October and November Release Roundup
Welcome back to our new monthly Release Roundup. In this edition, we bring a bumper update with a full breakdown of our releases from October and November.
✨Top features this month
Seamless Cross-Platform Identity Stitching with Snowplow’s new Unified Digital Model
Our new Unified Digital Model is designed to unify journeys across web and mobile with cross-platform tracking and deterministic identity resolution out-of-the-box. With disjointed customer journeys an unavoidable reality for data and marketing teams, the need to accurately identify and stitch the customer journey plays an essential role in every downstream application.
The model removes the need for complex modeling and provides a single view of customers in your warehouse or lake for downstream applications, aggregating raw web and mobile events into a set of derived tables – users, sessions and views.
The new Unified Digital Model supersedes our existing web and mobile models and is designed to work even if you are using web only or mobile only trackers, with the flexibility to add additional platforms when required.
This model will be released under our new Snowplow Personal and Academic License and is only available as part of our Data Model Pack. Snowplow customers who have purchased BDP can use this model at no additional charge.
Easily create and evolve schemas with the Data Structure Builder
Our existing customers will be familiar with our Data Structures code editor and APIs for managing schema creation and evolution. Our new Data Structures Builder has been designed to make schema creation and evolution easier. Previously users required in-depth knowledge of JSON schema and versioning.
Our new Data Structures Builder provides a new guided experience to help users easily create and evolve schemas without needing to rely on a code editor.
With our new Data Structures Builder you are taken step by step to build out your event including event name, type, description and create the properties that form your schema.
Versioning your schema is now easier than ever, with Snowplow automatically determining the level of versioning required based on the changes you have made and the destination that you are loading your data to.
Combining a Schema DDLand a standard set of JSON schema rules, the interface will automatically determine if the changes are major or minor and update versioning automatically avoiding any negative impact on the downstream destinations.
Please see our documentation for further information.
Snowplow is now available on Databricks Partner Connect
With Snowplow available on Databricks Partner Connect, joint customers can now easily set up a Snowplow pipeline from within the UI of their lakehouse account. This unlocks powerful new use cases like combining behavioral data with other data sources to power machine learning and AI applications on Databricks.
After validation and enrichment, Snowplow loads the behavioral data into storage targets of your choice like Databricks Delta Lake. This gives data teams a clean foundation for analytics, machine learning, and AI use cases to drive customer growth.
Easily build compelling use cases like churn prediction, next best offer, customer segmentation, attribution modeling, and more using notebooks, SQL, and machine learning on an optimized analytics platform.
Find out more about Snowplow on Databricks Partner Connect in our dedicated release post.
Introducing Snowplow’s new Data Modeling Pack for open source users
Snowplow’s new Data Modeling Pack provides open source users with access to Snowplow’s existing data models and our brand new data models, the Unified Data Model, an updated Media Model and Video and Media Analytics Accelerator.
As Snowplow continues to evolve, our future roadmap will focus on helping teams extract business value from the Snowplow data they create – aka. the “last mile”. This includes building solutions that run on our BDP platform, like Snowplow Digital Analytics.
Future versions of our open source data models code that enable organizations to unlock business value will be made available under our Personal & Academic License (SPAL). The SPAL license allows use for non-commercial purposes, but these components can be licensed under our new Data Modeling Pack. Full details of the license can be found in our documentation.
If you are a Snowplow customer who has purchased BDP Enterprise or BDP Cloud, your usage of the data model pack is governed by your existing commercial contract.
🆕 Other notable releases and updates
Visualize engagement in your videos and ads with Snowplow’s new Media Analytics Accelerator
Our new accelerator guides you through tracking, modeling and visualizing valuable insights across your media players. With the accelerator, you can visualize both engagement in content and advertising on your platform across a series of three dashboards. Including a high-level view of media and video performance, drill down into individual media with impressions and advertising performance with key metrics including ad audience retention.
The accelerator release also comes alongside an update to our media models (v0.6) designed to provide greater measurement of content and advertising performance. The release included two new modeled tables for measuring ad performance, improved metric tracking for time played, average playback, total content watched and buffering time. See a full breakdown in our dedicated release blog.
You can see an interactive version of the Tableau dashboards in the accelerator docs and be sure to read our full release blog for more information. If you haven’t quite got your Snowplow pipeline set up yet, you can upload our sample event data to try out modeling and exploring the metrics available.
Our latest model will be released under our new Personal and Academic license and only available as part of our Data Model Pack. Snowplow customers who have purchased BDP can use this model at no additional charge.
See event volumes directly in Console with our new Observability Dashboard
With our new “Overview” and “Collection Volumes” page in the console, you can see a complete breakdown of your pipeline, including the number of events collected by source, events validated and enriched, including the number of bad events, and the number of events by destination. A powerful tool that gives you an overview of your event volumes across your Snowlow pipeline. Other features include;
- Support for all clouds, warehouses, lakes and Snowbridge destinations.
- Configurable timeframe options, including 7, 14 and 30 days
- Overview of the number of validated and enriched events
- View source information, including platform, tracker version, events captured and more
- See a detailed breakdown of events grouped by platform, tracker or event ID.
🔧 Fixes and performance improvements
- Java Tracker 1.0.1
- Snowplow Android and iOS Trackers 5.6.0
- Snowplow React Native Tracker 2.0.0
- .NET Analytics SDK 0.3.0