `POSTGRES_USER` and `POSTGRES_DB` variables.
+- For production deployment, refer to the `.envs/.production/.postgres` file.
+
+4. Ensure that the database `<POSTGRES_DB>` is empty. Here's an example:
+
+```
+sde_indexing_helper-# \c
+You are now connected to database "sde_indexing_helper" as user "VnUvMKBSdk...".
+sde_indexing_helper-# \dt
+Did not find any relations.
+```
+
+If the database is not empty, delete its contents to create a fresh database:
+
+```
+sde_indexing_helper=# \c postgres      //connect to a different database before dropping
+You are now connected to database "postgres" as user "VnUvMKBSdk....".
+postgres=# DROP DATABASE sde_indexing_helper;
+DROP DATABASE
+postgres=# CREATE DATABASE sde_indexing_helper;
+CREATE DATABASE
+
+```
+
+5. Transfer the backup SQL dump (`backup.sql`) from your local machine to the PostgreSQL container.
+
+```
+docker cp /local/path/backup.sql 23d33f22cc43:/
+```
+
+6. Import the SQL dump into the PostgreSQL container.
+
+```
+psql -U <POSTGRES_USER> -d <POSTGRES_DB> -f backup.sql
+```
+
+**Note**: To create a SQL dump of your PostgreSQL database, use the following command:
+
+```
+pg_dump -U <POSTGRES_USER> -W -F p -f backup.sql <POSTGRES_DB>
+```
+
+7. Bring up all containers at once, and create a superuser account for logging in.
+
+```
+docker-compose -f local.yml up
+docker-compose -f local.yml run --rm django python manage.py createsuperuser
+```
+
+8. Log in to the SDE Indexing Helper frontend to ensure that all data has been correctly populated in the UI.