Access profiling and suggestions

Data Integrity Suite
Product
Spatial_Analytics
Data_Integration
Data_Enrichment
Data_Governance
Precisely_Data_Integrity_Suite
geo_addressing_1
Data_Observability
Data_Quality
dis_core_foundation
Services
Spatial Analytics
Data Integration
Data Enrichment
Data Governance
Geo Addressing
Data Observability
Data Quality
Core Foundation
ft:title
Data Integrity Suite
ft:locale
en-US
PublicationType
pt_product_guide
copyrightfirst
2000
copyrightlast
2026

View data profiling of Pipeline sample data. The data profiling is represented by bar charts that visually summarize the data integrity and provide detailed profiling information for each column. Additionally, Pipeline Suggestions provide transformations that can be applied to the data, with the ability to preview and save the changes.

On the Pipeline page, the vertical frequency bar chart in each column visually profiles data, while different colors on the horizontal bar indicate valid, invalid or outlier, and null/blank values. These charts help assess data integrity for any column of sample data.

  • The vertical bar chart shows cardinality (strings, Booleans) or a histogram (other types). Hover over a vertical bar to see the value or range and count it represents.
  • The horizontal bar shows counts, valid (green), invalid/outlier (red), and null (gray). Hover over any section to see counts for valid, invalid/outlier, or null values.

To view detailed profiling information, click in the chart area on a column or use the Profiling button on the right bar to open the Profiling panel. This panel displays:

  • Sample summary: Overall statistics for the column.
  • Sample quality: Valid, distinct, invalid/outliers, nulls/blanks.
  • Sample: Frequency chart of values.
  • Top values: Frequency chart of largest values.
  • Bottom values: Frequency chart of smallest values.
  • Statistics: Detailed statistics for the column data.
For descriptions of these sections, see Profiling panel. Vertical bars show frequency for values, and colored sections of the horizontal bar show frequencies of valid, invalid/outlier, or null values.
  • To view the value and frequency in the table, hover over a vertical bar.
  • To view counts for valid, invalid/outlier, or null values, hover over a colored section of the horizontal bar.
    • Green: valid values
    • Red: invalid or outlier values
    • Gray: null values
  • To view detailed profiling information, click the profiling button on the right toolbar or the chart area of a column. This expands the Profiling panel to show sample quality, top values, bottom values, invalids, and statistics for a column.

Use suggestions to identify and add steps to pipeline

Pipeline Suggestions show transformations that apply to semantic types for entities and column in the currently displayed dataset sample data.

You can click any suggested step on the Suggestions panel to open the configuration pane for the step. The step settings when the configuration panel opens are populated by the associated column in the sample dataset. After you add a step to the pipeline it no longer appears in the Suggestions list. Subsequently, you can click the Suggestions button to reopen the Suggestions panel and view steps that may still be applied to the pipeline. The list may include additional suggestions that were not previously in the list.

  1. On the right toolbar, click the Suggestions button. This expands the Suggestions panel. The panel initially feature transformations that apply to the currently selected column or entity.
  2. You can click a column heading or entity bar to highlight Suggestions for the column or entity.
  3. Click a suggested transformation that you want to apply to the data. This expands the configuration panel for the transformation and populates options to transform data in selected columns.
  4. Review and if necessary edit settings for the transformation.
  5. Optional: You can click the Preview button view the outcome of the new step in the sample data.
  6. Click the Save button.

Profiling panel

The profiling panel provides summary and detail profiling information about a sample data column in a Data Quality pipeline. This panel is expanded when you click either the profiling button on the right toolbar or the profiling charts in any column heading in a Data Quality pipeline sample data table.

Sample summary

  • Sample row count: Shows the number of rows for the profiled column of sample data.
  • Base type: Shows the base type for the profiled column of sample data.
  • Semantic type: Shows the semantic type for the profiled column of sample data.
  • Type confidence: The confidence level (between 0 and 100) for the type determinations.

Sample quality

  • Valid: Shows the number of valid values in the selected sample data column.
  • Distinct: Shows the number of distinct values in the selected sample data column.
  • Invalid/Outliers: Shows the number of values in the sample data that do not conform to the semantic or base type. This count also includes outlier values in the selected sample data column.
  • Null/Blank: Shows the number of null or blank values in the selected sample data column.

Invalids

Shows frequencies and percentages for invalid values in the sample.

Sample distribution

A frequency bar chart in which the length of each bar corresponds to the frequency of each value in the sample data. Hover over a bar in the chart to view the frequency and value represented by the bar. This bar chart is the same chart that is displayed at the top of the selected column. The number of distinct values are displayed under the chart. You can click Show more if there are more values than are initially visible.

  • Top values: Shows the frequency and percentage for the largest values in the selected sample data column. You can click Show more if there are more values than are initially visible.
  • Bottom values: Shows the frequency and percentage for the smallest values in the selected sample data column. You can click Show more if there are more values than are initially visible.
  • Statistics: This content provides a detailed overview of various statistical metrics used to analyze and describe the characteristics of data within a selected sample data column.
    • Null count: Shows the number of null values in the selected sample data column.
    • Blank count: Shows the number of blank values in the selected sample data column.
    • Minimum value: Shows the minimum value in the selected sample data column.
    • Maximum value: Shows the maximum value in the selected sample data column.
    • Minimum length: Shows the minim number of characters for any value in the selected sample data column.
    • Maximum length: Shows the maximum number of characters for any value in the selected sample data column.
    • Multiline: Shows whether multiple lines appear in values in the selected sample data column.
    • Leading whitespace: Shows whether values have leading white space characters in the selected sample data column.
    • Trailing whitespace: Shows whether values have trailing white space characters in the selected sample data column.