Looking at the Quality of Data and Information Chapter 6 Pages Chapter 6 Pages Business decisions are only as good as the. You never want to find yourself using technology to help you make.
BUSINESS DRIVEN MIS – DETERMINING INFORMATION QUALITY ISSUES Information Revolution - Video v=-4CV05HyAbM v=-4CV05HyAbM
Common Characteristics of High- Quality Information systems: faster, more effective decisions, smaller inventories, easier to track performance
Low-Quality Information Primary Sources of Low-Quality Information 1.C intentionally data to protect privacy. 2.Different entry standards and formats 3.Operators enter abbreviated or erroneous data 4.Third party and external information contains inconsistencies, inaccuracies and errors
At least 14 examples of Low-Quality Information Customer ID Customer First Name Customer Last Name AddressCityStateZipPhone 1771LarryShimk143 S.DenverNY CarolineShimk143 N. West St.BuffaloNY ShimkCaroline143 N. West St.BuffaloNY HeatherSchwiter55 N. W. S. MissLaGrangeGA DebbieFernandezS. Main St.DenverCO DebbieFernandezS. Main St.DenverCO Justin 34 Kerry Rd.LittletonCO Pam 66 S. CarltonNorth GlenCO
Potential business effects of using low-quality information 1.Inability to accurately customers. 2.Difficulty valuable customers and/or difficulty strong 3.Inability to identify selling opportunities. 4.Marketing to nonexistent customers. 5.Difficulty tracking revenue. 6.Might order too much inventory from a supplier based on inaccurate orders. 7.Instead of sending an expensive promotional item to your best customers, it High-quality information can the chances of, which can directly impact an organization's bottom line
Maintaining Quality Information in a Data Warehouse is extremely important Pulled from many different sources, some of which are external to your organization. Information may be inconsistent or just plain wrong. Information or is a process that weeds out and inconsistent, incomplete or incorrect information. Cleansing uses specialized software tools to and consolidate information in a data warehouse.
Accurate vs Complete Information Is it right/correct VS Is it all there/no blanks? Perfect Information?? 100% accurate and complete = –Birthdate 2/31/2014 (complete but not accurate) –Address containing Manhattan, KS, but no zip code (accurate, but not complete) –Some companies are willing to go as low as 20% complete to find BI –Few organizations go below 50% accurate – info is useless if not accurate. –Perfect information vs cost and time –Most organizations determine a percentage high enough such as 85 percent accurate and 65 percent complete