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Data Quality Overview
   Alex Meadows
     1/28/2013
Data Quality Facts
●    Cost of poor data quality in US - $600 Billion
●    Poor Data/Lack of visibility cited as #1 reason for
     project cost overruns
●    Poor data quality costs the US Economy $3.1 Trillion a
     year
●    Implementing data quality best practices boosts
     revenue by 66%
●    Median Fortune 1000 company could increase
     revenue by $2.01 Billion if they improved usability of
     data by 10%

    Source: http://www.webmastat.com/blog/2012/09/07/7-facts-about-data-quality/
What is Data Quality?




Measuring data to determine if it is
        “fit for purpose”
Fit For Purpose?
●   “Bad” data is a myth!
●   Two Questions
       ●   What is the data used for?
       ●   What can be measured to make sure it meets
            the need?
●   Application use vs. Reporting/Analysis
Data Quality Dimensions
●   Consistency                          ●   Accuracy
●   Correctness                          ●   Objectivity
●   Timeliness                           ●   Conciseness
●   Precision                            ●   Usefulness
●   Unamiguous                           ●   Usability
●   Completeness                         ●   Relevance
●   Reliability                          ●   Amount of data


        Source: Data Quality Fundamentals, The Data Warehousing Institute
Measuring Data Quality
●   Profiling – understanding metadata
       ●   Point in time shows what data looks like now
       ●   Automating shows trends
               –   Alert to new/potential issues as they happen
               –   Potentially fix issues in near real time
               –   Six Sigma Principals
Statistical Process Control
●   Automated inspection
●   Visibly shows process deviation
Data Profiling Analysis
●   Duplication           ●   Character Set
●   Pattern matching      ●   Reference Data
●   Boolean/String/Numb       Matching
    er                    ●   Value Distribution
●   Date Gap              ●   Inter-Data Set
●   Date/time                 Comparisons
●   Day of Week
Master Data Management
●   Create a gold standard for data
●   Distribute data so that all sources are uniform
       ●   Names
       ●   Addresses
       ●   Phone Numbers
       ●   Products
●   Can hook into third party sources
Data Governance Program
●   Central authority for data quality control
●   Applies information collected from data
    profiling, MDM, etc. Uniformly across the
    business
●   Communication channels between business
    and IT groups
Questions?

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Data quality overview

  • 1. Data Quality Overview Alex Meadows 1/28/2013
  • 2. Data Quality Facts ● Cost of poor data quality in US - $600 Billion ● Poor Data/Lack of visibility cited as #1 reason for project cost overruns ● Poor data quality costs the US Economy $3.1 Trillion a year ● Implementing data quality best practices boosts revenue by 66% ● Median Fortune 1000 company could increase revenue by $2.01 Billion if they improved usability of data by 10% Source: http://www.webmastat.com/blog/2012/09/07/7-facts-about-data-quality/
  • 3. What is Data Quality? Measuring data to determine if it is “fit for purpose”
  • 4. Fit For Purpose? ● “Bad” data is a myth! ● Two Questions ● What is the data used for? ● What can be measured to make sure it meets the need? ● Application use vs. Reporting/Analysis
  • 5. Data Quality Dimensions ● Consistency ● Accuracy ● Correctness ● Objectivity ● Timeliness ● Conciseness ● Precision ● Usefulness ● Unamiguous ● Usability ● Completeness ● Relevance ● Reliability ● Amount of data Source: Data Quality Fundamentals, The Data Warehousing Institute
  • 6. Measuring Data Quality ● Profiling – understanding metadata ● Point in time shows what data looks like now ● Automating shows trends – Alert to new/potential issues as they happen – Potentially fix issues in near real time – Six Sigma Principals
  • 7. Statistical Process Control ● Automated inspection ● Visibly shows process deviation
  • 8. Data Profiling Analysis ● Duplication ● Character Set ● Pattern matching ● Reference Data ● Boolean/String/Numb Matching er ● Value Distribution ● Date Gap ● Inter-Data Set ● Date/time Comparisons ● Day of Week
  • 9. Master Data Management ● Create a gold standard for data ● Distribute data so that all sources are uniform ● Names ● Addresses ● Phone Numbers ● Products ● Can hook into third party sources
  • 10. Data Governance Program ● Central authority for data quality control ● Applies information collected from data profiling, MDM, etc. Uniformly across the business ● Communication channels between business and IT groups