The Varigence Blog

Tag - BimlFlex

Dev Diary - Embracing the new Azure Data Factory Script Activity

Written by Roelant Vos on 3.16.2022

Varigence has moved fast to adopt the new Script Activity feature in Azure Data Factory.

Dev Diary - Pushing down data extraction logic to the operational system environment

Written by Roelant Vos on 3.6.2022

For the upcoming 2022 R2 release, we have added a pushdown extraction feature which in some scenarios optimizes the integration of data into the data solution.

Upcoming Business Modeling webinars

Written by Roelant Vos on 2.17.2022

We believe Business Modeling is a feature that is core to delivering lasting and manageable data solutions. To promote, explain and discuss this feature -and the planned improvements- we have organized a number of webinars.

BimlFlex 2022 R1 is available!

Written by Roelant Vos on 12.21.2021

The new BimlFlex 2022 R1 is available.

BimlFlex 2018 - Multi-Active Satellites in Data Vault

Written by Stefan Johansson on 9.21.2018

This BimlFlex webinar looks at Multi-Active Satellites in Data Vault

BimlFlex now support Snowflake Source to Staging

Written by Peter Avenant on 9.19.2018

In this webinar we look at how to easy it is to use BimlFlex to bring data into a Snowflake Data Warehouse.

BimlFlex 2018 - Dimensions and Facts

Written by Stefan Johansson on 4.18.2018

This BimlFlex webinar looks at Dimensional Modelling and the Dimensional data warehouse.

BimlFlex 2018 - Data Vault End Dating

Written by Peter Avenant on 3.16.2018

In this webcast, we configure ETL and ELT templates running initial and delta loads. We look at the performance differences in both these approaches with and without end dating.

Azure Data Warehouse Automation with BimlFlex

Written by Peter Avenant on 7.18.2017

Leverage metadata-driven DWA and data transformation optimized specifically for all Azure Data Warehousing options. For one of our BimlFlex customers in Australia, we integrated data from a distributed network point of sale systems. The ability to extract, compress and prepare data at source was critical to delivering an optimized solution.

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