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@ -95,7 +95,7 @@ In addition to the initial ingestion of data, you will typically need to setup a
### Artifacts
The following are the deliverables in this stage.
* **[Data Quality Report](https://github.com/Azure/Azure-TDSP-ProjectTemplate/blob/master/Docs/DataReport/DataSummaryReport.md)** : This report contains data summaries, relationships between each attribute and target, variable ranking etc. The [IDEAR](https://github.com/Azure/Azure-TDSP-Utilities/blob/master/DataScienceUtilities/DataReport-Utils) tool provided as part of TDSP can help with the quickly generating this report on any tabular dataset like a CSV or relational table.
* **[Data Quality Report](https://github.com/Azure/Azure-TDSP-ProjectTemplate/blob/master/Docs/Data_Report/DataSummaryReport.md)** : This report contains data summaries, relationships between each attribute and target, variable ranking etc. The [IDEAR](https://github.com/Azure/Azure-TDSP-Utilities/blob/master/DataScienceUtilities/DataReport-Utils) tool provided as part of TDSP can help with the quickly generating this report on any tabular dataset like a CSV or relational table.
* Solution Architecture: This can be a diagram and/or description of your data pipeline used to run scoring or predictions on new data once you have built a model. It will also contain the pipeline to retrain your model based on new data. The document is stored in this [directory](https://github.com/Azure/Azure-TDSP-ProjectTemplate/tree/master/Docs/Project) when using the TDSP directory structure template.