Hi <!channel>! announcement A new version of Elementary is out (CLI

0.7.7

, dbt package

0.7.5

)! elementary What's New? elementary • Seasonality and Anomaly direction fbwow ◦ On this release we are introducing 2 new anomaly detection tests configurations. The goal is to improve the accuracy and unlock more detection use cases. 🎯💪 ◦ We prepared a short video to explain 📽️👇 ◦

seasonality: day_of_week

📆 ▪︎ If enabled, daily values will be compared only to the same week day previous values. ▪︎ This configuration would improve accuracy and detection of datasets that have different volume and metrics on weekends and different weekdays. ◦

anomaly_direction: [ both | spike | drop ]

↗️↘️ ▪︎ By default, elementary alerts on both spikes and drops of a metric. Using this configuration, you can limit anomaly tests to alert only on the wanted direction. ▪︎ For example - If you want volume anomalies to fail only on drop in row count, and not on a spike, just add

anomaly_direction: drop

to the test config. • on-run-end performance improvements ⏳ ◦ We fixed problems in artifacts caching, and implemented an incremental upload. This means that upon a change to models / tests / sources - elementary will now only update the changed resources. ◦ This should improve the performance of the hooks, and we have additional ideas and planned tasks around further improvements. ◦ Special thanks to @panapost for helping with this effort 🤩 elementary Bug Fixes and Other Changes elementary • Added support to unsupported time buckets on Bigquery (week, month), and made buckets full and consistent to calendar times - Thank you @Kenneth Roos and @Julian Schulte for reporting! • Added log rotation to

edr.log

to prevent large log files that won't open - Thank you @Stéphane Burwash and @Grant Mehrer for reporting! • Fixed elementary tests custom names issue - Thank you @Fabien Traventhal for reporting! • Fixed subscribers parsing issue - Thank you @Muthu for reporting! • Added

target-path

to upload_source_freshness - Requested by @Ange Melhuish! 🎁 Helped with this release? Did you claim your swag yet? Join the #C050YB1B12M channel 🎁 As always - We are looking forward to talk to you here on Slack (#C02CTC89LAX, #C03LPJ5EYU9 or DM to the elementary team), and happy to schedule calls!

Seasonality looks very cool! A situation we have in our SAAS business is that at some point we used to have a 1st of the month rule for invoice dates/billing periods, which means on the 1st of the month every month we’re getting volume alerts across a number of different data sources (mainly invoices, but due to integrated systems it impacts a surprising range of source tables). It would be nice if we could get seasonality at month level too.

Video report very good!

Thank you @pei0804 ! And thanks @Ian McLaren for sharing the use case! Do you think it would be preferable in thay case to have a monthly seasonality, or the ability to exclude dates? (Ignore all the 1st of the month)

Excluding the single date would probably work. Thinking about months a little bit it can get quite complex (different month lengths, different days etc), maybe true seasonality wouldn't apply as much...