As an example of our data sources I can mention, Relational Databases on AWS running SQL SERVER, we have some input from S3 (text files) and of course, some excel files.
Training on Matillion and getting the development team on-board was quite a challenge. Would require immense experience to explore the core functionality of Matillion. Matillion was running …
Took 1 month to make it useful in production, and 9 months in, I'm still learning features and quirks of Matillion.
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- Connect to traditional data sources (92)9.292%
- Testing and debugging (83)9.292%
- Simple transformations (93)9.090%
- Complex transformations (92)7.979%
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Matillion is data transformation for cloud data warehouses. According to the vendor, only Matillion is purpose-built for Amazon Redshift, Snowflake, and Google BigQuery enabling businesses to achieve new levels of simplicity, speed, scale, and savings.
Users can develop custom Transformation jobs by combining Filters, Joins, Aggregates, Calculators, Ranks, as well as more complex transformations such as Rankings, window calculations, and change-detection by dragging and dropping these onto a canvas GUI. Use Orchestration features to automate ETL workflows with scheduling, notifications and alerting, and control flow.
Once jobs are built, run them with component level validation and data sampling. For any custom or unique needs, Matillion also has Bash and Python Script components to give users extensibility and flexibility.
Shared Job templates, Dynamic and Grid variables, and Version control help development teams share resources across Matillion instance.
Enterprise customers gain additional auditing and permissions, automatic job documentation, data lineage and more. Learn more about enterprise features here.
Each product comes with a set of warehouse specific features to help users get the most out of the platform. Their Product Feature pages on matillion.com provides more information.
- Supported: Connect to traditional data sources
- Supported: Connecto to Big Data and NoSQL
- Supported: Simple transformations
- Supported: Complex transformations
- Supported: Business rules and workflow
- Supported: Collaboration
- Supported: Testing and debugging
|Deployment Types||Software as a Service (SaaS), Cloud, or Web-Based|
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