Google Dev Ops Engineer Intermediate - Data Analytics скачать в хорошем качестве

Google Dev Ops Engineer Intermediate - Data Analytics

Ready to move beyond the basics? In this Solution Workshop, we break down the architectural logic behind two intermediate Google Cloud scenarios. We explore why specific workflows are chosen for technical logs and financial tracking, and how BigQuery sits at the heart of it all. Workshop Highlights: • Scenario 1: From Logs to Dashboards ◦ The Workflow: We move VM logs from Cloud Operations Suite to BigQuery, then visualise them in Looker Studio. ◦ The "Why": We avoid Google Sheets because BigQuery is designed for the "heavy lifting" required for quarterly data aggregation. We choose Looker Studio over custom-built apps because it offers an easier, native way to provide interactive, real-time dashboards for stakeholders. • Scenario 2: Precision Cost Tracking ◦ The Workflow: To track costs for specific systems, we apply Labels to instances and configure a BigQuery billing export. ◦ The "Why": While you could name VMs or look at basic breakdowns, Labels are the technical standard for distinguishing costs in high-level billing reports. This method allows you to query exact spending per system with high accuracy. Expert Insight: Notice the pattern? Whether you are managing technical performance or financial data, BigQuery acts as your central hub. Its versatility makes it the most powerful tool in your data analytics arsenal. Subscribe to master the architectural logic needed for your professional certification! #GCP #BigQuery #LookerStudio #CloudArchitecture #DevOps #CloudBilling #DataAnalytics #GoogleCloudPlatform