CAJ | 학술논문

大数据的应用核心就是大数据预测。大数据预测完全依赖大数据来源，因此具有“全样非抽样、效率非精确、相关非因果”的特征。按照预测的精细程度，大数据预测的层级分为三级，依次递进：圈子范围的大小、圈子内有哪些族群、族群中每个成员的个性特征。能否在三个层次获得准确的预测结果，关键在于前台数据和后台数据、宏观数据和微观数据、共性数据和个性之间的关联分析。对于任何大数据的预测结果，必须设计一个验证流程，以防止出现不必要的错误。
대수거적응용핵심취시대수거예측。대수거예측완전의뢰대수거래원，인차구유“전양비추양、효솔비정학、상관비인과”적특정。안조예측적정세정도，대수거예측적층급분위삼급，의차체진：권자범위적대소、권자내유나사족군、족군중매개성원적개성특정。능부재삼개층차획득준학적예측결과，관건재우전태수거화후태수거、굉관수거화미관수거、공성수거화개성지간적관련분석。대우임하대수거적예측결과，필수설계일개험증류정，이방지출현불필요적착오。
The core application of big data is forecasts based on big data. It is accuracy entirely dependent on big data sources, and therefore has the feature of"full but non-part, efifciency but non-precise, relevant but non-causal". According to forecasts ifneness, big data predicted l accuracy is divided into three levels, followed by progressive:the size of the groups, the size of sub-groups, the personality characteristics of each member within the sub-groups. The key to get the accurate predictions is correlation analysis between the behavioral data and outcome data, the macro data and micro data, and the common and personality data. For any predictions of big data, you must design a veriifcation process to prevent unnecessary errors.