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BIwTL: A Business Information Warehouse Toolkit and Language for Warehousing Simplification and Automation

机译:Biwtl:用于仓储简化和自动化的商业信息仓库工具包和语言

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Rapidly leveraging information analytics technologies to mine the mounting information in structured and unstructured forms, derive business insights and improve decision making is becoming increasingly critical to today's business successes. One of the key enablers of the analytics technologies is an Information Warehouse Management System (IWMS) that processes different types and forms of information, builds, and maintains the information warehouse (IW) effectively. Although traditionalmulti-dimensional data warehousing techniques, coupled with the well-known ETL processes (Extract, Transform, Load) may meet some of the requirements in an IWMS, in general, they fall short on several major aspects: 1. They often lack comprehensive support for both structured and unstructured data processing; 2. They are database-centric and require detailed database and warehouse knowledge to perform IWMS tasks, and hence they are tedious and time-consuming to operate and learn; 3. They are often inflexible and insufficient in coping with a wide variety of on-going IW maintenance tasks, such as adding new dimensions and handling regular and lengthy data updates with potential failures and errors. To cope with such issues, this paper describes an IWMS, called BIwTL (Business Information Warehouse Toolkit and Language), that automates and simplifies IWMS tasks by devising a high-level declarative information warehousing language, GIWL, and building the runtime system components for such a language. BIwTL hides system details, e.g., databases, full text indexers, and data warehouse models, from users by automatically generating appropriate runtime scripts and executing them based on the GIWL language specification. Moreover, BIwTL supports structured and unstructured information processing by embedding flexible data extraction and transformation capabilities, while ensuring high performance processing for large datasets. In addition, this paper systematically studied the core tasks around information warehousing and identified five key areas. In particular, we describe our technologies in three areas, I.e., constructing an IW, data loading, and maintaining an IW.We have implemented such technologies in BIwTL 1.0 and validated it in real world environments with a number of customers. Our experience suggests that BIwTL is light-weight, simple, efficient, and flexible.
机译:迅速利用信息分析技术,以矿结构化和非结构化的形式,衍生业务洞察力的安装信息,提高决策正成为今天的商业成功越来越重要。一位分析技术的关键促成因素是一个信息仓库管理系统(IWMS),其处理不同类型和信息的形式,建立和维护的信息仓库(IW)有效。虽然traditionalmulti维数据仓库技术,再加上众所周知的ETL过程(提取,转换和加载),可满足部分在IWMS的要求,在一般情况下,他们功亏一篑几个主要方面:1。他们往往缺乏综合用于结构化和非结构化数据处理支持; 2.他们是数据库为中心,需要详细的资料库和仓库的知识来执行任务IWMS,因此他们是繁琐和耗时的工作和学习; 3.他们在与各种各样的应对往往缺乏灵活性,不足以持续的IW维护任务,如添加新的层面和处理潜在的故障和错误经常和冗长的数据更新。为了应对这些问题,本文介绍的IWMS,称为BIwTL(业务信息仓库工具包和语言),是自动化并简化通过设计一个高层次的声明信息仓储语言,GIWL,建设,运行时系统组件,例如IWMS任务一种语言。 BIwTL皮系统的详细信息,例如,数据库,全文索引器和数据仓库的模型,从用户通过自动生成相应的运行时的脚本以及基于所述GIWL语言规范执行它们。此外,支撑件BIwTL结构化和非结构化信息通过嵌入灵活的数据提取和转换功能的处理,同时确保大的数据集的高性能处理。此外,本文系统地研究了核心任务围绕信息仓库和确定了五个重点领域。尤其是,我们描述了三个方面的技术,即构建IW,数据加载,并维持IW.We已经BIwTL 1.0中实现这些技术,并与多家客户的验证,它在现实世界环境中。我们的经验表明,BIwTL重量轻,操作简单,高效和灵活。

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