How to source good data

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Post on 11-Jul-2015



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<p>PowerPoint Presentation</p> <p>Sourcing Good Data10 best practices</p> <p>WelcomeWhy is data quality important?Our 10 best practicesAgenda:Data Quality Story</p> <p>Overbooked 10,000 tickets for eventManual spreadsheet error- data has reach* Panko and Port, 2012</p> <p>Inter-departmental69%Within department31%</p> <p>42%Where data from a report is used:% of data in spreadsheets that influences CEOJust how much of an issue is data quality?1 in 10 organisations rate their data quality as excellent</p> <p>Poor data quality accounts for 20% of business process costs$611bnThe cost of poor data quality to US companies each year* Gartner, TDWI</p> <p>And we want more2009 enough data to fill a stack of DVDs to the moon and back</p> <p>2020 Grow by 44xLess than 1% of available data is analysed93% of execs believe they are losing revenue as a result of not fully leveraging the information they collect* IDC, Oracle and EMC</p> <p>1%</p> <p>x44 by 2020What is data quality?HOW RELIABLEIS YOUR DATA?</p> <p>TRUSTEDANDCREDIBLECompleteAccurateAvailableConsistentWhy is data quality important?It gives us accurate and timely information to manage our businessIt supports accountabilityIt ensures the best use of our resourcesIt increases our efficiencyIt reduces the cost of reworkIt can increase customer satisfactionIt ensures we have the best possible understanding of our customers and employeesIt improves the success rate of enterprise initiatives like Business IntelligenceBuilding high quality supply chains of data</p> <p>MEASUREFOR QUALITY</p> <p>GET THERIGHT DATA</p> <p>BE AGILEFocus on the outcome</p> <p>Analysis ParalysisLetting data dictate what is important Limited time and energy to focus1ISSUES</p> <p>Focus on the outcome1</p> <p>Start with the outcomethen the data.Focus on what mattersRECOMMENDATIONS</p> <p>Profile your data2</p> <p>Data supplier doesnt know your data needsThe data you source is as good as the information you provide to the supplierISSUES</p> <p>Profile your data2</p> <p>Write your data profileStructure, Format, Frequency, Age, Delivery MethodCommunicate it to data providersOpportunity to identify issues and gapsRECOMMENDATIONS</p> <p>13Get as close to the source as possible3</p> <p>When your source data is somebody elses spreadsheet.Human Error RiskUnexpected ChangesAdditional effort and complexityAvailability of dataISSUES</p> <p>Get as close to the source as possible3CAUTION</p> <p>Be cautious of manual spreadsheetsSkip the spreadsheet as a sourcePLANCommunicate and measure for qualityRECOMMENDATIONS</p> <p>Streamline data sources4Using multiple sources </p> <p>Redundant data</p> <p>Increased complexity and quality risk</p> <p>ISSUES</p> <p>Streamline data sources4Identify redundant data</p> <p>Focus on the essentials</p> <p>Cut out the stuff you dont need</p> <p>RECOMMENDATIONSSet data quality expectations5</p> <p>Perfectionism BurnoutYou cant expect to focus on everythingISSUES</p> <p>Set data quality expectations5</p> <p>Focus on high impact dataEmploy tolerances and ranges for quality and accuracyRECOMMENDATIONSRELAX(a little)</p> <p>Catch data quality issues early6Early$1$10$100If found in the middle of the journeyIf found at the end of the journeyLate* Total Quality Management</p> <p>If found at the start of journey1-10-100 Rule:ISSUES</p> <p>Catch data quality issues early6</p> <p>Implement quality measures near the start of the data supply chainUse the start as a reference point when checking data further down the journey RECOMMENDATIONS</p> <p>Actively measure quality7ISSUESNo simple way to identify if data is correctInvalid Assumption:If the data meets our expectations today, it will going forwardWhat happens when we do find an issue?</p> <p>Actively measure quality7</p> <p>OKGOODNOT GOODDefine metrics for your data qualityMeasure for quality on a consistent basisAddress consistent issues with strategic solutions (e.g. data cleansing)</p> <p>RECOMMENDATIONS</p> <p>Expect Change. Embrace It.8</p> <p>We all know change is comingBusiness activity, changes in strategies and systemsSo rigid that you need to resetISSUES</p> <p>Expect Change. Embrace It.8LikelihoodImpactLLHHFocus on high likelihood/impact changesScore and rank potential changesHave a plan in place for high risk itemsRECOMMENDATIONS</p> <p>Plan for change9</p> <p>A change occurs, then what?Lack of clear policies and rules on who needs to do whatKnowledge resting in the minds of key individualsISSUES</p> <p>Plan for change9RECOMMENDATIONSCAUTIONIn the eventof a changethe following people willPolicies and rulesTracking ChangesDocumentation</p> <p>Controlled human interaction10</p> <p>Value of human interaction with data at the cost of data qualityUncontrolled manipulation of dataISSUES</p> <p>Controlled human interaction10Avoid uncontrolled manipulation</p> <p>Facilitate controlled and discrete changes</p> <p>Make sure it is traceable</p> <p>RECOMMENDATIONS</p> <p>Recap1Focus on the outcome2Profile your data3Get close to the source4Streamline data sources5Set data quality expectations</p> <p>Recap6Catch data quality issues early7Measure quality8Expect and embrace change9Plan for change10Controlled human interaction</p> <p>Thank You</p>