MIS5101: Business Intelligence Outcomes Measurement and Data Quality

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Presentation transcript:

MIS5101: Business Intelligence Outcomes Measurement and Data Quality

Data Quality The degree to which the data reflects the actual environment. Do we have the right data? Is the collection process reliable? Is the data accurate?

? Finding the right data Key Performance Indicator Consistent with goals of the analysis Measures what it claims to measure Include analysts during data selection Key Performance Indicator ? Adapted from http://www2.ed.gov/about/offices/list/os/technology/plan/2004/ site/docs_and_pdf/Data_Quality_Audits_from_ESP_Solutions_Group.pdf

What do these have in common? KPI Criteria: SMART Specific purpose for the business Measurable Achievable by the organization Relevant to success Time-phased What do these have in common?

Ensuring accuracy How do these impact the balance with access? Know where the data comes from Manual verification through sampling Use of knowledge experts Verify calculations for derived measures How do these impact the balance with access? Adapted from http://www2.ed.gov/about/offices/list/os/technology/plan/2004/ site/docs_and_pdf/Data_Quality_Audits_from_ESP_Solutions_Group.pdf

Reliability of the collection process Build fault tolerance into the process Check logs (if you can) Periodically run reports and verify results Keep up with (and communicate) changes What can you do when you find an error after collection has begun? Adapted from http://www2.ed.gov/about/offices/list/os/technology/plan/2004/ site/docs_and_pdf/Data_Quality_Audits_from_ESP_Solutions_Group.pdf

Evaluating System Usability What are some good KPIs? Why are they good? Why doesn’t everyone rigorously measure usability? What are the benefits of compound metrics? Are goal-based comparisons better than expert-based comparisons?