پاورپوینت کامل Improving Data Quality:Why is it so difficult 84 اسلاید در PowerPoint

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پاورپوینت کامل Improving Data Quality:Why is it so difficult 84 اسلاید در PowerPoint

اسلاید ۴: What do we mean by data quality Data is correct Data is accurate Data is consistent Data is complete Data is integrated Data values follow the business rules Data corresponds to established domains Data is well defined and understood#1

اسلاید ۵: Symptoms of poor-quality data Do your programs abend with data exceptions Are your users confused about meaning of data Is some of your data is too stale for reporting Is your data being shared Is it sharable Are reports inconsistent Does it take your IT staff or the end users hours to reconcile inconsistent reports Does merging data often cause the system to fail Do beepers go off at night

اسلاید ۶: Dirty data categoriesDummy (default) values“Intelligent” dummy valuesMissing valuesMulti-purpose fieldsCryptic valuesFree-form address linesContradicting valuesViolation of business rulesReused primary keyNon-unique primary keyMissing data relationshipsInappropriate data relationshipsnot just data entryerrors

اسلاید ۷: Dummy (default) values Defaults for mandatory fields SSN 999-99-9999 Age 999 Zip 99999 Income 9,999,999.99 Business Impact:Inability to determine customer profiles Inability to determine customer demographics

اسلاید ۸: “Intelligent” dummy values Defaults with meaning SSN 888-88-8888Income 999,999.99Age 000Source Code‘FF’Non-resident alienEmployeeCorporate customer Account closed prior to 1991 Business Impact:Inability to write straight forward queries withoutknowing how to filter data

اسلاید ۹: Missing Values Operational systems do not always require informational or demographic dataGender EthnicityAgeIncomeReferring Source Business Impact:Inability to analyze marketing channels

اسلاید ۱۰: Multi-purpose fields Business Impact:Inability to judge product profitability ONE field explicitly has MANY meanings Which business unit enters the data At what time in history it was entered A value in one or more other fields Appraisal Amount redefined as Advertised Amount redefined as Sold Date Loan Type Code redefined as …25 redefines = 25 attributes !Not mutually exclusive ! Only the value of oneis known for each record !

اسلاید ۱۱: Cryptic values (1) Often found in “Kitchen Sink” fields Usually one byte (if not one bit) Highly cryptic (A, B, C, 1, 2, 3, …) Non-intelligent, non-intuitive codes Often not mutually exclusive Business Impact:Inability to empower end users to write their own queries

اسلاید ۱۲: Cryptic values (2)Need a CODE TRANSLATION booklet ONE field implicitly has MANY meaningsMaster_Cd{A, B, C, D, E, F, G, H, I}{A, B, C}{D, E, F} {G, H, I}Type of customerType of supplierRegional constraints

اسلاید ۱۳: Free-form address lines Unstructured text no discernable pattern cannot be parsedaddress-line-1:ROSENTHAL, LEVITZ, Aaddress-line-2:TTORNEYSaddress-line-3:10 MARKET, SAN FRANCaddress-line-4:ISCO, CA 95111Business Impact:Inability to perform market analysis

اسلاید ۱۴: Contradicting values Values in one field are inconsistent with values in another related field 1488 Flatbush Avenue New York, NY 75261 Type of real property:Single Family Residence Number of rental units:fourTexas ZipIncome propertyBusiness Impact:Inability to make reliable business decisions

اسلاید ۱۵: Violation of business rules Business Rule: Adjustable Rate Mortgages must haveMaximum Interest Rate ( Ceiling)Minimum Interest Rate ( Floor) Business Rule: A Ceiling is always higher than a Floorceiling-interest-rate: 8.25floor-interest-rate: 14.75switched Business Impact:Inability to calculate product profitability

اسلاید ۱۶: Reused primary keys Little history, if any, stored in operational files primary keys are customarily re-used may have a different rollup structureJanuary ‘۹۴: branch 501 = San Francisco Mainregion 1area SWAugust ‘۹۷: branch 501 = San Luis Obisporegion 2area SWBusiness Impact:Inability to evaluate organizational performance

اسلاید ۱۷: Non-unique primary keys Business Impact:Inability to determine customer relationshipsInability to analyze employee benefits trends Duplicate identification numbers Multiple customer numbers Customer Name Phone Number Cust. Number Philip K. Sherman 818.357.5166 960601 Philip K. Sherman 818.357.7711 960105 Philip K. Sherman818.357.8911 960003 Multiple employee numbers Employee Name Department Empl. Number July 1995: Bob Smith 213 (HR) 21304762 January 1996: Bob Smith 432 (SRV) 43218221 August 1999: Bob Smith 206 (MKT) 20684762

اسلاید ۱۸: Missing data relationships Data that should be related to other data in a dependent (parent-child) relationship Branch number 0765 does not exist in the BRANCH tableBranchEmployeeBusiness Impact:Inability to produce accurate rollupsBenefit

اسلاید ۱۹: Inappropriate data relationships Data that is inadvertently related, but should not be two entity types with the same key valuesPurchaser:Jackie Schmidt837221Seller:Robert Black837221Business Impact:Inability to determine customer or vendorrelationships

اسلاید ۲۰: Impact of erroneous data Extra time it takes to correct data problems Extra resources needed to correct data problems Time and effort required to re-run jobs that abend Time wasted arguing over inconsistent reports Lost business opportunities due to unavailable data Unable to demonstrate business potential in a buyout Fines may be paid for noncompliance with government regulations Shipping products to the wrong customers Bad public relations with customers leads to alienated and lost customer

اسلاید ۲۱: Cost of erroneous dataMarketingCampaignPerInstanceNumberof InstancesTotal NumberPer YearTotalCostPer YearTime: ($60/hour loaded rate) Creating redundant occurrence 2.4 min 167,141 1 $ 401,138 Researching correct address 10 min 5,000/mo 12 $ 600,000 Correcting address errors 0.3 min 6,000/mo 12 $ 21,600 Handling complaints from customers 5.5 min 974/yr 1 $ 5,357 Mail preparation 0.1 min 393,273 4 $ 157,3als, Facilities, Equipment: Marketing brochure $1.96 393,273 4 $3,083,260 Postage $0.52 393,273 4 $ 818,008 Warehouse storage $0.01 393,273 4 $ 15,731 Shipping equipment and maintenance $5,000/yr 36% 1 $ 1,800Computing resources: CPU transactions $0.02/trans 393,273 4 $ 31,462 Data storage $0.001/mo 393,273 12 $ 4,719 Data backup $0.005/mo 393,273 12 $ 23,596Direct Costs of Non-Quality Information© Larry English,Improving DW and BI QualityTotal Annual Costs $5,163,980

اسلاید ۲۲: Impact of redundant data Hardware (CPU, disks) and software (program maintenance) costs incurred as a result of uncontrolled redundant data Extra time it takes to reconcile inconsistencies Extra resources needed to reconcile inconsistencies Unwise business decisions made due to redundant and inconsistent data Lost opportunities due to unreliable data Overcharging or overpayment for products Duplicate shipping of products Money wasted on sending redundant marketing material

اسلاید ۲۳: Cost of redundant dataInformation Development Cost AnalysisCategoryPortfolioTotalNumberRelativeWeightFactor*AverageUnitDev/MaintCostsTotalDev/MaintExpenses**TotalInfrastructureValue-addingCost-addingExpenses% ofBudgetExpensesInfrastructure Basis: Enterprise architected DBs 200 0.75 $ 15,000 $ 3,000,000 Enterprise reusable create/update programs + 300 1.50 $ 30,000 $ 9,000,000 Total Infrastructure expenses $12,000,000Value Basis: Total retrieve equivalent pgms + 300 1.00 $ 20,000 $ 6,000,000 Total value-adding expenses $ 6,000,000 Cost-adding Basis: Redundant create/update pgms 500 1.50 $ 30,000 $15,000,000 Interface/extract programs 400 1.00 $ 20,000 $ 8,000,000 Redundant database files 600 0.75 $ 15,000 $ 9,000,000 Total cost-adding expenses 1,500 $32,000,000 Lifetime Total ** 3,800 $50,000,000 * Determine relative effort to develop average unit of each category using effort to develop a retrieve program as “۱.۰۰”+ For programs that retrieve some data and create/update other data, determine the percent of retrieve only attributes and percent of create/update attributes (e.g., to retrieve customer data to create an order)**Based on 3.800 application programs and database files in portfolio and $50 Million in development© Larry English,Improving DW and BI Quality 24% 12% 64%100%

اسلاید ۲۴: Dirty data – How did it happenBusinessManagerBusinessManagerTechnologyManagerTechnologyManager…………Business TechnologyChiefExecutiveOfficerChiefOperatingOfficerChiefInformationOfficerpaired withBusiness UnitsMarketingFinancial (AP & AR)Product PricingCustomer SupportDistributionInventorySalesClient Client Client Client Client Client ClientIT IT IT IT IT IT ITInformation Technology Unitsswim lane data redundancy process redundancy dirty data

اسلاید ۲۵: Major cause for data deficienciesTIMESCOPEBUDGETPEOPLEQUALITY1 2 3 4 5highest to lowest priorityProject ConstraintsWrong priority on project constraints! PriorityIndustrial Age: Cheaper, faster, better Automate as quickly as possibleCost-based value proposition

اسلاید ۲۶: Time is getting shorter – scope is getting biggerEveryone on the business side and in IT wants quality, but rarely is the extra time given or taken to achieve it. Quality and time are polarized constraints. The higher the quality the more effort (time) it takes to deliver. Companies are driven by shorter and shorter schedules.SCOPETIMEYAHDDD

اسلاید ۲۷: How are we addressing it todayData WarehousingCustomer Relationship ManagementEnterprise Resource PlanningEnterprise Application IntegrationKnowledge ManagementWhy can’t technologyfix thisIneffective Technology Solutions

اسلاید ۲۸: Data Warehousing The Promise:t data integrationt no redundancyt consistency t historical datat ad-hoc reportingt trend analysis reportingt faster data delivery t faster data access The Reality:t stove pipe martst departmental views t swim lane development approacht too time consuming to integrate t too costly to cleanse datat increased data redundancyIf it sounds too good to be true, it is to good to be true. DW delivers…a collection of integrated data used to support the strategic decision making process for the enterprise.

اسلاید ۲۹: Customer Relationship Management The Promise:t data integration t data qualityt customer intimacyt customer wallet sharet product pricing customization t knowing your competitiont geographic market potential The Reality:t more stovepipe systemst departmental views t dirty customer datat purchased