The Complete Data Quality and Digital Transformation Course
※注意事項:
1.需透過LINE購物前往並在同一瀏覽器於24小時內結帳才享有回饋,點數將於廠商出貨後,隔天起算之90個日曆天陸續確認發送。
2.國際商家之商品金額及回饋點數依據將以商品未稅價格為準。
3.國際商家之商品金額可能受匯率影響而有微幅差異。
4.若於商家App下單,不符合LINE購物導購資格。商品描述
In light of the accelerating AI revolution across industries in the past years, it has never been more relevant than it is now post the global pandemic that you should improve your digital literacy and upskill yourself with data analytics skillsets. This course features the latest addition of an organisation structure - Chief Data Office which enables an organisation to become data and insights driven, no matter it's in a centralised, hybrid or de-centralised format. You'll be able to understand how each of the Chief Data Office function works and roles and responsibilities underpinned each pillar which covers the key digital concepts you need to know. There is a focus on the end-to-end data quality management lifecycle and best practices in this course which are critical to achieving the vision set out in the data strategy and laying the foundations for advanced analytics use cases such as Artificial Intelligence, Machine Learning, Blockchain, Robotic Automation etc. You will also be able to check your understanding about the key concepts in the exercises and there are rich reading materials for you to better assimilate these concepts. At the end of the course, you'll be able to grasp an all-round understanding about below concepts: Digital TransformationChief Data OfficerChief Data OfficeCentralised Chief Data Office Organisation StructureData StrategyData MonetisationData GovernanceData StewardshipData QualityData ArchitectureData Lifecycle ManagementOperations IntelligenceAdvanced Analytics and Data ScienceData Quality Objectives6 Data Quality Dimensions and ExamplesRoles and Responsibilities of Data Owners and Data Stewards (Data Governance)Data Quality Management PrinciplesData Quality Management Process CycleData DomainISO 8000Data ProfilingData Profiling Technologies (Informatica, Oracle, SAP and IBM)MetadataDifferences Between Technical and Business MetadataBusiness Validation RulesData Quality Scorecard (with Informatica example)Tolerance LevelRoot Cause AnalysisData CleansingData Quality Issue Management (with a downloadable issue management log template)After you complete this course, you will receive a certificate of completion. So how does this sound to you? I look forward to welcoming you in my course. Cheers, Bing