{"id":3303,"date":"2026-05-30T16:54:57","date_gmt":"2026-05-30T16:54:57","guid":{"rendered":"https:\/\/ranaghazzi.com\/?page_id=3303"},"modified":"2026-06-26T08:02:16","modified_gmt":"2026-06-26T08:02:16","slug":"blogs","status":"publish","type":"page","link":"https:\/\/ranaghazzi.com\/?page_id=3303","title":{"rendered":"Blogs"},"content":{"rendered":"<p><style>\n    .light-font-container, .light-font-container p, .light-font-container h2, .light-font-container li {<br \/>\n        font-weight: #FFFFFF !important;<br \/>\n    }<br \/>\n<\/style>\n<\/p>\n<div class=\"light-font-container\" style=\"background-color: #FFFFFF; padding: 40px; border-radius: 15px;\">\n\n\n<ul class=\"wp-block-list\">\n<li style=\"margin-top:var(--wp--preset--spacing--40);margin-right:var(--wp--preset--spacing--20);margin-bottom:var(--wp--preset--spacing--40);margin-left:var(--wp--preset--spacing--20)\"><a href=\"https:\/\/ranaghazzi.com\/?p=5475\">Handling Duplicates in Spark Streaming Pipelines: 3 Practical Approaches<\/a><\/li>\n\n\n\n<li style=\"margin-top:var(--wp--preset--spacing--40);margin-right:var(--wp--preset--spacing--20);margin-bottom:var(--wp--preset--spacing--40);margin-left:var(--wp--preset--spacing--20)\"><a href=\"https:\/\/ranaghazzi.com\/?p=5124\">Streaming Tables vs. Regular Delta Tables: Choosing the Right Tool for Your Data<\/a><\/li>\n\n\n\n<li style=\"margin-top:var(--wp--preset--spacing--40);margin-right:var(--wp--preset--spacing--20);margin-bottom:var(--wp--preset--spacing--40);margin-left:var(--wp--preset--spacing--20)\"><a href=\"https:\/\/ranaghazzi.com\/?p=5144\">Streaming Tables vs. Materialized Views in Databricks: Which One Should You Use?<\/a><\/li>\n\n\n\n<li style=\"margin-top:var(--wp--preset--spacing--40);margin-right:var(--wp--preset--spacing--20);margin-bottom:var(--wp--preset--spacing--40);margin-left:var(--wp--preset--spacing--20)\"><a href=\"https:\/\/ranaghazzi.com\/?p=5165\">Auto Loader: The Smartest Way to Ingest Streaming Data in Databricks<\/a><\/li>\n\n\n\n<li style=\"margin-top:var(--wp--preset--spacing--40);margin-right:var(--wp--preset--spacing--20);margin-bottom:var(--wp--preset--spacing--40);margin-left:var(--wp--preset--spacing--20)\"><a href=\"https:\/\/ranaghazzi.com\/?p=5203\">Windowing and Watermarking in Databricks Streaming<\/a><\/li>\n\n\n\n<li style=\"margin-top:var(--wp--preset--spacing--40);margin-right:var(--wp--preset--spacing--20);margin-bottom:var(--wp--preset--spacing--40);margin-left:var(--wp--preset--spacing--20)\"><a href=\"https:\/\/ranaghazzi.com\/?p=5184\">Predefined Schemas vs. Schema Inference<\/a><\/li>\n\n\n\n<li style=\"margin-top:var(--wp--preset--spacing--40);margin-right:var(--wp--preset--spacing--20);margin-bottom:var(--wp--preset--spacing--40);margin-left:var(--wp--preset--spacing--20)\"><a href=\"https:\/\/ranaghazzi.com\/?p=4556\">Stop Flying Blind: How We Built a Custom Monitoring Framework for Databricks Pipelines<\/a><\/li>\n\n\n\n<li style=\"margin-top:var(--wp--preset--spacing--40);margin-right:var(--wp--preset--spacing--20);margin-bottom:var(--wp--preset--spacing--40);margin-left:var(--wp--preset--spacing--20)\"><a href=\"https:\/\/ranaghazzi.com\/?p=5268\">Structured Streaming&nbsp;vs. &nbsp;DLT&nbsp;Live Table(@dp Declarative Pipeline<\/a><\/li>\n\n\n\n<li style=\"margin-top:var(--wp--preset--spacing--40);margin-right:var(--wp--preset--spacing--20);margin-bottom:var(--wp--preset--spacing--40);margin-left:var(--wp--preset--spacing--20)\"><a href=\"https:\/\/ranaghazzi.com\/?p=5291\">PostgreSQL (SQL) vs pandas vs PySpark \u2014 Cheatsheet \u2014 quick syntax referen<\/a>ce<\/li>\n\n\n\n<li style=\"margin-top:var(--wp--preset--spacing--40);margin-right:var(--wp--preset--spacing--20);margin-bottom:var(--wp--preset--spacing--40);margin-left:var(--wp--preset--spacing--20)\"><a href=\"https:\/\/ranaghazzi.com\/?p=5352\">Databricks Clusters Demystified: A Practical Guide to Job Clusters, All-Purpose Clusters, and Serverless Compute<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/ranaghazzi.com\/?p=5381\">The Six Lanes of Data Ingestion in Databricks: A Practical Guide<\/a><\/li>\n\n\n\n<li class=\"has-text-color has-link-color has-x-large-font-size wp-elements-9649c635ef58fbfadc226257556a968b\" style=\"color:#f20707\">Coming Soon <\/li>\n\n\n\n<li>Upserts in Databricks: From Delta Merge to AUTO CDC<\/li>\n\n\n\n<li style=\"margin-top:var(--wp--preset--spacing--40);margin-right:var(--wp--preset--spacing--20);margin-bottom:var(--wp--preset--spacing--40);margin-left:var(--wp--preset--spacing--20)\">Databricks Pipeline Architecture: Tasks Within a Job vs. Job Chaining Explained<\/li>\n\n\n\n<li style=\"margin-top:var(--wp--preset--spacing--40);margin-right:var(--wp--preset--spacing--20);margin-bottom:var(--wp--preset--spacing--40);margin-left:var(--wp--preset--spacing--20)\">Flattening Nested GA4 Data with PySpark: A Practical Guide Coming Soon <\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":2,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-3303","page","type-page","status-publish","hentry"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.0 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Blogs - Rana Nasri Ghazzi<\/title>\n<meta name=\"description\" content=\"Browse real-world data projects by Rana Ghazzi, covering data cleaning, analysis, and storytelling with Python, SQL, and Tableau Explore Rana Ghazzi&#039;s data analytics portfolio \u2014 dashboards, visualizations, and insights built with Tableau, Power BI &amp; Python.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/ranaghazzi.com\/?page_id=3303\" \/>\n<meta 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