IVI Framework Viewer

Representative POMs are described for Data Cleansing at each level of maturity.

2Basic

• Practice

  Correct any obvious errors or replace/insert missing values.

  Outcome

  Data cleansing focuses on ‘fix and repair’.

  Metrics

  • Number of errors corrected per data set.
  • Number of missing values inserted per data set.

3Intermediate

• Practice

  Carry out a deep clean of the data, eliminating all erroneous data records and elements.

  Outcome

  Data cleansing focuses on root cause prevention.

  Metric

  Percentage of erroneous data elements and records removed per data set.

4Advanced

• Practice

  Automate the deep clean process and apply it to the complete data set(s) — for example by inputting missing data using statistical means or algorithms.

  Outcome

  Data cleansing focuses on automation.

  Metric

  Percentage automation of the data cleansing process per data set.

5Optimized

• Practice

  Establish a continuous control and feedback mechanism whereby any inaccurate information is automatically reported and corrected.

  Outcome

  There is a very high level of trust in the data provided.

  Metric

  Percentage trust in the data sets after cleansing.