An architecture for automatically developing secure OLAP applications from models

ContextDecision makers query enterprise information stored in Data Warehouses (DW) by using tools (such as On-Line Analytical Processing (OLAP) tools) which use specific views or cubes from the corporate DW or Data Marts, based on the multidimensional modeling. Since the information managed is critical, security constraints have to be correctly established in order to avoid unauthorized accesses.ObjectiveIn previous work we have defined a Model-Driven based approach for developing a secure DWs repository by following a relational approach. Nevertheless, is also important to define security constraints in the metadata layer that connects the DWs repository with the OLAP tools, that is, over the same multidimensional structures that final users manage. This paper defines a proposal to develop secure OLAP applications and incorporates it into our previous approach.MethodOur proposal is composed of models and transformations. Our models have been defined using the extension capabilities from UML (conceptual model) and extending the OLAP package of CWM with security (logical model). Transformations have been defined by using a graphical notation and implemented into QVT and MOFScript. Finally, this proposal has been evaluated through case studies.ResultsA complete MDA architecture for developing secure OLAP applications. The main contributions of this paper are: improvement of a UML profile for conceptual modeling; definition of a logical metamodel for OLAP applications; and definition and implementation of transformations from conceptual to logical models, and from logical models to the secure implementation into a specific OLAP tool (SSAS).ConclusionOur proposal allows us to develop secure OLAP applications, providing a complete MDA architecture composed of several security models and automatic transformations towards the final secure implementation. Security aspects are early identified and fitted into a most robust solution that provides us a better information assurance and a saving of time in maintenance.     

基于SQL Server的OLAM的研究及应用

OLAM(On-line Analytical Mining)是当前的热点技术,是融合了联机分析处理(OLAP)和数据挖掘(Data Mining)的一种新的数据挖掘技术。本文主要研究数据仓库中OLAP,On-line Analytical Processing和数据挖掘技术,这两个技术是商业智能中的核心技术和主要内容,在两者的基础上引入OLAM的概念,并阐述其基本原理和核心技术。基于微软的SQL Server平台,为一个商业案例建立数据仓库,利用Analysis Services服务,建立销售分析的多维数据集,利用OLAM的基本模型实现OLAP和聚类挖掘技术的结合,借助两者的各自优势,得到很好的客户聚类分析结果。     

Developing secure data warehouses with a UML extension

Data Warehouses (DWs), Multidimensional (MD) Databases, and On-Line Analytical Processing Applications are used as a very powerful mechanism for discovering crucial business information. Considering the extreme importance of the information managed by these kinds of applications, it is essential to specify security measures from the early stages of the DW design in the MD modeling process, and enforce them. In the past years, some proposals for representing main MD modeling properties at the conceptual level have been stated. Nevertheless, none of these proposals considers security issues as an important element in its model, so they do not allow us to specify confidentiality constraints to be enforced by the applications that will use these MD models. In this paper, we will discuss the specific confidentiality problems regarding DWs as well as present an extension of the Unified Modeling Language for specifying security constraints in the conceptual MD modeling, thereby allowing us to design secure DWs. One key advantage of our approach is that we accomplish the conceptual modeling of secure DWs independently of the target platform where the DW has to be implemented, allowing the implementation of the corresponding DWs on any secure commercial database management system. Finally, we will present a case study to show how a conceptual model designed with our approach can be directly implemented on top of Oracle 10g.     

基于Essbase的商业智能实例产品开发

本文介绍了商业智能的产生、发展及其体系结构。从理论和技术两方面对商业智能的基础数据仓库以及它最成熟的在线工具联机分析处理（OLAP）进行了深入分析,包括数据仓库的特征、数据仓库的关键技术,OLAP的原理、数据结构及实现等。基于IBM的联机分析处理服务器Essbase,开发了商业智能产品,重点描述了其中间层Application Server的工作原理。     

商业智能在科技服务决策支持系统中的应用

在介绍了商业智能的核心技术和体系结构包括数据仓库、联机分析处理、数据挖掘等的基础上,通过分析科技信息服务这个特定领域的决策需求,给出了基于商业智能的科技服务决策支持系统的解决方案。实际应用表明该系统提高了科技信息供需双方对现有信息数据的利用效率,还提高了科技信息服务机构的决策分析能力。     

数据仓库中的一种立方体数据模型

数据仓库和联机分析处理(OLAP)是商业数据处理领域中的两个最重大的新技术。OLAP应用要求对数据仓库中存储的大量数据进行分析,用标准关系数据库技术来实现非常复杂的查询是相当困难的。所以,在数据仓库中,数据被组织成立方体数据模型。该文提出了一种简单、直观的数据立方体模型以及在这个立方体上支持OLAP操作的代数。为复杂的查询提供了简要的表述方法。     

Extending OCL for OLAP querying on conceptual multidimensional models of data warehouses

The development of data warehouses begins with the definition of multidimensional models at the conceptual level in order to structure data, which will facilitate decision makers with an easier data analysis. Current proposals for conceptual multidimensional modelling focus on the design of static data warehouse structures, but few approaches model the queries which the data warehouse should support by means of OLAP (on-line analytical processing) tools. OLAP queries are, therefore, only defined once the rest of the data warehouse has been implemented, which prevents designers from verifying from the very beginning of the development whether the decision maker will be able to obtain the required information from the data warehouse. This article presents a solution to this drawback consisting of an extension to the object constraint language (OCL), which has been developed to include a set of predefined OLAP operators. These operators can be used to define platform-independent OLAP queries as a part of the specification of the data warehouse conceptual multidimensional model. Furthermore, OLAP tools require the implementation of queries to assure performance optimisations based on pre-aggregation. It is interesting to note that the OLAP queries defined by our approach can be automatically implemented in the rest of the data warehouse, in a coherent and integrated manner. This implementation is supported by a code-generation architecture aligned with model-driven technologies, in particular the MDA (model-driven architecture) proposal. Finally, our proposal has been validated by means of a set of sample data sets from a well-known case study.     

Logical Representation of a Conceptual Model for Spatial Data Warehouses

The MultiDimER model is a conceptual model used for representing a multidimensional view of data for Data Warehouse (DW) and On-Line Analytical Processing (OLAP) applications. This model includes a spatial extension allowing spatiality in levels, hierarchies, fact relationships, and measures. In this way decision-making users can represent in an abstract manner their analysis needs without considering complex implementation issues and spatial OLAP tools developers can have a common vision for representing spatial data in a multidimensional model. In this paper we propose the transformation of a conceptual schema based on the MultiDimER constructs to an object-relational schema. We based our mapping on the SQL:2003 and SQL/MM standards giving examples of commercial implementation using Oracle 10g with its spatial extension. Further we use spatial integrity constraints to ensure the semantic equivalence of the conceptual and logical schemas. We also show some examples of Oracle spatial functions, including aggregation functions required for the manipulation of spatial data. The described mappings to the object-relational model along with the examples using a commercial system show the feasibility of implementing spatial DWs in current commercial DBMSs. Further, using integrated architectures, where spatial and thematic data is defined within the same DBMS, facilitates the system management simplifying data definition and manipulation.

基于ODS构建商业系统的即时OLAP应用

基于DB和DW的中间层ODS的数据存储技术,从应用的角度分析设计了一个商业系统的即时OLAP系统。通过使用ODSD克服了利用DW进行决策过于臃肿且不适合企业即时中层决策的问题。     

OLAP性能测试方法研究与实现

随着商业智能市场的逐步扩大,联机分析处理(OLAP)系统的使用质量评估已经成为数据库应用的研究热点.作为效用特性的OLAP系统性能评估需要一个性能基准.以OLAP委员会推出的APB-1性能基准为基础,首先设计了面向多维数据库的立方体(Cube)模型以及相应的多维表达式(MDX)查询模板,在Cube模型设计的过程中修改了APB-1基准ROLAP星型模型的不足之处;接着在测试数据一致和测试参数一致的前提下,通过对设计的MOLAP模型查询结果与ROLAP模型查询结果进行对比分析,证明了MOLAP模型及MDX查询模板设计的正确性;然后给出了OLAP性能测试流程,描述了支持ROLAP和MOLAP性能测试的工具框架及其主要模块.最后使用该测试框架在商业数据库管理系统上对ROLAP和MOLAP进行并发查询实践,验证了框架的有效性.提出的方法及技术实现为未来OLAP产品性能的测试和评价提供多维数据模型、业务模型和工具的支持.     

The data warehouse virtualization framework for operational business intelligence

In order to explore the most current information and react faster to changing business conditions, organizations consider real‐time data warehousing a powerful technique to achieve operational business intelligence (BI). We propose in this paper a novel real‐time data warehouse (RTDW) framework based on the virtualization concept. Our approach introduces a conceptual modelling technique, known as ring modelling, for real‐time data management and multidimensional analysis. This technique produces a flexible semi‐structured data model that accommodates unknown business process data and relationships as they evolve, handles schema changes and aggregate‐management efficiently, and scales well with the large size of increasing data volumes. With the help of a telecommunication business example, We evaluated our proposed approach in an extensive experimental study where we compared our approach Ring Model with existing structured multidimensional conceptual models (MCMs), i.e. relational OLAP and multidimensional OLAP, and with semi‐structured MCM, i.e. XML Cubes, in terms of scalability, data storage estimations, data updates loading time, and query response times. Our performance results show that encouraging speedups are achieved.     

从EDOC的业务过程建模到J2EE应用程序框架的MDA转换

OMG（Object Management Group,对象管理组织）提出的模型驱动架构（MDA,Model Driven Architecture）是解决不同中间件平台之间的集成以及技术升级所引起的问题的软件开发方法。MDA的基本思想是将系统的模型作为软件开发过程的核心制品,并且将模型区分为描述系统业务功能的平台独立模型（PIM,Platform Independent Model）和描述系统在特定技术平台上实现细节的平台相关模型（PSM,Platform Specific Model）。模型转换是MDA开发的核心内客。MDA的开发效率依赖于良好的支撑工具,特别是支持模型转换的工具的涌现。本文介绍一种对业务过程建模并将模型转换成程序代码的设计恩想和实现方法。开发者可以用该工具对企业的业务过程建模。这个工具能将建立的模型自动转换成J2EE平台上的程序代码。     

机场数据仓库/商业智能平台的设计与实现

杭州萧山国际机场数字空港规划的落实,促使许多信息系统相继建成,在不少信息系统数据库中已经积累了大量的数据。建设机场的商业智能平台,实现数据的集成和共享,将积累的信息资源服务于管理决策势在必行。文章介绍了数据仓库和商业智能的相关概念,对机场数据仓库/商业智能平台的设计和构建作了阐述。目前该平台一期已经建成,并投入使用。     

The cgmCUBE project: Optimizing parallel data cube generation for ROLAP

On-line Analytical Processing (OLAP) has become one of the most powerful and prominent technologies for knowledge discovery in VLDB (Very Large Database) environments. Central to the OLAP paradigm is the data cube, a multi-dimensional hierarchy of aggregate values that provides a rich analytical model for decision support. Various sequential algorithms for the efficient generation of the data cube have appeared in the literature. However, given the size of contemporary data warehousing repositories, multi-processor solutions are crucial for the massive computational demands of current and future OLAP systems. In this paper we discuss the cgmCUBE Project, a multi-year effort to design and implement a multi-processor platform for data cube generation that targets the relational database model (ROLAP). More specifically, we discuss new algorithmic and system optimizations relating to (1) a thorough optimization of the underlying sequential cube construction method and (2) a detailed and carefully engineered cost model for improved parallel load balancing and faster sequential cube construction. These optimizations were key in allowing us to build a prototype that is able to produce data cube output at a rate of over one TeraByte per hour. Research supported by the Natural Sciences and Engineering Research Council of Canada (NSERC).     

基于医院信息系统的商业智能系统研究

介绍了商业智能系统的概念及功能,对商业智能在医院信息系统中的应用进行了探索性研究,以SQL Server 2005作为构建数据仓库的技术平台,并作为对数据仓库进行联机分析的工具,给出了一个以医院住院病人医嘱为主题的数据仓库实例.探索性研究了数据仓库构建、多维数据分析、数据展现等技术问题.     

一种数据仓库操作的优化方法

数据立方体在许多多维数据的数据仓库的高速OLAP操作中扮演着重要的角色.但是在许多高维的数据仓库的应用中,例如超过100维,大约106个元组,在这样高维下建立物化数据立方体是不可行的.利用最小方的方法可以在高维数据集上进行有效OLAP操作的方法.但每次进行OLAP操作所涉及的维大多有固定的分布,所以大量的查询都有重复计算.如果能部分物化与大多数OLAP操作相关维的立方体ID,就能在进行OLAP操作时可以大大的提高OLAP操作的效率.     

多维数据库模式下联机数据分析技术的实施

随着社会的发展和技术的进步,越来越多的领域和企业组织都需要处理并分析其已有的海量数据和信息。基于目前数据库技术的日趋成熟与相应的数据仓库技术的不断兴起,提出了一个基于多维数据库模式的联机数据分析技术的原型平台解决方案,即侧重于多维数据库存储模式的实现和该存储模式下的联机数据分析功能的设计两方面,完成了该原型平台的设计与实现。文中主要研讨了该原型平台的开发过程中所涉及的重点以及难点技术问题,并最终将该原型平台应用并满足某信息系统的实际联机数据分析的需求,从而验证了该原型平台的相关功能的实用性和有效性。     

SQL Server 2005 OLAP技术研究与实现

简要介绍了OLAP的概念和特点;从OLAP最新概念和技术等方面,解释了微软SQL Server 2005中统一维度模型;研究了微软现代OLAP搭建方法与传统搭建方法的差异;通过基于企业销售数据多维数据集的OLAP实例,说明了微软最新OLAP的设计概念的可行性,有助于企业方便快捷地建立自已的分析决策支持平台。     

基于J2EE平台的MDA模型转换技术

The OMG's MDA defines an approach to IT system specification that separates the specification of system functionality from the specification of the implementation of that functionality on a specific technology platform. To this end, the MA defines two kinds of models: platform independent model (PIM) and platform specific model(PSM). The MDA approach allows the same model specifying system functionality to be realized on multiple platforms through auxiliary mapping standards from PIM to PSM. This paper presents a mapping method from PIMsto PSMs based on J2EE platform. This transformation can promote the efficiency of system analysis and design.     

Object-based selective materialization for efficient implementationof spatial data cubes

With a huge amount of data stored in spatial databases and the introduction of spatial components to many relational or object-relational databases, it is important to study the methods for spatial data warehousing and OLAP of spatial data. In this paper, we study methods for spatial OLAP, by integrating nonspatial OLAP methods with spatial database implementation techniques. A spatial data warehouse model, which consists of both spatial and nonspatial dimensions and measures, is proposed. Methods for the computation of spatial data cubes and analytical processing on such spatial data cubes are studied, with several strategies being proposed, including approximation and selective materialization of the spatial objects resulting from spatial OLAP operations. The focus of our study is on a method for spatial cube construction, called object-based selective materialization, which is different from cuboid-based selective materialization (proposed in previous studies of nonspatial data cube construction). Rather than using a cuboid as an atomic structure during the selective materialization, we explore granularity on a much finer level: that of a single cell of a cuboid. Several algorithms are proposed for object-based selective materialization of spatial data cubes, and a performance study has demonstrated the effectiveness of these techniques