Redo project points

content/resume/_index.md

@@ -22,42 +22,50 @@ date="July 2025" show="true" %}}
 
 <!--- RBC AML }}} -->
 
-<!--- Rarity Surf {{{ -->
-
-{{% resume/project name="Rarity Surf" 
-languages="Python, Django, JavaScript, React"  
-date="Oct 2024" show="true" %}}
-
-- **Developed a full-stack web application** to generate rarity 
-  rankings for NFT's integrated with leading NFT 
-  marketplace's (OpenSea) API, 
-  enabling users to **quickly identify rare NFT's** and check 
-  their listing status, **improving market research efficiency by 80%**.
-- **Architected a robust Django (Python) [backend](https://github.com/Kevin-Mok/rarity-surf)** to fetch and process 
-  NFT metadata from IPFS, store rarity rankings in 
-  **PostgreSQL**, and serve the data via GraphQL API, **ensuring low-latency access and scaling to handle 2,000+ concurrent requests**.
-
-{{% /resume/project %}}
-
-<!--- Rarity Surf }}} -->
-
 <!--- Spotify Visualized {{{ -->
 
 {{% resume/project name="Spotify Visualized" 
-url="https://github.com/Kevin-Mok/astronofty" languages="Python, Django" date="June 2022" 
+url="https://github.com/Kevin-Mok/astronofty" languages="Python, Django" date="June 2023" 
 show="true" %}}
 
-- **Built a [high-performance backend](https://github.com/Kevin-Mok/spotify-lib-vis)** in Python with Django, 
-  utilizing Django ORM to model and manage user data 
-  efficiently, processing over **10,000 tracks per library** via 
-  the Spotify API.
-- **Engineered and optimized database models** achieving a **50% reduction in query latency** on PostgreSQL 
-  for core workflows through effective schema normalization.
+- **Built a high-performance Python backend** using 
+  Django and PostgreSQL to process 10K+ data records 
+  per user, optimizing ingestion pipelines via API 
+  integration and ORM modeling.
+- **Engineered normalized database schemas** to 
+  streamline query workflows, achieving a **50% 
+  reduction in PostgreSQL latency** for high-volume 
+  reporting tasks.
+- **Visualized user music libraries in Tableau**, 
+  creating dashboards that grouped tracks by **artist 
+  and genre**, enabling users to explore listening 
+  patterns and discover trends in their Spotify data.
 
 {{% /resume/project %}}
 
 <!--- Spotify Visualized }}} -->
 
+<!--- Rarity Surf {{{ -->
+
+{{% resume/project name="Rarity Surf" 
+languages="Python, Django, JavaScript, React"  
+date="Oct 2022" show="true" %}}
+
+- **Built a full-stack reporting tool** using React, 
+  Django, and **PostgreSQL** to analyze 
+  structured/unstructured metadata from APIs, enabling 
+  real-time rarity scoring and improving insight 
+  delivery by **80%**.
+- **Engineered a scalable data pipeline** in Django 
+  (Python) to ingest, process, and expose NFT ranking 
+  data via GraphQL, supporting **low-latency 
+  reporting** and scaling to **2,000+ concurrent 
+  queries** for end-user research.
+
+{{% /resume/project %}}
+
+<!--- Rarity Surf }}} -->
+
 {{% /resume/section %}}<!--- }}} -->
 
 {{% resume/section "Work Experience" %}}<!--- {{{ -->