Analytics Blog

Meet the New Operators in Chorus 6.3

Alpine’s latest product release adds ten new operators, including the much-requested Python Execute operator. The rest fall into a two primary themes: (1) Data movement — copying between databases, moving to and from Excel, exporting to your Tableau server, and connecting to Hive. (2) Enhanced user experience in data analysis — new and improved ARIMA… Read more »

All About Deep Tech: Creating Scoring Engines with PFA

In recent blogs we have talked extensively about model operationalization and the support Chorus provides for the PFA (Portable Format for Analytics) standard. PFA provides a standardized way of representing analytical models, providing much needed model portability i.e. the ability to train a model on one data platform, serialize the model as PFA, and then… Read more »

All About Deep Tech: Model Operationalization

Model operationalization is a core component of effective data science, and is a key focus at Alpine Data. In previous blogs, I’ve written frequently about model ops, especially the support Chorus provides for exporting models using the PFA and PMML formats. However, what about scoring on data platforms that don’t yet provide PFA or PMML… Read more »

The Chorus Python SDK

We are excited to announce the 1.0 release of our open-source Python API package alpine! Available now, this package serves as a Python wrapper to some API endpoints in Alpine and includes functions that add useful functionality to Alpine. The library can be found at Feel free to fork; if you do something interesting… Read more »

Meet the New Operators in Chorus 6.2.2

The recent release of Chorus 6.2.2 brings five new ETL and Machine Learning operators to your analytics toolbox. These are quiet features that may not have caught your attention yet, but they make a big impact on the analytics functionality you have at your fingertips. Consider this blog post a highlight reel to welcome these… Read more »