Oracle DV introduces Data Flows that allow you to prepare and enrich your dataset by applying ongoing updates and improving the accuracy of your analysis.
Within a data flow, you can define transformations in a business user friendly visual interface by simple click and drag/drop operations. These transformations can however be extended to any level of complexity required by real life use cases.
Within your data flow, you can bring in one or more datasources of various types. For example, one datasource could be an excel file, joined to a table from a Spark database and further joined to an Oracle table. You can apply aggregate functions on your datasource to change the grain, apply filters, create new calculated metrics and so on.
The final output of this data flow can be saved as a specific dataset. This dataset will behave like any other DV dataset and can be refreshed at will. They can be exported as part of the DV projects as well.
This brief video gives a tour of this feature and its capabilities.
Within a data flow, you can define transformations in a business user friendly visual interface by simple click and drag/drop operations. These transformations can however be extended to any level of complexity required by real life use cases.
Within your data flow, you can bring in one or more datasources of various types. For example, one datasource could be an excel file, joined to a table from a Spark database and further joined to an Oracle table. You can apply aggregate functions on your datasource to change the grain, apply filters, create new calculated metrics and so on.
The final output of this data flow can be saved as a specific dataset. This dataset will behave like any other DV dataset and can be refreshed at will. They can be exported as part of the DV projects as well.
This brief video gives a tour of this feature and its capabilities.
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