本文是计算机专业的留学生作业范例，题目是“How Effective is Metadata?（元数据的有效性如何?）”，在一个高度发展的技术世界里，大型组织要处理大量的信息。随着历史信息的快速增长，历史信息的检索已成为决策者的一项强制性任务。这就是数据仓库发挥作用的地方。数据仓库是一个集成数据库的集合，旨在支持管理决策和问题解决功能。
Abstract 摘要
In a highly growing technological world, large organizations deal with huge amount of information. With this rapid growth the retrieval of historical information has become a compulsory task for the decision makers. Here is where data warehouse comes into play. Data warehouse is a collection of integrated databases designed to support managerial decision making and problem solving functions.
Metadata is one of the most important feature available in data warehouse. In this paper we are going to explain how effective is metadata in data warehouse and how it helps in improvising the performance measures of the data warehouse making it highly efficient.
元数据是数据仓库中最重要的功能之一。在本文中，我们将解释数据仓库中的元数据如何有效，以及它如何帮助改进数据仓库的性能度量，使其高效。
1.INTRODUCTION引言
Retrieving the required information from data warehouse without metadata will be a daunting task. metadata is a small piece of data which tells the decision making analysts what kind of data is it and where it is stored. Thus making the task easy and time saving. Metadata has a significant role in data warehouse. There are of two parts front room and back room metadata. The back room metadata helps in extraction, cleaning and loading. the front room metadata is descriptive type helping in smooth functioning.
在不使用元数据的情况下，从数据仓库中检索所需的信息将是一项令人生畏的任务。元数据是一小块数据，它告诉决策分析师它是什么类型的数据以及它存储在哪里。从而使任务容易和节省时间。元数据在数据仓库中扮演着重要的角色。其中包括前厅元数据和后厅元数据两部分。后屋元数据有助于提取、清洁和装载。前厅元数据是描述性类型，有助于平稳运行。
While creating the data warehouse for large organizations one or more meta data has to be stored, for this meta model is been created. Meta model is a conceptual model for metadata database where meta data of a warehouse are stored. It renders detailed description of metadata units and their relationship existing between them. The metadata type and their abstraction level has a direct impact on building a meta model. Meta data management system mostly follows the federal structure (i.e.) combining the advantages of both centralized and distributed structures enabling a variety of meta database for storage. Meta model should be highly scalable so that when the application requirements change the users can customize the application specific component of metadata.
2.EFFECTS OF METADATA ON DATA WAREHOUSE元数据对数据仓库的影响
Metadata and its management play a very important role in data warehouse system. When a user needs to access a data in data warehouse, he first looks into the metadata for where it is located in that cluster of information. What if the metadata is not present, the user has to skim through the whole information to find out his required information which is practically an impossible task. Thus metadata showing up to be highly efficient in data warehouse. In context with data warehouse, metadata is majorly classified as business, technical and operational meta data.
元数据及其管理在数据仓库系统中起着非常重要的作用。当用户需要访问数据仓库中的数据时，他首先查看元数据，看看它在信息集群中的位置。如果元数据不存在，用户必须浏览整个信息以找到他所需的信息，这实际上是一项不可能完成的任务。因此，元数据在数据仓库中表现出了很高的效率。在数据仓库中，元数据主要分为业务元数据、技术元数据和运营元数据。
Business metadata explains about business definition, policies and others. Technical metadata has all technical information such as db. system names, tables, columns names, data types and values. Whereas operational metadata shows the currency of data. Meta data also ensures code reusability, accuracy, consistency and integrity of the system. It highly supports the development, maintenance and upgradation of Data warehouse.
LIMITATIONS:
When different layers of metadata fail to communicate and update successfully, the users will land up in wrong search of data.
SOLUTION:
A proper maintenance should be done on a timely basis and a notification mechanism should be initiated whenever such updating does not take place to ensure that metadata has updated and works fine. A good quality data warehouse should ensure good performance measures such as quality control, confidentiality of data, integrity, availability etc. Here we are going to see how metadata is playing a vital role in improvising the performance measures of data warehouse.
应该及时进行适当的维护，并且在没有发生此类更新时，应该启动通知机制，以确保元数据已经更新并正常工作。一个高质量的数据仓库应该确保良好的性能指标，如质量控制、数据保密性、完整性、可用性等。在这里，我们将看到元数据如何在改进数据仓库的性能度量方面发挥重要作用。
3.QUALITY CONTROL BY METADATA元数据质量控制
Implementation of data warehouse is a most efficient solution for decision makers. In some cases, data warehouse fails to meet the requirements due to lack of data quality. The major area where the data quality fails is while integrating the input sources. In a metadata quality control system, initially the demands for quality are gathered from the user and then convert these requirements into specifications. These specifications are added to metadata.
数据仓库的实现是决策者最有效的解决方案。在某些情况下，数据仓库由于缺乏数据质量而不能满足需求。数据质量出现问题的主要方面是在集成输入源时。在元数据质量控制系统中，首先从用户那里收集质量需求，然后将这些需求转换成规范。这些规范被添加到元数据中。
Along with this metadata, total data warehouse architecture is combined so the data is examined along the dataflow. This security mechanism is implemented in metadata since the metadata repository is responsible for each and every characteristic of data present in the warehouse. Hence applying quality demands in metadata helps to rectify the quality issues in data warehouse.
ADVANTAGES:
The quality demands of the user are satisfied, efficiency is improved, performance measure is boosted.
LIMITATION:
Firstly, though the quality control measure is applied in the initial stage, the data after stored in the warehouse do not guarantee the same quality. secondly, there is a slight modification in the warehouse architecture in accordance to the quality control model which may affect the performance of the warehouse.
SOLUTION:
A proper quality check should be carried out even after the data is stored in warehouse by involving quality maintenances in warehouse and also before involving modification in warehouse architecture the performance measure is to be checked so that it does not affect the efficiency.
4.SECURITY MEASURES BY METADATA元数据安全措施
A high quality data warehouse should have highly confidential storage system. Security is more important in this competitive world where hacking of information no more a big deal. Data warehouse is an inaccessible system providing huge of amount of data easily available for users. Security aspects are considered before building the data warehouse and inserted in the metadata in the architecture.so the user will be restricted to only a particular area where the access is provided, the rest data cannot be accessed unless proper authentication is provided. Inserting security measures after developing data warehouse will not be that effective and cost efficient. We apply security measure in metadata since applying it to the other parts will affect the performance of data warehouse and also it won’t end up in an efficient way.
一个高质量的数据仓库应该有高度机密的存储系统。在这个竞争激烈的世界里，安全变得更加重要，黑客攻击信息已不再是一件大事。数据仓库是一个不可访问的系统，为用户提供了大量的数据。在构建数据仓库并将其插入体系结构中的元数据之前，要考虑安全性方面的问题。因此，用户将被限制在提供访问的特定区域，除非提供适当的身份验证，否则无法访问其他数据。在数据仓库开发完成后，在数据仓库中插入安全措施的效果和成本效率并不高。我们将安全措施应用于元数据，因为将其应用于其他部分会影响数据仓库的性能，也不会以一种有效的方式结束。
ADVANTAGES:
Confidentiality of the data is maintained, illegal authentication is prohibited, increases the performance.
LIMITATION:
This security model is advantageous for those kind of data whose content is described by metadata and also it restricts the access to users, so the users end up making decision with the available decision thus indirectly affecting the performance of data warehouse.
SOLUTION:
Rather than giving authentication to a area, security system should be designed in such a way that only highly trusted users are let in the warehouse and are allowed to migrate throughout the system and make the better decision by considering all the available data.
5.CRITICAL REASONING批判性推理
For large organizations, metadata management is of great importance and great potential. Metadata not only provide information about the data in warehouse but also, helps in boosting various performance measures by which the user requirements are satisfied. By improving the quality of the data, consistency and efficiency is maintained in warehouse.
对于大型组织来说，元数据管理非常重要，也有很大的潜力。元数据不仅提供关于数据仓库中的数据的信息，而且还有助于提高满足用户需求的各种性能度量。通过提高数据质量，保证了仓库数据的一致性和效率。
By providing a secured data to the users as per their demands increases the performance of the warehouse. Other security measures and quality control measures involves more complexity than that of one involving metadata. So, using metadata would be a simple and prudent choice.
In this goal, driven business environment, it is important to serve the demands of the user rather than giving them a comprehensive result. Metadata is a small part in data warehouse architecture but in turn provides huge effects in functioning. Meta data gives meaning to data and adds clarity to the users. hereby we summarize the effects of metadata in data warehouse and how it helps in improving the performance measures of warehouse. This performance improvement techniques using metadata is not widely followed because of lack of understanding of importance of metadata and, the metadata management has higher degree of complexity. So, by this we get to know that metadata is essential and highly effective in data warehousing.
在这个目标驱动的业务环境中，重要的是为用户的需求服务，而不是给他们一个全面的结果。元数据在数据仓库体系结构中只是一个很小的部分，但反过来却提供了巨大的功能效果。元数据赋予数据意义，并为用户增加清晰度。在此，我们总结了元数据在数据仓库中的作用，以及它如何帮助提高数据仓库的性能指标。这种使用元数据的性能改进技术并没有得到广泛的应用，因为缺乏对元数据重要性的理解，而且元数据管理的复杂性更高。因此，通过这一点，我们了解到元数据在数据仓库中是必不可少的和非常有效的。
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