diff --git a/docsrc/source/pages/getting_started/overview.rst b/docsrc/source/pages/getting_started/overview.rst index 26baa6070..63454326c 100644 --- a/docsrc/source/pages/getting_started/overview.rst +++ b/docsrc/source/pages/getting_started/overview.rst @@ -35,11 +35,6 @@ Overview The package outputs a simple and digested analysis of a dataset, including **time-series** and **text**. -.. NOTE:: - **Looking for a scalable solution that can fully integrate with your database systems?** - Leverage `YData Fabric Data Catalog `_ to connect to different databases and storages (Oracle, snowflake, PostGreSQL, GCS, S3, etc.), - and leverage an interactive and guided profiling experience in Fabric. Check out the `Community Version `_. - Key features ------------ - **Type inference**: automatic detection of columns' data types (*Categorical*, *Numerical*, *Date*, etc.) @@ -58,4 +53,9 @@ The report contains three additional sections: * **Alerts**: a comprehensive and automatic list of potential data quality issues (high correlation, imbalance, skewness, uniformity, zeros, missing values, constant values, between others) * **Reproduction**: technical details about the analysis (time, version and configuration) -The package can be used via code but also directly as a CLI utility. The generated interactive report can be consumed and shared as regular HTML or embedded in an interactive way inside Jupyter Notebooks. \ No newline at end of file +The package can be used via code but also directly as a CLI utility. The generated interactive report can be consumed and shared as regular HTML or embedded in an interactive way inside Jupyter Notebooks. + +.. NOTE:: + **Looking for a scalable solution that can fully integrate with your database systems?** + Leverage `YData Fabric Data Catalog `_ to connect to different databases and storages (Oracle, snowflake, PostGreSQL, GCS, S3, etc.), + and leverage an interactive and guided profiling experience in Fabric. Check out the `Community Version `_.