In this video, review additional details to consider for the services in the customer analytics architecture.
- [Instructor] In this video, … I will discuss some best practices … for executing on the architecture we laid out … for this customer analytics use case. … We start off with building connectors. … Whenever a cloud REST API is provided, … either by GCP or Salesforce or Twitter, … they all have bandwidth and data load-related pricing. … They also have rate limits, where the REST APIs stop working … after a specific threshold is reached. … So understand, model, and measure bandwidth … and data usage for your application. … Create batch sizes that minimize costs and maximize value. … Ensure that you will not violate the set rate limits, … or your application can abort … or start lagging in its data uploads. … While there is eagerness to keep these data uploads … as real time as possible, … ask yourself if they are really required, … given the cost impact it has. … Batch sizes and batch processing usually are sufficient … for historical data archival and processing. … Next, let's look at Dataflow best practices. …
- Benefits and shortcomings of GCP
- Enterprise and multicloud integrations
- Comparing GCP technology options
- Outlining solutions for various problems
- Analyzing use cases and best fits
Skill Level Intermediate
1. Architecting in GCP
2. UC1: Cloud Data Archive
3. UC2: Log Analytics
4. UC3: Customer Analytics
5. UC4: Real-Time Mobile Couponing
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