Working with the Sample-patients Dataset

The Sample-patients dataset is used to show how you can analyze, validate, transform, and cleanse, and deliver data using various methods.

The Sample-patients dataset contains a set of artificial patients data. By default, a project named project 1 is created from this dataset. On the home page, click the project name to go to the project data page. The patients data is stored in the following columns:
  • PATNO: Patient number.
  • GENDER: Gender.
  • VISIT: Date of visit.
  • HR: Heart rate.
  • SBP: Systolic blood pressure.
  • DBP: Diastolic blood pressure.
  • DX: Diagnosis code.
  • AE: Adverse event.
This example dataset is used to show how you can analyze, validate, transform, cleanse, and deliver data:
  • Analyzing Data

    Profile data, facet data, check data dependency, and chart data.

  • Validating Data

    Validate data by data types, and analyze and export validating results.

  • Transforming Data

    Transform data into a uniform data format.

  • Cleansing Data

    Trim white space, remove empty rows, and remove or modify invalid data.

  • Delivering Data

    A complete procedure: load, analyze, transform, cleanse, and deliver data.

  • Analyzing Data
    You can analyze data by profiling data, faceting data, checking data dependency, and charting data.
  • Validating Data
    Use the data validation function to filter out invalid data. After validation, you can analyze and export the validating results.
  • Transforming Data
    Use the data transforming function to transform column data to a specified format.
  • Cleansing Data
    To cleanse your data, you can trim white spaces, remove empty rows, and remove and modify invalid values.
  • Delivering Data
    A complete procedure of delivering data involves loading data, analyzing data, transforming data, cleansing data, and exporting data.