𝗘𝘅𝗽𝗹𝗼𝗿𝗲 𝘁𝗵𝗲 𝗗𝗲𝗽𝘁𝗵𝘀 𝗼𝗳 𝗗𝗮𝘁𝗮 𝗪𝗮𝗿𝗲𝗵𝗼𝘂𝘀𝗶𝗻𝗴 🏘💡

📌 Learn about the intricacies of Data Warehousing and the key components that shape this dynamic landscape:

📄 𝗗𝗮𝘁𝗮 𝗦𝗼𝘂𝗿𝗰𝗲𝘀

✔️OLTP (Online Transaction Processing): Real-time transaction processing..

✔️Flat Files: Text-based files serving as data sources.

✔️ERP/CRM: Integration of Enterprise Resource Planning and Customer Relationship Management data.

⚙ 𝗗𝗮𝘁𝗮 𝗣𝗿𝗼𝗰𝗲𝘀𝘀𝗶𝗻𝗴

✔️ELT (Extract, Load, Transform): Critical process of collecting, loading, and transforming data.

✔️Staging Data: Temporary storage for processed data before integration.

🔄 𝗗𝗮𝘁𝗮 𝗦𝘁𝗼𝗿𝗮𝗴𝗲

✔️Raw Data: Unprocessed foundation for transformation.

✔️Summary Data: Aggregated and condensed data for quick insights.

✔️Metadata: Crucial information about stored data.

✔️Data Marts: Specialized subsets catering to specific business needs.

📊 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀

✔️ OLAP (Online Analytical Processing): Empowers dynamic, multidimensional analysis.

✔️ Data Mining: Extracting patterns and knowledge from large datasets.

✔️ Analysis: In-depth examination of data for trends, patterns, and insights.

✔️ Reporting: Communicating findings through comprehensive reports.