Boost Your CLOUD CAREER with Microsoft Fabric in 2024 | Azure Data Basics | DP-600 скачать в хорошем качестве

Boost Your CLOUD CAREER with Microsoft Fabric in 2024 | Azure Data Basics | DP-600

Follow us on Linkedin:   / yatharth-kapoor     / uberlernen   Drop me an email at: yatharth.kapoor@uberlernen.com Summary of the Transcript Topics for the Video: Contextual Value of Data: Data without context is useless, but when context is provided, it turns into information, even if it's useful or not. Importance of understanding data's business value. Types of Data: Structured Data: Organized in a predefined format, such as tables with rows and columns. Semi-Structured Data: Loosely structured with some rules, like JSON or XML. Unstructured Data: No specific structure, such as text files or multimedia. Data Storage Formats: Files: Word files, CSV, JSON, XML. Blob Storage: Binary Large Objects. Databases: Relational (structured) vs. Non-relational (unstructured or semi-structured). Databases vs. Files: Databases: Highly structured, use tables and schemas, optimized for OLTP (Online Transactional Processing). Files: Suitable for semi-structured and unstructured data. Schemas and Tables: Definition of schema in databases. Dimension Tables vs. Fact Tables: D-tables for categories, F-tables for actual data. OLTP vs. OLAP: OLTP: Databases optimized for transaction-based operations (real-time updates). OLAP: Used for analytics, summarized data stored in cubes. ETL Process: Extract, Transform, Load: Moving important data from databases to data lakes and warehouses for analytics. Data Analytics and Cubes: Analytics best performed on summarized data. OLAP cubes for reporting; they must be refreshed periodically. Data Warehousing: Data warehouses are relational databases optimized for read-heavy operations. Importance of using data models for efficient reporting. Microsoft Cloud Services for Data: Azure SQL Database: PaaS offering, providing managed SQL services. Emphasis on cloud-based solutions for data management and analytic