<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Unity Catalog on AI VOID</title><link>https://ai-blog.noorshomelab.dev/tags/unity-catalog/</link><description>Recent content in Unity Catalog on AI VOID</description><generator>Hugo</generator><language>en</language><lastBuildDate>Sat, 20 Dec 2025 00:00:00 +0000</lastBuildDate><atom:link href="https://ai-blog.noorshomelab.dev/tags/unity-catalog/index.xml" rel="self" type="application/rss+xml"/><item><title>Setting Up Your Databricks Lakehouse Environment</title><link>https://ai-blog.noorshomelab.dev/realtime-supply-chain-intelligence-2/01-databricks-environment-setup/</link><pubDate>Sat, 20 Dec 2025 00:00:00 +0000</pubDate><guid>https://ai-blog.noorshomelab.dev/realtime-supply-chain-intelligence-2/01-databricks-environment-setup/</guid><description>&lt;h2 id="chapter-1-setting-up-your-databricks-lakehouse-environment"&gt;Chapter 1: Setting Up Your Databricks Lakehouse Environment&lt;/h2&gt;
&lt;p&gt;Welcome to the first chapter of our comprehensive guide to building a real-time supply chain analytics platform! In this chapter, we&amp;rsquo;ll lay the foundational groundwork for our project by setting up a robust, secure, and scalable Databricks Lakehouse environment. This initial setup is critical, as it dictates the security, governance, and operational efficiency of all subsequent data pipelines and analytics.&lt;/p&gt;
&lt;p&gt;Our focus in this chapter will be on configuring the core components of the Databricks Data Intelligence Platform, specifically enabling Unity Catalog for centralized data governance, establishing secure authentication mechanisms, defining cluster policies for cost control and consistency, and integrating with Git for version control. By the end of this chapter, you will have a production-ready Databricks workspace capable of securely hosting and processing sensitive supply chain data, ready for the real-time ingestion pipelines we&amp;rsquo;ll build next.&lt;/p&gt;</description></item><item><title>Setting Up Your Databricks Lakehouse Environment</title><link>https://ai-blog.noorshomelab.dev/realtime-supply-chain-intelligence/01-databricks-environment-setup/</link><pubDate>Sat, 20 Dec 2025 00:00:00 +0000</pubDate><guid>https://ai-blog.noorshomelab.dev/realtime-supply-chain-intelligence/01-databricks-environment-setup/</guid><description>&lt;h2 id="chapter-1-setting-up-your-databricks-lakehouse-environment"&gt;Chapter 1: Setting Up Your Databricks Lakehouse Environment&lt;/h2&gt;
&lt;p&gt;Welcome to the first chapter of our comprehensive guide to building a real-time supply chain analytics platform! In this chapter, we&amp;rsquo;ll lay the foundational groundwork for our project by setting up a robust, secure, and scalable Databricks Lakehouse environment. This initial setup is critical, as it dictates the security, governance, and operational efficiency of all subsequent data pipelines and analytics.&lt;/p&gt;
&lt;p&gt;Our focus in this chapter will be on configuring the core components of the Databricks Data Intelligence Platform, specifically enabling Unity Catalog for centralized data governance, establishing secure authentication mechanisms, defining cluster policies for cost control and consistency, and integrating with Git for version control. By the end of this chapter, you will have a production-ready Databricks workspace capable of securely hosting and processing sensitive supply chain data, ready for the real-time ingestion pipelines we&amp;rsquo;ll build next.&lt;/p&gt;</description></item><item><title>Ingesting &amp;amp; Harmonizing HS Code and Tariff Data</title><link>https://ai-blog.noorshomelab.dev/realtime-supply-chain-intelligence-2/06-hs-code-tariff-ingestion/</link><pubDate>Sat, 20 Dec 2025 00:00:00 +0000</pubDate><guid>https://ai-blog.noorshomelab.dev/realtime-supply-chain-intelligence-2/06-hs-code-tariff-ingestion/</guid><description>&lt;h2 id="chapter-6-ingesting--harmonizing-hs-code-and-tariff-data"&gt;Chapter 6: Ingesting &amp;amp; Harmonizing HS Code and Tariff Data&lt;/h2&gt;
&lt;h3 id="chapter-introduction"&gt;Chapter Introduction&lt;/h3&gt;
&lt;p&gt;In the intricate world of global supply chains, accurate and timely information on Harmonized System (HS) codes and associated tariffs is paramount. These codes classify traded goods, determining duties, taxes, and trade policies. In this chapter, we will build a robust data pipeline using Databricks Delta Live Tables (DLT) to ingest, cleanse, and harmonize raw HS Code and tariff data into our Customs Trade Data Lakehouse.&lt;/p&gt;</description></item><item><title>Ingesting &amp;amp; Harmonizing HS Code and Tariff Data</title><link>https://ai-blog.noorshomelab.dev/realtime-supply-chain-intelligence/06-hs-code-tariff-ingestion/</link><pubDate>Sat, 20 Dec 2025 00:00:00 +0000</pubDate><guid>https://ai-blog.noorshomelab.dev/realtime-supply-chain-intelligence/06-hs-code-tariff-ingestion/</guid><description>&lt;h2 id="chapter-6-ingesting--harmonizing-hs-code-and-tariff-data"&gt;Chapter 6: Ingesting &amp;amp; Harmonizing HS Code and Tariff Data&lt;/h2&gt;
&lt;h3 id="chapter-introduction"&gt;Chapter Introduction&lt;/h3&gt;
&lt;p&gt;In the intricate world of global supply chains, accurate and timely information on Harmonized System (HS) codes and associated tariffs is paramount. These codes classify traded goods, determining duties, taxes, and trade policies. In this chapter, we will build a robust data pipeline using Databricks Delta Live Tables (DLT) to ingest, cleanse, and harmonize raw HS Code and tariff data into our Customs Trade Data Lakehouse.&lt;/p&gt;</description></item><item><title>Data Governance and Security with Unity Catalog</title><link>https://ai-blog.noorshomelab.dev/databricks-mastery-2025/unity-catalog-governance/</link><pubDate>Fri, 19 Dec 2025 00:00:00 +0000</pubDate><guid>https://ai-blog.noorshomelab.dev/databricks-mastery-2025/unity-catalog-governance/</guid><description>&lt;h2 id="introduction-to-unity-catalog-your-datas-guardian"&gt;Introduction to Unity Catalog: Your Data&amp;rsquo;s Guardian&lt;/h2&gt;
&lt;p&gt;Welcome to Chapter 9! So far, you&amp;rsquo;ve mastered the art of processing data, building pipelines, and optimizing queries on Databricks. That&amp;rsquo;s fantastic! But imagine building a magnificent data castle without proper security or a clear map of its rooms and treasures. That&amp;rsquo;s where data governance and security come in, and on Databricks, the knight in shining armor for this task is &lt;strong&gt;Unity Catalog&lt;/strong&gt;.&lt;/p&gt;</description></item><item><title>End-to-End Real-time Procurement Price Intelligence</title><link>https://ai-blog.noorshomelab.dev/realtime-supply-chain-intelligence-2/11-procurement-price-intelligence/</link><pubDate>Sat, 20 Dec 2025 00:00:00 +0000</pubDate><guid>https://ai-blog.noorshomelab.dev/realtime-supply-chain-intelligence-2/11-procurement-price-intelligence/</guid><description>&lt;h2 id="chapter-11-end-to-end-real-time-procurement-price-intelligence"&gt;Chapter 11: End-to-End Real-time Procurement Price Intelligence&lt;/h2&gt;
&lt;h3 id="1-chapter-introduction"&gt;1. Chapter Introduction&lt;/h3&gt;
&lt;p&gt;In this pivotal chapter, we will construct an end-to-end real-time procurement price intelligence pipeline. This pipeline is crucial for modern supply chains, enabling organizations to react swiftly to price fluctuations, optimize procurement costs, and mitigate risks associated with volatile markets. By leveraging the power of Apache Kafka for real-time event ingestion, Databricks Delta Live Tables (DLT) for robust stream processing, and Delta Lake with Unity Catalog for reliable data storage and governance, we will build a system that delivers actionable insights continuously.&lt;/p&gt;</description></item><item><title>End-to-End Real-time Procurement Price Intelligence</title><link>https://ai-blog.noorshomelab.dev/realtime-supply-chain-intelligence/11-procurement-price-intelligence/</link><pubDate>Sat, 20 Dec 2025 00:00:00 +0000</pubDate><guid>https://ai-blog.noorshomelab.dev/realtime-supply-chain-intelligence/11-procurement-price-intelligence/</guid><description>&lt;h2 id="chapter-11-end-to-end-real-time-procurement-price-intelligence"&gt;Chapter 11: End-to-End Real-time Procurement Price Intelligence&lt;/h2&gt;
&lt;h3 id="1-chapter-introduction"&gt;1. Chapter Introduction&lt;/h3&gt;
&lt;p&gt;In this pivotal chapter, we will construct an end-to-end real-time procurement price intelligence pipeline. This pipeline is crucial for modern supply chains, enabling organizations to react swiftly to price fluctuations, optimize procurement costs, and mitigate risks associated with volatile markets. By leveraging the power of Apache Kafka for real-time event ingestion, Databricks Delta Live Tables (DLT) for robust stream processing, and Delta Lake with Unity Catalog for reliable data storage and governance, we will build a system that delivers actionable insights continuously.&lt;/p&gt;</description></item><item><title>Securing Your Lakehouse with Databricks Unity Catalog</title><link>https://ai-blog.noorshomelab.dev/realtime-supply-chain-intelligence-2/13-unity-catalog-security/</link><pubDate>Sat, 20 Dec 2025 00:00:00 +0000</pubDate><guid>https://ai-blog.noorshomelab.dev/realtime-supply-chain-intelligence-2/13-unity-catalog-security/</guid><description>&lt;h2 id="securing-your-lakehouse-with-databricks-unity-catalog"&gt;Securing Your Lakehouse with Databricks Unity Catalog&lt;/h2&gt;
&lt;p&gt;Welcome to Chapter 13 of our comprehensive guide! In the previous chapters, we&amp;rsquo;ve meticulously built robust data pipelines, ingesting real-time supply chain events, performing complex analytics, and establishing a sophisticated data lakehouse architecture. We&amp;rsquo;ve focused on data transformation, reliability, and performance. Now, it&amp;rsquo;s time to address a critical aspect for any production-ready system: &lt;strong&gt;security and data governance&lt;/strong&gt;.&lt;/p&gt;
&lt;p&gt;This chapter will guide you through implementing Databricks Unity Catalog to secure your data lakehouse. Unity Catalog provides a centralized governance solution for data and AI on the Databricks Lakehouse Platform, offering fine-grained access control, auditing, and data lineage across all your data assets. By the end of this chapter, you will have a securely governed lakehouse, ensuring that only authorized users and applications can access specific data, and that all data access is auditable and compliant with organizational policies.&lt;/p&gt;</description></item><item><title>Securing Your Lakehouse with Databricks Unity Catalog</title><link>https://ai-blog.noorshomelab.dev/realtime-supply-chain-intelligence/13-unity-catalog-security/</link><pubDate>Sat, 20 Dec 2025 00:00:00 +0000</pubDate><guid>https://ai-blog.noorshomelab.dev/realtime-supply-chain-intelligence/13-unity-catalog-security/</guid><description>&lt;h2 id="securing-your-lakehouse-with-databricks-unity-catalog"&gt;Securing Your Lakehouse with Databricks Unity Catalog&lt;/h2&gt;
&lt;p&gt;Welcome to Chapter 13 of our comprehensive guide! In the previous chapters, we&amp;rsquo;ve meticulously built robust data pipelines, ingesting real-time supply chain events, performing complex analytics, and establishing a sophisticated data lakehouse architecture. We&amp;rsquo;ve focused on data transformation, reliability, and performance. Now, it&amp;rsquo;s time to address a critical aspect for any production-ready system: &lt;strong&gt;security and data governance&lt;/strong&gt;.&lt;/p&gt;
&lt;p&gt;This chapter will guide you through implementing Databricks Unity Catalog to secure your data lakehouse. Unity Catalog provides a centralized governance solution for data and AI on the Databricks Lakehouse Platform, offering fine-grained access control, auditing, and data lineage across all your data assets. By the end of this chapter, you will have a securely governed lakehouse, ensuring that only authorized users and applications can access specific data, and that all data access is auditable and compliant with organizational policies.&lt;/p&gt;</description></item></channel></rss>