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dbt Models / Transformation Layer
Transformation layer built in dbt on BigQuery. Models handle
data cleaning, normalization of inconsistent labels, and
aggregation logic for energy consumption metrics by household
segment, time of day, and weather conditions.
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Related posts
Title:
Lead Management Dashboard — Data Visualization.
Description:
Designed a lead management dashboard to visualize and track key sales metrics including lead status, conversion rates, and session sources. Created a sample dataset and built the dashboard to demonstrate how businesses can monitor their pipeline and make data-driven decisions at a glance.
Tools used:Canva (design), Power BI / Tableau (data visualization experience).
looks great,
Built a full YouTube analytics dashboard in Google Looker Studio using real channel data from Dark Psychology Archive.
The dashboard tracks 6 KPIs — Views (18,582), Watch Time (51.2 hrs), CTR (4.32%), Likes (1,302), Subscribers Gained (105), and Engagement Rate (10.31%). A monthly trend line reveals the growth curve peaking at 4,266 views in November. Content-type breakdown shows Shorts drive 71% of total views. Top performer: Hoovering at 1,232 views with 8.2% CTR.
Built to help content creators make data-driven decisions on what to post, when, and in what format — without exporting CSVs manually.
💡 𝗧𝗶𝗽 𝗼𝗳 𝘁𝗵𝗲 𝗗𝗮𝘆 — 𝗗𝗷𝗮𝗻𝗴𝗼
𝗗𝗶𝗱 𝘆𝗼𝘂 𝗸𝗻𝗼𝘄?
Using "only()" and "defer()" in Django can significantly reduce query payload when you don’t need every model field.
🔧 "only()" → Load 𝘰𝘯𝘭𝘺 𝘴𝘱𝘦𝘤𝘪𝘧𝘪𝘤 𝘧𝘪𝘦𝘭𝘥𝘴
🔧 "defer()" → Load 𝘦𝘷𝘦𝘳𝘺𝘵𝘩𝘪𝘯𝘨 𝘦𝘹𝘤𝘦𝘱𝘵 𝘴𝘱𝘦𝘤𝘪𝘧𝘪𝘦𝘥 𝘧𝘪𝘦𝘭𝘥𝘴
Why it matters:
- Less data transferred from DB
- Lower memory usage
- Faster responses for large models
Smart field selection = better performance.
#Python #BackendDevelopment #WebDevelopment #PerformanceOptimization
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