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Informatica Data Quality:无所不在的Data Quality,提供可信数据
Informatica Data Quality将转换企业的经营方式,让您的所有<em>数据</em>获得公信力,随时随地地满足您的所有需求。Informatica Data Quality通过一个统一平台,向所有利益相关人士、所有项目、<em>数据</em>域和业务应用程序(无论在内部预置,还是在云中)<em>提供</em>可靠而<em>可信</em>的<em>数据</em>
Informatica data quality
<em>data</em> <em>quality</em>; <em>data</em> analysis; <em>data</em> profile; <em>informatica</em> <em>data</em> <em>quality</em> tools
Informatica Data Quality 9.5
Informatica Data Quality 9.5介绍
Informatica Data Quality Analyst
通过允许业务经理访问基于 浏览器的<em>数据</em>质量记分卡,我 们让数量不限的相关人员均能 直接参与<em>数据</em>质量流程并从顶 部推动改善流程。Informatica Data Quality 的主要益处是通过 使<em>数据</em>质量更为显而易见,与 业务的相关性更高,从而不断 提高对企业<em>数据</em>的信心和信任 度。”
Informatica Data Quality 9.5介绍
Informatica Data Quality 9.5介绍
Informatica Data Quality Lab Guide
Informatica Data Quality培训资料,基于IDQ8.6.1版本。
Informatica Data Quality Student Guide
这个是Student Guide,需要结合Lab Guide一起学习。
data quality
Data <em>quality</em> made every day
Data Quality And TrustIn Big Data
Data Quality And TrustIn Big Data
Data Quality and Trust in Big Data
Data Quality and Trust in Big Data, 5th International Workshop, QUAT 2018, Held in Conjunction with WISE 2018, Dubai, UAE, November 12–15, 2018, Revised Selected Papers
适用于数据仓库的 MDM 和Informatica Data Quality
虽然许多公司都曾投资兴建成熟完善的商务智能 (BI) 系统,以优化业务流程或确保遵守管制报告要求,但是这些公司却往往仍无法达到预期的效果。为什么呢?这是因为这些系统没有包含有关客户、产品、渠道合作伙伴、供应商和员工的关键业务可靠<em>数据</em> — 亦称之为主<em>数据</em>或参考<em>数据</em>。
Quality Measures in Data Mining
The purpose of this book is to present the state of the art concerning <em>quality</em>/interestingness measures for <em>data</em> mining. The book summarizes recent developments and presents original research on this topic. The chapters include reviews, comparative studies of existing measures, proposals of new measures, simulations, and case studies. Both theoretical and applied chapters are included.
DW2.0 and Data Quality
This paper will describe the optimal <em>data</em> <em>quality</em> process with the aid of the DW2.0 Architecture, DW2.0TM is the architecture of the next generation of <em>data</em> warehousing. It is a statement of what a <em>data</em> warehouse should be and the vision that Bill Inmon has for the future of <em>data</em> warehousing. This architecture gives your organization a sustained <em>quality</em> improvement of the corporation's <em>data</em> warehousing investment. Several features of DW 2.0 include the recognition of the life cycle of <em>data</em> within the <em>data</em> warehouse; inclusion of unstructured <em>data</em> along with structured <em>data</em> inside the <em>data</em> warehouse.
datawarehouse data quality management
<em>data</em>warehouse <em>data</em> <em>quality</em> management
Journey to Data Quality
Data Mining's Quality MIT Press
introduction to data quality
The file is an introduction to <em>data</em> <em>quality</em>, and was created in 2004. You could know some researchers, and search them, maybe you will get more.
data quality assessment
by Leo L. Pipino, Yang W. Lee, and Richard Y. Wang 一篇不错的关于<em>数据</em>质量的论问题
Data Mining, Metadata management,data quality
<em>数据</em>挖掘,元<em>数据</em>管理大家有何高见?rnrnibm,sas,ca,oracle等少数几家<em>提供</em>挖掘的厂商。rnrnascential,ca,sybase,oracle,cognos,busness object等<em>提供</em>meta<em>data</em>的管理rnrn<em>数据</em>质量管理就只知道ascential的<em>quality</em> manager,印象中ca也有,希望大家多多补充。rnrnrn:)
Developing High Quality Data Models
Developing High Quality Data Models 开发高质量的<em>数据</em>模型 - <em>数据</em>仓库
NASA data for quality estimation tasks
NASA <em>data</em> for <em>quality</em> estimation tasks, including faults, object-oriented design metrics and size information of the modules.
wq:Exploring water quality monitoring data
基于R的程序包wq,主要用于水质监测<em>数据</em>的时间序列处理,但不限于水质<em>数据</em>。本资源含documents与package.
Quality and Efficiency in Kernel Density Estimates for Large Data
Sigmod 13文章,关于KDE在大<em>数据</em>上的做法的文章,值得看一下
Stream Data Processing A Quality of Service Perspective
The systems used to process <em>data</em> streams and provide for the needs of stream-based applications are Data Stream Management Systems (DSMSs). This book presents a new paradigm to meet the needs of these applications, including a detailed discussion of the techniques proposed. Ii includes important aspects of a QoS-driven DSMS (Data Stream Management System) and introduces applications where a DSMS can be used and discusses needs beyond the stream processing model. It also discusses in detail the design and implementation of MavStream. This volume is primarily intended as a reference book for researchers and advanced-level students in computer science. It is also appropriate for practitioners in industry who are interested in developing applications.
Talend Data Quality Job and Analysis Examples
Incorporating appropriate <em>data</em> <em>quality</em> tools in your business processes is vital at the beginning of any project and through the project plan in order to see what type of <em>data</em> <em>quality</em> you have and decide how and what <em>data</em> to resolve.
SAS Data Analytic Development Dimensions of Software Quality
SAS Data Analytic Development Dimensions of Software Quality
Design of Video Quality Metrics with Muilt-Way Data Analysis.pdf
本书介绍了目前广泛使用的各种视频编码质量评估客观标准,同时<em>提供</em>各种<em>数据</em>分析方法
A Model for Data Quality Assessment .pdf
对<em>数据</em>质量评测的方法,这个主题比较小众,但是很有用
MASTER DATA MANAGEMENT ROLES - THEIR PART IN DATA QUALITY IMPLEMENTATION
MASTER DATA MANAGEMENT ROLES - THEIR PART IN DATA QUALITY IMPLEMENTATION
About the Power Quality Data Interchange Format (PQDIF)
About the Power Quality Data Interchange Format (PQDIF)
Start Improving Your Data Quality with the %FreqAll Macro
The first step in understanding and improving the <em>quality</em> of <em>data</em> requires knowledge of the composition of the tables within a <em>data</em>base. What follows is an effective yet simple macro called %FreqAll, designed to deliver a fast and easy first glance at the <em>data</em> values and <em>quality</em>.
Pattern Recognition. A Quality of Data Perspective
Pattern recognition has established itself as an advanced area with a well-defined methodology, a plethora of algorithms, and well-defined application areas. For decades, pattern recognition has been a subject of intense theoretical and applied research inspired by practical needs. Prudently formulated evaluation strategies and methods of pattern recognition, especially a suite of classification algorithms, constitute the crux of numerous pattern classifiers. There are numerous representative realms of applications including recognizing printed text and manuscripts, identifying musical notation, supporting multimodal biometric systems (voice, iris, signature), classifying medical signals (including ECG, EEG, EMG, etc.), and classifying and interpreting images. With the abundance of <em>data</em>, their volume, and existing diversity arise evident challenges that need to be carefully addressed to foster further advancements of the area and meet the needs of the ever-growing applications. In a nutshell, they are concerned with the <em>data</em> <em>quality</em>. This term manifests in numerous ways and has to be perceived in a very general sense. Missing <em>data</em>, <em>data</em> affected by noise, foreign patterns, limited precision, information granularity, and imbalanced <em>data</em> are commonly encountered phenomena one has to take into consideration in building pattern classifiers and carrying out comprehensive <em>data</em> analysis. In particular, one has to engage suitable ways of transforming (preprocessing) <em>data</em> (patterns) prior to their analysis, classification, and interpretation.
Data Quality Consideration in Master Data Management Structures(White Book)
主<em>数据</em>管理结构中如何设计<em>数据</em>质量,是白皮书。最后讲了一个<em>数据</em>质量控制的软件产品。
调试经验——数据数据质量对报表的影响 (Impact of data quality to reporting quality
问题及分析: 用户在询问为什么前端页面上<em>数据</em>是正确的,但报表上显示为空白。 经过一番艰苦的<em>数据</em>排查(反复推测原因、反复验证),最终发现是<em>数据</em>表中的<em>数据</em>质量问题。表现在两个方面: 1. 有些view中包含的<em>数据</em>不全 (可通过改用all_v的新view来避免) 2. <em>数据</em>表中<em>数据</em>本身为空,原因未知(猜测是前端应用在版本管理上出现了问题,导致最大的action ID对应的字段值为空,报表中抓出来...
Quality of Service
很好的Qos资料哦、 Implementing Cisco Quality of Service
Informatica Data Subset
简介:Informatica Data Subset 是一款非常灵活的企业<em>数据</em>增长解决方案,可将大型复杂<em>数据</em>库自动创建为较小的目标<em>数据</em>库。使用完整引用的生产<em>数据</em>子集,IT 组织可以大幅缩减支持非生产环境所需的时间、工作量和磁盘空间。
Informatica B2B Data Exchange
Informatica B2B Data Exchange 让 IT 机构来定义流程和转换,并允许企业用户可以按照合作伙伴和来源配置它们。IT 部门和企业用户都可以监控有关每个合作伙伴和流程的<em>数据</em>事件,并对变化作出有效响应。可以在整个交换过程中清楚掌握<em>数据</em>情况,从而可以成功实施和管理极其复杂的流程。
Informatica Data Masking的主要功能
•单一的可扩展<em>数据</em>屏蔽环境rn•健全的<em>数据</em>屏蔽支持rn•整套应用程序 Acceleratorsrn•广泛的连接和自定义应用程序支持rn
Informatica B2B Data Transformation.
Informatica B2B Data Transformation <em>提供</em>了一种全面的企业级解决方案来应对您的转换挑战。它可以从任何文件、文档或消息中提取任何格式、复杂度或大小的<em>数据</em>,并将这些<em>数据</em>转换成实用格式,在这方面,它拥有最出色的技术。
Quality Center
容易检测问题报告,1. 文件的所有权益归上传用户所有 2. 未经权益所有人同意不得将文件中的内容挪作商业或盈利用途 3. CSDN<em>下载</em>频道仅<em>提供</em>交流平台,并不能对任何<em>下载</em>内容负责 4. <em>下载</em>文件中如有侵权或不适当内容,请与我们联系,我们立即纠正。 5. 本站不保证本站<em>提供</em>的<em>下载</em>资
Quality Is Free
当读者们在欣赏这套丛书,他们会发现克劳士比管理哲学和实践是如何从一家企业中产生、发展和成熟,一直到如今被广泛应用到全球大量企业中的。读者们也会被这套丛书的实战风格所吸引,享受到阅读的乐趣。
ISO_IEC_9126_Software Quality
ISO9126 1 English version
下载,安装部署Quality Center 10.doc
找了好久终于找到了,和大家共享了( ⊙ o ⊙ )啊!
Informatica Data Explorer 9.5
Informatica Data Explorer 9.5功能介绍
Uncertainty Modelling Quality Control for spatial Data(Stein,_Alfred)
Uncertainty Modelling Quality Control for spatial Data([作者Stein,_Alfred;_Wenzhong,_Shi;_Wu,_Bo])原版清晰pdf。
红葡萄酒数据集winequality-red.csv,白葡萄酒数据集winequality-white.csv,Wine Quality Data Set
包括两个<em>数据</em>集:红葡萄酒<em>数据</em>集wine<em>quality</em>-red.csv,白葡萄酒<em>数据</em>集wine<em>quality</em>-white.csv,涉及来自葡萄牙北部的红色和白色vinho verde葡萄酒样本。 目标是根据物理化学测试对葡萄酒质量进行建模 Two <em>data</em>sets are included, related to red and white vinho verde wine samples, from the north of Portugal. The goal is to model wine <em>quality</em> based on physicochemical tests
Modern Big Data Algorithms (Lower quality PDF).pdf
HyperLearn is written completely in PyTorch, NoGil Numba, Numpy, Pandas, Scipy & LAPACK, and mirrors (mostly) Scikit Learn. HyperLearn also has statistical inference measures embedded, and can be called just like Scikit Learn's syntax
SAS Data Analytic Development Dimensions of Software Quality epub
SAS Data Analytic Development Dimensions of Software Quality 英文epub 本资源转载自网络,如有侵权,请联系上传者或csdn删除 查看此书详细信息请在美国亚马逊官网搜索此书
ON CREATING A NEW FORMAT FOR POWER QUALITY AND QUANTITY DATA INTERCHANGE
ON CREATING A NEW FORMAT FOR POWER QUALITY AND QUANTITY DATA INTERCHANGE
Informatica Data Quality for SAP:在您的 SAP ERP 系统中保持高水平的数据质量
Informatica Data Quality for SAP会在问题<em>数据</em>进入SAP ERP系统之前及时发现它们。当<em>数据</em>输入SAP ERP系统后,立刻进行验证,这项程序有助于防止坏<em>数据</em>在第一时间进入系统。这一程序通常被部署在成熟的SAP环境下,其中<em>数据</em>质量被视为运营效率与竞争优势的关键组成部分。
Design of Video Quality Metrics with Multi-Way Data Analysis A data 无水印pdf
Design of Video Quality Metrics with Multi-Way Data Analysis A <em>data</em> driven approach 英文无水印pdf pdf所有页面使用FoxitReader和PDF-XChangeViewer测试都可以打开 本资源转载自网络,如有侵权,请联系上传者或csdn删除 本资源转载自网络,如有侵权,请联系上传者或csdn删除
Diameter Quality of Service Application
Diameter Quality of Service Application
Quality Center.zipQuality Center.zipQuality Center.zip
Quality Center.zipQuality Center.zipQuality Center.zip
嵌入式软件测试技术[QUALITY]
嵌入式软件测试技术,很不错的文档,适合初学者
ISO_IEC_90003_2004 Quality Assurance on Software.pdf
ISO_IEC_90003_2004 Quality Assurance on Software.pdf
Quality Center测试专用
Quality Center 不好用不要钱,人品担保绝对可用,网上搜索不到的 ,我这是很久之前找测试要的。现在已经绝版了。
Quality Function Deployment
Quality Function Deployment
Web Servicesdefuwuzhiliang(Quality of Service)
1.提出了一个结合领域相关服务质量属性的Web Services服务质量模型.2.提出了一种基于API Hook技术的Web Services服务质量度量方法.3.本文还实现了一个基于该方法的度量工具原型,并通过客户端和服务端的度量实验以及度量开销的实验证明了该方法的可行性和有效性
Software Quality Assurance
2013Director-Software-Quality-Assurance 经典要求
Developing Quality Metadata
Data and meta<em>data</em> drives the TV production and broadcast scheduling systems. Meta<em>data</em> helps to manage content and when you examine a broadcast infrastructure, a lot of what is happening is to do with the manipulation of nonvideo <em>data</em> formats. Interactive TV and digital text services also require <em>data</em> in large quantities. Managing it, cleaning it, routing it to the correct place at the right time and in the right format are all issues that are familiar to <em>data</em> management professionals inside and outside the media industry. While I wrote this book, I spent a little time working with some developers who build investment-banking systems. Interestingly they face identical problems to my colleagues in broadcasting. I suspected this was the case all along because I have frequently deployed solutions in broadcasting that I learned from projects in nonbroadcast industries. Spend some ‘sabbatical’ time in another kind of industry. It will teach you some useful insights. Workflow in an organization of any size will be composed of many discrete steps. Whether you work on your own or in a large enterprise, the processes are very similar. The scale of the organization just dictates the quantity. The <em>quality</em> needs to be maintained at the highest level in both cases. The Data and Meta<em>data</em> Workflow Tools you choose and use are critical to your success. The key word here is Tools. With good tools, you can “Push the Envelope” and raise your product <em>quality</em>. There has been much discussion about meta<em>data</em> systems and <em>data</em> warehouses. Systems used as <em>data</em> repositories are useful but if you don’t put good <em>quality</em> <em>data</em> in there you are just wasting your time. We need to focus on making sure the <em>data</em> is as good as possible—and stays that way. Raw <em>data</em> is often in somewhat of a mess. There are a series of steps required to clean the <em>data</em> so it can be used. Sometimes even the individual fields need to be broken down so that the meaning can be extracted. This book is not so much about storage systems but more about what gets stored in them. There are defensive coding techniques you can use as avoidance strategies. There are also implications when designing <em>data</em>base schemas. Data entry introduces problems at the outset and needs to be as high <em>quality</em> as possible or the entire process is compromised. The book describes risk factors and illuminates them with real-world case examples and how they were neutralized. Planning your systems well and fixing problems before they happen is far cheaper than clearing up the mess afterwards. This book is designed to be practical. If nontechnical staff read it, they will understand why some of the architectural designs for their systems are hard to implement. For people in the implementation area, they will find insights that help solve some of the issues that confront them. A lot of the advice is in the form of case studies based on genuine experience of building workflows. Some explanation is given about the background to the problem and why it needs to be solved. The material is divided into two parts. Part 1 deals with theory while Part 2 provides many practical examples in the form of tutorials. We lay a foundation for further projects that look inside the media files and examine audio/video storage and the various tools that you can build for manipulating them. Before embarking on that, we need to manage a variety of <em>data</em> and meta<em>data</em> components and get that right first.
reality instead of quality?
SAP在其产品开发中导入agile方法论中的一些思考。作为开发超复杂企业管理软件的超大型软件公司,SAP成功导入了agile,其经验极具参考意义。
sensio premium quality 3D
sensio premium <em>quality</em> 3D
image quality ranking
图像质量等级评估,使用深度学习,对一张图像进行等级划分。python源代码。
Informatica B2B Data Exchange 9.5
Informatica B2B Data Exchange 9.5功能介绍
Quality Center QC资料 QC帮助大全 Quality Center帮助文档
Quality Center帮助文档大全,Quality Center帮助文档大全,Quality Center帮助文档大全
Mercury Quality Center使用说明
Mercury Quality Center使用说明 Mercury Quality Center使用说明
HP Quality Center10 licence.rar
可以使用的HP Quality Center10licence.rar
Quality Center9.0移植笔记
一个讲述QC的移植操作的详细笔记,里面有详细的操作步骤,非常的实用。
Molex Quality Manual
Molex Crimp Qualit Handbook
Advanced Quality System
AQS focuses on identifying improvement opportunities, reducing variation, improving products and processes, improving product design, solving problems, and implementing reliable and efficient processes. Identifying product key characteristics and understanding the processes used in producing key characteristics is an important element in reducing variation and improving product <em>quality</em>.
automotive quality systems handbook
汽车质量手册,TS16949最全解释,适用于研发,生产,质量等工程师使用。
high quality C++
一个小不点的函数,他从三个方面考查: (1)编程风格; (2)出错处理; (3)算法复杂度分析(用于提高性能)。
matlab imag quality measurement
This is an implementation of the algorithm for calculating the Structural SIMilarity (SSIM) index between two images
Six lessons in software quality
six-lessons-in-sw-<em>quality</em> by Rax Black Rax Black是ISTQB培训师, 这是他的一次公开课。
ISO13485-Medical devices — Quality management
Medical devices — Quality management systems — Requirements for regulatory purposes
quality center用户操作手册
<em>quality</em> center用户操作手册
Mercury Quality Center8.2教程
QC8.2教程,包括指定测试需求,计划测试,运行测试,添加和跟踪缺陷,跟踪更改,分析测试流程.......
Quality Center 9破解
Quality Center 9破解含有注册许可证
quality center 10 new
<em>quality</em> center 10 new
Power Quality Problems
Pattern Recognition Methodology for Network-Based Diagnostics of Power Quality Problems
Quality Center 安装文档
附件文档是测试工具<em>quality</em> center的安装帮助
Quality Center使用帮助简介
主要介绍一些最基本的关于Quality center的使用,一些最基本的配置等
Quality Center要点思维导图
Quality Center学习思维导图
Quality of Service Attributes for Diameter
Quality of Service Attributes for Diameter
hp官方Quality Center.pdf
hp官方Quality Center.pdf
Software Quality Engineering
Software Quality Engineering Software Quality Engineering Software Quality Engineering
Quality Center 安装指南
描述QC安装的全部过程。 以及安装过程中会遇到问题的地方。
QC(Quality Center)中文教程
全面中文QC教程,包括QC使用指南、站点管理、项目自定义等
Mercury Quality Center 教程
欢迎使用 Mercury Quality Center 教程!这是一个可由您自己掌握学习进度的 教程,教您使用 Mercury 开发的基于 Web 的测试管理工具 Mercury Quality Center (原名 TestDirector)。 该教程将指导您如何使用 Quality Center 管理应用程序测试流程。它帮助您熟悉 指定测试需求、计划测试、执行测试和跟踪缺陷。它还介绍如何通过创建报告和 图监视测试流程。
Software Quality Assurance Plan
Software Quality Assurance Plan For Database Applications
matlab for image quality evaluation
matlab code for ct image <em>quality</em> evaluation
uci wine quality
UCI<em>数据</em>集 wine <em>quality</em>的红白酒<em>数据</em>CSV文件,用于SVM、贝叶斯等验证
Quality center问题
遇到一个Quality center卸载的问题rnrn当时安装完成后,qc无法使用,则用优化大师把qc卸载掉了rn但是重新安装时,提示:没有卸载干净rnrn不知道该怎末办?怀疑是否注册表的缘故;不知道该怎末重新安装rn
PMP-project quality management
PMP-project <em>quality</em> management质量管理习题集,附有答案详解!
Total Quality Management
Total Quality Management System and relevant technology
LO710_mySAP PLM Quality Notifications
SAP中QM的标准教程,LO710_mySAP PLM Quality Notifications
camera video quality
camera video <em>quality</em>
pro asp.net mvc3 预览版下载
pro asp.net mvc3 framework 预览版, 少2,14章。。 相关下载链接:[url=//download.csdn.net/download/hugejingui/3342164?utm_source=bbsseo]//download.csdn.net/download/hugejingui/3342164?utm_source=bbsseo[/url]
VF教程(详细)下载
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