Data Analysis
Data analysis in cloud engineering involves collecting and examining quantitative data to gain insights. This can include data from system monitoring, usage patterns, resource consumption, cost metrics, security logs, or performance measurements.
By systematically analyzing this data, cloud engineers can make informed decisions rather than relying on gut feelings. Data analysis provides insights into patterns or problems that are not visible to the naked eye. In a broader sense, data analysis enables you to quantitatively validate architectural choices: measuring effects. It thus contributes to an 'evidence-based' improvement cycle for your cloud infrastructure and services.
Starting Points
Key Points
- You think in advance about which metrics you want to collect and how to collect them efficiently and securely, implementing appropriate logging and monitoring solutions.
- You demonstrate understanding of data quality. You check the dataset for completeness, reliability, and biases, and justify the analysis method used.
- You present concrete findings from the data with visualizations (graphs, tables) and draw conclusions that link to architectural improvements or operational optimizations for your cloud environment.