The Varigence Blog
Tag - BimlFlex
BimlFlex ensures that businesses can tailor their data solutions precisely to their needs, ensuring efficiency and adaptability in an ever-evolving digital landscape
BimlFlex's next version will include Databricks automation support, extending to all data pipeline layers, and has received positive feedback from customers. This development can save time and costs, improve data quality, and provide robust data insights for businesses. An upcoming blog post will provide instructions on configuring and implementing a fully automated Databricks solution.
Automating Change Data Capture on Azure Data Factory: Streamline Your Data Integration with BimlFlex
Discover how BimlFlex, a metadata-driven framework, can help you automate Change Data Capture (CDC) on Azure Data Factory (ADF), creating efficient, scalable, and reusable solutions with significantly less manual effort. Learn how to overcome common CDC implementation challenges, including full load or initial load and restarting CDC, and improve the overall efficiency of your data integration process.
Varigence has moved fast to adopt the new Script Activity feature in Azure Data Factory.
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.
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.
The new BimlFlex 2022 R1 is available.
This BimlFlex webinar looks at Multi-Active Satellites in Data Vault
In this webinar we look at how to easy it is to use BimlFlex to bring data into a Snowflake Data Warehouse.
This BimlFlex webinar looks at Dimensional Modelling and the Dimensional data warehouse.
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.
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.