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Big Data Analytics System for Fact/Data-driven Decision Making

机译:用于事实/数据驱动决策的大数据分析系统

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摘要

Big Data analytics system has been developed for the London Borough of Lambeth to assist its activities in fact/data driven decision making. The system integrates various historical data from both internal and external sources to provide timely and accurate profiles on multiple measures that the borough council would be concerned.udThe data integrated from multiple sources includes demographics (Census: Population, ethnicity, disability, gender, tenure, household composition), employment (NOIMS, census, and annual business survey: Working age, unemployment by age and gender, employment by industry, year-on-year change in unemployment, NEETs), deprivation (NOIMS, IMD, census, and school survey: Child and working tax credits, free school meals, IMD scores, DLA claimants), health care (Health stats: Childhood obesity, percentage of people with respiratory problems, number of hospital admissions, live expectancy, deaths), transport (Gov.uk: Road accident instances, year-on-year change in road accident instances), crime (Met police: Average monthly total crimes, year-on-year change in total crimes), etc.udThe information is presented in an interactive, hierarchical and comparative way by using a map-based visualization dashboard. For a given measure, the borough average value can be obtained and compared with the value of each ward/LSOA code within the borough. The system is available in both Tableau-based and SQL Server-based platforms
机译:已为伦敦兰贝斯自治市开发了大数据分析系统,以协助其实际/以数据为依据的决策活动。该系统整合了来自内部和外部来源的各种历史数据,以提供有关自治市镇委员会将要关注的多种措施的及时,准确的概况。 ud来自多种来源的数据整合包括人口统计(人口普查:人口,种族,残疾,性别,任期) ,家庭构成),就业(NOIMS,人口普查和年度商业调查:工作年龄,按年龄和性别划分的失业率,按行业划分的就业,失业率的逐年变化,NEET),剥夺(NOIMS,IMD,人口普查和学校调查:儿童和工作税收抵免,免费学校进餐,IMD分数,DLA索赔人),医疗保健(健康统计:儿童肥胖,有呼吸道疾病的人口比例,住院人数,预期寿命,死亡人数),交通运输(政府) .uk:道路交通事故实例,道路交通事故实例的同比变化),犯罪(警察局:平均每月犯罪总数,犯罪总数同比变化) ud信息为公关通过使用基于地图的可视化仪表板以交互,分层和比较的方式来设计。对于给定的度量,可以获得自治市镇平均值并将其与自治市镇中每个病房/ LSOA代码的值进行比较。该系统在基于Tableau和基于SQL Server的平台中均可用

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    Chen D;

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