Data Architecture - Critical Components

 Referred Link - https://www.linkedin.com/feed/update/urn:li:activity:7218958479162531840/

Every Data Architect must know the critical components of Data Architecture.

Here is a quick rundown for you:

🔘 𝐃𝐚𝐭𝐚 𝐒𝐨𝐮𝐫𝐜𝐞𝐬:

↳ Systems of Records: The sources where data is created.
↳ APIs & Files: Pathways and formats through which data travels and is stored.

🔘 𝐃𝐚𝐭𝐚 𝐈𝐧𝐠𝐞𝐬𝐭𝐢𝐨𝐧:

↳ Data Streaming: Real-time data flow, like live news updates.
↳ Batch Processing: Collecting and processing data in intervals, like weekly reports.

🔘 𝐃𝐚𝐭𝐚 𝐏𝐫𝐨𝐜𝐞𝐬𝐬𝐢𝐧𝐠:

↳ Data Pipelines: The routes that data takes from collection to storage.
↳ ML/Analytics: Using algorithms to analyse and gain insights from data.

🔘 𝐃𝐚𝐭𝐚 𝐒𝐭𝐨𝐫𝐚𝐠𝐞:

↳ Data Lake House: A combo of data lakes and warehouses for flexible storage.
↳ Data Warehouse: A structured storage space for easy data retrieval and analysis.

🔘 𝐃𝐚𝐭𝐚 𝐂𝐨𝐧𝐬𝐮𝐦𝐞𝐫𝐬:

↳ Business Intelligence: Tools that turn data into actionable business insights.
↳ Users & Data Scientists: The people who use and analyse the data to make decisions.

🔘 𝐃𝐚𝐭𝐚 𝐆𝐨𝐯𝐞𝐫𝐧𝐚𝐧𝐜𝐞:

↳ Lineage, Marketplace, Catalog, Glossary: Ensuring data is accurate, consistent, and accessible.

🔘 𝐃𝐚𝐭𝐚 𝐈𝐧𝐟𝐫𝐚𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞:

↳ Compute, Memory, Networking, Storage: The technical foundation that supports data operations.

🔘 𝐃𝐚𝐭𝐚 𝐒𝐞𝐜𝐮𝐫𝐢𝐭𝐲:

↳ Access, IAM, Encryption, Backup, Archive: Keeping data safe and secure from breaches.

🔘 𝐃𝐚𝐭𝐚 𝐏𝐥𝐚𝐭𝐟𝐨𝐫𝐦 𝐎𝐛𝐬𝐞𝐫𝐯𝐚𝐛𝐢𝐥𝐢𝐭𝐲:

↳ Monitoring and Alerts: Observe and act on platform issues.

#Data Science, #Data Analytics,