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🔅 Data Analytics with Observable
🌐 Author: Bill Shander
🔰 Level: Intermediate
⏰ Duration: 2h 9m
📗 Topics: Data Visualization, Data Analytics
📤 Join Data Analysis for more courses
🌀 Get an overview of the Observable platform and build real skills fast.
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Observable is one of the most exciting (and constantly expanding) platforms to use for data analytics, visualization, storytelling, and collaboration. Its blend of easy-to-use click and drag features and customization makes it extremely popular for users across a wide range of skillsets. In this course, data analytics and visualization expert Bill Shander gives you an overview of the Observable platform, introducing the key features and functionalities with practical and tangible examples. Bill shows you how to get data into Observable, manipulate that data, and make visuals and reports with it. He demonstrates how to add interactivity to the reports, and how to make visuals in a variety of ways—some of which are one-click and others that offer more customizability with coding. By the end of the course, you will be able to spin up a new notebook, add data to it, and create a fully interactive data report.
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Built using C language, PostgreSQL is the most popular choice of database from small web apps to enterprise systems. It runs as a multi-process system and follows ACID principles.
1 - PostgreSQL supports concurrent client connections independently. Each client connection to PostgreSQL creates a dedicated server process.
2 - The Postmaster Process is the main supervisor that manages all other PostgreSQL processes. It controls the entire database instance.
3 - Background workers run parallel processes when needed to handle specialized tasks.
4 - PostgreSQL shared memory is a central memory area containing multiple buffers such as Shared, WAL, Clog, and Temporary buffers. All components communicate through this shared memory.
5 - PostgreSQL also has several auxiliary processes such as:
- BG Writer: Manages background writing
- WAL Writer: Handles write-ahead logging
- Auto Vacuum: Maintains database cleanliness
- Checkpointer: Ensures data consistency
- Stats Collector: Gathers statistics
- System Logger: Manages Logging
- Archiver: Handles archiving
- Replication launcher: Manages replication
6 - PostgreSQL has different types of physical files for varied needs such as:
- Data Files: Stores actual database data
- WAL Files: Write-ahead log storage
- Archive Files: Backup and recovery data
- Log Files: System and error logs
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