Description
Hello there, Data quality is a key business challenge of the 21st century. Quality has been an issue since the dawn of the IT profession and becomes increasingly challenging as the volumes of data increase and the uses for data expand. Regardless of your roles and responsibilities in IT - manager, developer, or technologist - you will at some time be challenged by data quality issues. And quality is an equal opportunity issue, imposing itself in every aspect from transaction systems to Web content and business intelligenceWhy is data quality important?Data quality matters because it significantly impacts your business performance. High-quality data helps you make better decisions and perform better actions, leading to increased revenue, decreased costs, and reduced risk. Low-quality data has the opposite effect, resulting in poor profitability and an increased risk that your business will fold prematurely. At the end of the course, you'll be able to grasp an all-round understanding of below concepts: Data QualityData StrategyData GovernanceData ArchitectureData Lifecycle ManagementAnalytics and Data ScienceData Quality Objectives6 Data Quality Dimensions and ExamplesRoles and Responsibilities of Data Owners and Data StewardsData Quality Management PrinciplesData Quality Management Process CycleData Quality Issue ManagementData CleansingOutcome: Understand the various Data Quality areasExplore Data Quality policies and proceduresDiscuss data profiling, validation rules, facets, data cleansing, and more... Understand how Data Quality is linked to other data disciplinesThank you!
