Purpose - 
       after this course you will be able to…
  • Describe why Data Quality matters
  • Define what is data quality
  • Show how Data Quality fits into the Data Life Cycle
  • Explain the measures of data quality
  • Describe the general data quality process
  • Demonstrate a knowledge of how to measure data quality
          Data Quality
  • Data: A representation of facts, which when put 
   into context becomes information that is used to 
   draw  a conclusion or make a decision.
  • The only people who DO NOT need to worry about 
   data quality are those who neither create nor use 
   data. 
      Data Life Cycle - Evaluate and QA/QC
                      PLAN                • The Evaluate Phase of the 
                                            BLM Data Life Cycle is where 
        ARCHIVE
                                ACQUIRE     numerous data evaluation 
                                            factors are addressed
                    QA/QC
                                          • The QA/QC location in the 
        EVALUATE                            middle shows that data 
                                MAINTAIN
                                            quality should be addressed 
                    ACCESS                  throughout the entire life 
                                            cycle
       What is Data Quality?
  • BLM has defined data quality as “fitness for the 
   intended use”
   Data quality may be considered as 
   the sum of all data characteristics 
   that determine how useful the 
   data is in performing specific 
   business processes. 
      Data Quality Dimensions
  •  Validity
  •  Non-Duplication
  •  Completeness
  •  Relationship Validity
  •  Consistency 
  •  Concurrency