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.