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Best practices for log management and analytics: 1. Set a strategy. Don't log blindly. 2. Structure log data. 3. Separate and centralize log data. 4. Practice end-to-end logging. 5. Correlate data sources. 6. Use unique identifiers. 7. Add context. 8. Perform real-time monitoring.

Log correlation is about constructing rules that look for sequences and patterns in log events that are not visible in the individual log sources. They describe analysis patterns that would require human. interpretation otherwise, tied together by logical operators.

Information or data on your computer could be lost, if: The hard drive in your computer fails The data on your computer is corrupted for a variety of reasons Your computer is lost or stolen Your computer is in a fire or other environmental event A virus infects your computer and deletes or corrupts your files

Steps to perform log analysis: 1. Instrument and collect - install a collector to collect data from any part of your stack. 2. Centralize and index - integrate data from all log sources into a centralized platform to streamline the search and analysis process.

In signal processing, data compression, source coding, or bit-rate reduction involves encoding information using fewer bits than the original representation. Compression can be either lossy or lossless. Lossless compression reduces bits by identifying and eliminating statistical redundancy.

Steps to perform log analysis: 1. Obtain and Integrate Test Case Data. Order Test Case Data. Setup and Maintenance of the Test Data Shop. 2. Benefits. Allows DBAs to quickly and easily identify, isolate and undo unwanted changes. 3. Features. Filters log records by various attributes such as table, database, plan, user, job name.