data quality

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Published By: IBM     Published Date: Mar 24, 2009
Electronics and Software Engineering are quickly merging with traditional Mechanical Engineering to create a new paradigm in auto manufacturing: Mechatronics. Industry experts predict that this shift will bring about profound advances in automotive product development. Unfortunately, existing IT and process infrastructures do not provide sufficient capabilities to support the new paradigm: multiple data silos, a lack of standardized processes, and integration issues on a tool level (Mechanical, Electronic, Software) continue to pose serious obstacles to development efficiency, and remain a frequent source of delays, quality issues and cost increases.
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ibm, ibm telelogic, automotive system design, mechanical engineering, mechatronics, oems, electronic stability programs, esp
    
IBM
Published By: OutlookSoft     Published Date: Aug 21, 2009
An effective corporate performance management (CPM) solution leverages a unified application for all key business processes, a centralized database ensuring the highest level of data accuracy and consistency, and provides critical decision-making information in real-time. Read this insightful white paper to learn more.
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performance management, business management, business process management, bpm, data quality, business decision, business metrics, outlook soft
    
OutlookSoft
Published By: Soffront     Published Date: Aug 21, 2009
How marketing automation and CRM can help a mid-sized business consolidate data, improve customer information, streamline marketing efforts, and take full advantage of marketing campaigns.
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crm, smb, smbs, data consolidation, data quality, application integration, marketing, marketing roi
    
Soffront
Published By: TriTuns Innovation     Published Date: Nov 14, 2006
This paper examines the nature, cause and impact of data quality problems in typical IT system implementations.  It argues that the extent and impact of poor data quality is largely misunderstood and often ignored.
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data quality, data protection, data improvement, improve data, trituns, trituns innovation, data management
    
TriTuns Innovation
Published By: SoftLanding Systems     Published Date: Nov 18, 2006
This no-nonsense primer covers the benefits and basic principles of good testing, offers practical advice for getting the most out of your testing efforts, and pinpoints several areas where automation will help you achieve the most cost-effective results.
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software testing, quality assurance, application testing, test and measurement, database development, quality assurance, scripting, software testing
    
SoftLanding Systems
Published By: Siperian     Published Date: Jan 24, 2007
Master Data Management is a cohesive strategy for managing all master data domains.  Where is your organization most likely to derive business value from a Master Data Management solutions?  This report answers these questions and details the path forward:  Adaptive Master Data Management.
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data management, master data management, mdm, business intelligence, data integration, data quality, siperian
    
Siperian
Published By: Siperian     Published Date: Jan 24, 2007
Discover the essential steps to delivering a solid business case for the right customer-centric MDM architecture and achieve maximum ROI.
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roi, data management, return on investment, master data management, mdm, data integration, data quality, siperian
    
Siperian
Published By: BusinessObjects     Published Date: Jan 30, 2007
Download this step by step guide to learning how mid-size companies can benefit from Business Intelligence. You'll learn the benefits of BI and why mid-size companies need it for effective decision-making and improved results.
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performance management, data quality, msrs, microsoft reporting services, cognos 8, cognos, powerplay, cognos reportnet
    
BusinessObjects
Published By: C2C Systems, Inc.     Published Date: Mar 15, 2007
This paper considers the use of email archives for compliance. It will also review how archives are trusted and look at what has to be done to ensure that integrity is maintained throughout the chain of events that take place within an email archive environment.
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compliance, email archiving, data quality, records management, personal email, enterprise email, email security, c2c
    
C2C Systems, Inc.
Published By: Informatica     Published Date: Sep 28, 2007
David Loshin, consultant and author talked to Karen Hsu about Informatica's data quality, unstructured data and data governance solutions. Karen highlighted customers like Navteq and Humberside Police's innovative use of Informatica.
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b-eye, business intelligence, data integration, karen hsu, interview, informatica, crm, customer relationship management
    
Informatica
Published By: Informatica     Published Date: Sep 28, 2007
The purpose of this white paper is to outline the importance of data quality with reference to single view of customer. In any organization SVC is the foundation of successful customer relationship management (CRM).
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crm, data quality, data integrity, customer relationship, informatica, svc, data management
    
Informatica
Published By: Marketo     Published Date: Nov 04, 2011
Knowing the right questions to ask makes a world of difference when making a purchase. To ensure you make the most out of your reference calls, use this list of valuable questions you should always ask. Topics range from CRM integration, support experience and implementing functions like lead scoring, lead nurturing and data quality.
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marketo, reference call, crm integration, white paper, marketing, data quality
    
Marketo
Published By: BMC Control M     Published Date: Apr 01, 2009
Listen in as Sentrigo interviews Dr. Charles Popper, who discusses specific data integrity and security requirements for the pharma sector. Dr. Popper will address how to enforce the proper balance of information sharing and database protection, without compromising high-quality research.
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platforms, data management
    
BMC Control M
Published By: SAS     Published Date: Apr 16, 2015
Ecclesiastical uses SAS® to improve data quality to make better decisions that enhance the reputation of the business, affect millions of pounds of risk selection/underwriting and help to establish optimum reinsurance levels. Millions of pounds hang on decisions around reinsurance and risk selection. Achieving the best possible outcome means taking data and turning it into ‘decision-making gold’. The key is to have good data going into the process.
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SAS
Published By: Trillium Software     Published Date: Jun 06, 2011
The second Web seminar in the series is titled "Data Governance". Learn how Digital River successfully implemented Data Governance across their organization.
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trillium software, operational data quality, upstream operational systems, data governance, data monitoring, businessprocesses, digital river, data management
    
Trillium Software
Published By: Trillium Software     Published Date: Jun 06, 2011
The fourth Web seminar in the series is titled "Tips, Tools & Best Practices" which shows how you can learn to deliver high performance data quality in real-time.
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trillium software, operational data quality, odq, performance management, real-time transactions, high performance data quality, business processes optimization, information integrity
    
Trillium Software
Published By: Optis     Published Date: Mar 07, 2013
Integrating leave and workforce data doesn’t have to be overly complicated. With the right plans, you can make the business case to implement an integrated database so you can get the people answers you need.
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integrated workforce database,   implementing integrated systems,   data quality management,   value of integrated data,   people data management,   disparate people data,   analyze leave data,   employment data
    
Optis
Published By: Oracle     Published Date: Nov 08, 2017
Webcast on why choose Oracle Cloud solutions
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oracle. database. cloud, enterprise, network, quality assurance, storage management, servers
    
Oracle
Published By: IBM     Published Date: May 02, 2014
The end-to-end information integration capabilities of IBM® InfoSphere® Information Server are designed to help organizations understand, cleanse, monitor, transform and deliver data—as well as collaborate to bridge the gap between business and IT.
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ibm, integrating big data, governing big data, integration, best practices, big data, ibm infosphere, it agility
    
IBM
Published By: IBM     Published Date: May 02, 2014
This eBookoutlines the best practices for data lifecycle management and how InfoSphere Optimsolutions enable organizations to support and implement them.
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ibm, integrating big data, governing big data, integration, best practices, big data, ibm infosphere, it agility
    
IBM
Published By: GE Healthcare     Published Date: Feb 23, 2015
Southwestern Ontario Diagnostic Imaging Network relies on Centricity™ Clinical Archive to connect 62 hospitals with disparate PACS & RIS systems, resulting in reduced storage costs and data duplication and increased productivity and enhanced quality of care. Learn more in this case study. Centricity Clinical Archive includes the following product components: Centricity Enterprise Archive, Universal Viewer ZFP, Caradigm eHIE, Centricity Clinical Gateway, NextGate MatchMetrix EMPI, PACSGEAR PacsSCANTM
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xds, cross enterprise document sharing, unified view of patient images, archive & storage, image sharing & management, vendor neutral archive (vna), centricity clinical archive, mobile image capture
    
GE Healthcare
Published By: Delphix     Published Date: Apr 14, 2015
Current test data management solutions are flawed in at least one key dimension. Technologies in the emerging Data as a Service (DaaS) category bring the benefits of virtualization to application data, delivering high-quality test data with both speed and efficiency.
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Delphix
Published By: AWS     Published Date: Jun 11, 2019
Join us to learn why Human-in-the-Loop training data should be powering your machine learning (ML) projects and how to make it happen. If you’re curious about what human-in-the-loop machine learning actually looks like, join Figure Eight CTO Robert Munro and AWS machine learning experts to learn how to effectively incorporate active learning and human-in-the-loop practices in your ML projects to achieve better results. You'll learn: When to use human-in-the-loop as an effective strategy for machine learning projects How to set up an effective interface to get the most out of human intelligence How to ensure high-quality, accurate data sets When: Available On Demand (please register to view) Who Should Attend: IT leaders and professionals, line-of-business managers, business decision makers, data scientists, developers, and other experts interested in implementing AI/ML on the cloud are encouraged to attend this webinar. AWS Speaker: Chris Burns, Solutions Architect Figure Eight Spea
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AWS
Published By: Cox Business     Published Date: Dec 19, 2016
Businesses need to plan for unforeseen events that can disrupt productivity, impair the customer experience, and possibly even threaten a business’s existence. A disruption every business needs to plan for is any event that destroys valuable data, inhibits access to data, or causes downtime of core applications. Consider the staggering amount of information your company stores electronically. What if an unforeseen event destroyed all financial records, client contacts, and application data? You wouldn’t be able to send customers accurate invoices. Your marketing efforts might be undermined. You would lack key metrics for measuring quality, profitability, and more. The losses could be staggering. In every aspect of life, it’s smart to plan for unexpected events. That’s especially true for two plans every business must have: a disaster recovery plan and a business continuity plan.
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Cox Business
Published By: Dun & Bradstreet     Published Date: Feb 21, 2017
As the volume of data coming into organizations – from both internal and external sources – continues to grow and makes its way across departmental systems in many different formats, there is a critical need to create a single, holistic view of the key data entities in common use across the enterprise. Master Data Management (MDM) aims to accomplish this goal. Not surprisingly, MDM has become a significant priority for global enterprises, with the market expected to triple from $9.4B to $26.8B by 2020 according to analysts. The reality, though, is that while seemingly everyone is investing heavily in the tools to manage data, few are putting a great enough emphasis on the data itself. And that’s a problem. Poor data quality is said to be costing businesses $3.1 trillion annually – and that’s just in the US alone. The information being put into MDM tools must be mastered first and foremost.
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managing data, data management insight, mdm, master data management
    
Dun & Bradstreet
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