Job Results Page

In the Job Results page, you can explore the details of an executed job. In the Jobs page, click View Results next to the specific job.

Figure: Job Results page

  • Click View Dependencies to see the recipes and datasets on which the job depends.

  • Click Export Results to export the results. See Export Results Window.

Summary Information

The upper section of the Job Results window provides summary information on the job that was executed. In particular, you should pay attention to the mismatched values and missing values counts, which identify the percentage of values in the dataset that are affected by these issues.

NOTE: The computational cost of generating exact visual profiling measurements on large datasets in interactive visual profiles severely impacts performance. As a result, visual profiles across an entire dataset represent statistically significant approximations.

NOTE: Cloud Dataprep by TRIFACTA® treats null values as missing values. Imported values that are null are generated as missing values in job results (represented in the gray bar). See Manage Null Values.

  • Environment: Location where the job was executed, as specified when the job was started. See Jobs Page.
  • Dataset: Click the name of the dataset to review details. See Dataset Details Page.
  • Duration: Indicates the length of time required to execute the job.

Column break-downs

In the lower section, you can explore details of the transformations on individual columns. Use this area to explore mismatched or missing data elements in individual columns. Then, you can add the selected rows back into the Transformer Page for further refinement on the recipe.

Depending on the data type of the column, varying information is displayed. For more information, see Column Statistics Reference.

Tip: You should review the type information for each column, which is indicated by the icon to the left of the column. For example, in the above image, the type of business_id is identified as a number, when it is probably more useful to treat these identifiers as string values.

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Google Cloud Dataprep Documentation