Advanced Snapshotting Use Cases in Einstein Analytics - Best Practices and Tips

DataDreamin September 19th, 2020.

Advanced Snapshotting Use Cases in Einstein Analytics - Best Practices and Tips by Robert Anderson & Gene James

Einstein Analytics implementations often require snapshotting to capture and analyze changes in data over time.

Though the out of the box Snapshot Analytics app is a great starting point, though it lacks some complexity that a lot of users require. We’ll go over the basics of the app, and cover important considerations for snapshotting use cases, including:
- Snapshot frequency and retention logic
- Lookups (at time of snapshot vs most recent values)
- Development and migration strategies
- Data grain
- We’ll also go over a few common examples, including:
- Pipeline Trending and Change waterfall analysis
- Adding snapshots to your existing datasets for simple trending.

Видео Advanced Snapshotting Use Cases in Einstein Analytics - Best Practices and Tips канала CRM Analytics (formerly Tableau CRM) Data Tribe