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data quality management

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By: AWS     Published Date: Oct 31, 2018
Today AMP Ltd. integrates and manages its customer data more efficiently using a single Talend platform that enables data reconciliation, quality-assessment dashboards, and metadata management. Ten billion rows of AMP Ltd. data are computed in less than an hour. In this webinar you will learn how you can modernize your data architecture to help you collect and validate data, act upon it, and transform your organization for the digital age.
Tags : amp, cloud, data, customer, reconciliation, digital
     AWS
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.
Tags : compliance, email archiving, data quality, records management, personal email, enterprise email, email security, c2c
     C2C Systems, Inc.
By: Claravine     Published Date: Jan 03, 2019
Marketers have long struggled with the simple task of knowing which marketing spend is truly effective, and how to optimize that spend. At the heart of the issue lies the challenge of ensuring the data quality and consistency exists to make decisions based on real intelligence. Why is this a problem? First, effective tracking is reliant on the consistent, complete application of campaign tracking codes and associated metadata, which has traditionally been a manual, ungoverned process. Adding to this complexity has been the dramatic expansion of digital marketing point solutions, and the disparate teams expected to execute across each of these channels and geographies. The result is what you would expect—highly inaccurate, incomplete, and inconsistent data that must be manually cleaned before reporting is possible. Fortunately a solution exists. Progressive marketing leaders are implementing Digital Experience Data Management (DXDM), ensuring the rich, consistent insights critical to ma
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     Claravine
By: Dun & Bradstreet     Published Date: Mar 03, 2017
Complexity, globalization and digitalization are just some of the elements at play in the risk landscape—and data is becoming a core part of understanding and navigating risk. How do modern finance leaders view, navigate and manage enterprise risk with data? Dun & Bradstreet surveyed global finance leaders across industries and business types. Here are the top trends that emerged from the study: 1. The Enterprise Risk & Strategy Disconnect—Finance leaders are using data and managing risk programs, but over 65% of finance leaders say there’s missing link between risk and strategy. 2. The Risks of the Use and Misuse of Data—Up to 50% of the data used to manage modern risk is disconnected. Only 15% of leaders are confident about the quality of their data. 3. Risky Relationships—Only 20% of finance leaders say the data they use to manage risk is fully integrated and shared. Download the study to learn how finance leaders are approaching data and enterprise risk management
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     Dun & Bradstreet
By: ETQ     Published Date: Jul 10, 2019
According to Gartner, "supply chain leaders responsible for quality management are shifting to software solutions that standardize processes, optimize data and ensure compliance. This research provides guidance for structuring a process for QMS software selection." Download this Gartner Analyst Guide to learn: Key challenges in the QMS software selection processes What to expect from different QMS solutions across the market Analysis of the current state of quality management to help define software requirements Self assessment questions and commonly sought QMS system functionalities to use in your decision making process
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     ETQ
By: Group M_IBM Q119     Published Date: Jan 08, 2019
The discipline of data quality assurance ensures that data is "fit for purpose" in the context of existing business operations, analytics and emerging digital business scenarios. It covers much more than just technology. It includes program management, roles, organizational structures, use cases and processes (such as those for monitoring, reporting and remediating data quality issues). It is also linked to broader initiatives in the field of enterprise information management (EIM), including information governance and master data management (MDM)
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     Group M_IBM Q119
By: Hitachi Vantara     Published Date: Mar 20, 2018
ESG Lab performed hands-on evaluation and testing of the Hitachi Content Platform portfolio, consisting of Hitachi Content Platform (HCP), Hitachi Content Platform Anywhere (HCP Anywhere) online file sharing, Hitachi Data Ingestor (HDI), and Hitachi Content Intelligence (HCI) data aggregation and analysis. Testing focused on integration of the platforms, global access to content, public and private cloud tiering, data quality and analysis, and the ease of deployment and management of the solution.
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     Hitachi Vantara
By: HP     Published Date: Jul 22, 2014
HP offers an approach to the modern data center that addresses systemic limitations in storage by offering Tier-1 solutions designed to deliver the highest levels of flexibility, scalability, performance, and quality—including purpose-built, all-flash arrays that are flash-optimized without being flash-limited. This white paper describes how, through the incorporation of total quality management throughout each process and stage of development, HP delivers solutions that exceed customer quality expectations, using HP 3PAR StoreServ Storage as an example.
Tags : 3par, storeserv, storage, data, solutions, flash
     HP
By: IBM     Published Date: Dec 12, 2006
The purpose of this paper is to highlight the issues, requirements, and technologies available for automated advanced name recognition.
Tags : business process automation, data integration, data quality, information management, customer service, data management, enterprise software, contact management
     IBM
By: IBM     Published Date: Dec 30, 2008
Does your business need to safeguard information, keep auditors and regulators satisfied, and improve data quality? Data governance is the answer. This informative video outlines the latest challenges and best practices in data governance. IBM data governance solutions help businesses with:• Audit and reporting • Data architecture/infrastructure • Data quality • Information lifecyle management • Metadata/business glossaries • Organizational design/development • Policy/risk management • Security/privacy/compliance • Stewardship/value creation
Tags : ibm, data governance, safeguard information, data quality, data architecture, data infrastructure, information lifecycle management, metadata
     IBM
By: IBM     Published Date: Sep 10, 2009
IDC studied 14 mobile and fixed-line service providers that implemented Tivoli Netcool and found that IBM Tivoli Netcool can help in big ways. It reduces costs by improving operational efficiencies and still allows you to deliver a high-quality custom management.
Tags : ibm, tivoli, netcool, roi, future proofing, data integration, operations productivity, cost reduction
     IBM
By: IBM     Published Date: Aug 30, 2010
Adopting an Integrated Data Management strategy can be a highly effective way to help IT support business growth, facilitate data governance and manage costs.
Tags : ibm, back-up, data quality, database management, knowledge and data management, storage management, data management, databases
     IBM
By: IBM     Published Date: Jan 09, 2014
According to Dr. Barry Devlin of 9sight Consulting, the truth behind all the talk about big data and the possibilities it can offer is not hard to see, provided that organizations are willing to return to the principles of good data management processes.
Tags : ibm, big data, 9sight consulting, data, it management, maximize business, deployment, business opportunities
     IBM
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.
Tags : ibm, integrating big data, governing big data, integration, best practices, big data, ibm infosphere, it agility
     IBM
By: IBM     Published Date: May 28, 2014
Read the whitepaper to find out how one client improved business value of their data by implementing InfoSphere Optim processes and technologies.
Tags : ibm, data lifecycle management, infosphere optim, integrating big data, governing big data, integration, best practices, big data
     IBM
By: IBM     Published Date: Feb 24, 2015
Big data analytics offer organizations an unprecedented opportunity to derive new business insights and drive smarter decisions. The outcome of any big data analytics project, however, is only as good as the quality of the data being used. Although organizations may have their structured data under fairly good control, this is often not the case with the unstructured content that accounts for the vast majority of enterprise information. Good information governance is essential to the success of big data analytics projects. Good information governance also pays big dividends by reducing the costs and risks associated with the management of unstructured information. This paper explores the link between good information governance and the outcomes of big data analytics projects and takes a look at IBM's StoredIQ solution.
Tags : big data, ibm, big data outcomes, information governance, big data analytics
     IBM
By: IBM     Published Date: Apr 06, 2015
Big data analytics offer organizations an unprecedented opportunity to derive new business insights and drive smarter decisions. The outcome of any big data analytics project, however, is only as good as the quality of the data being used. Although organizations may have their structured data under fairly good control, this is often not the case with the unstructured content that accounts for the vast majority of enterprise information. Good information governance is essential to the success of big data analytics projects. Good information governance also pays big dividends by reducing the costs and risks associated with the management of unstructured information. This paper explores the link between good information governance and the outcomes of big data analytics projects and takes a look at IBM's StoredIQ solution.
Tags : big data, analytics, unstructured content, enterprise information, ibm, security, storage
     IBM
By: IBM     Published Date: Jul 13, 2015
This paper discusses how InfoSphere capabilities can be used to create comprehensive and accurate 3600 views of your customers from internal and external sources.
Tags : crm cloud solution, salesforce, user productivity, data enrichment, security, data quality, customer data search, customer relationship management
     IBM
By: IBM     Published Date: Jul 13, 2015
This ebook explores how an enhanced 360-degree view of the customer optimizes and facilitates more personalized customer interactions.
Tags : customer centric organizations, crm, customer usability, personalized interactions, big data, data quality, data management, internet marketing
     IBM
By: IBM     Published Date: Apr 18, 2016
"Built using the IBM® InfoSphere® Information Server, IBM BigInsights® BigIntegrate and BigInsights BigQuality provide the end-to-end information integration and governance capabilities that organizations need."
Tags : ibm, big data, ibm infosphere, ibm biginsights, ibm bigintegrate, ibm bigquality, data management, data quality
     IBM
By: IBM     Published Date: Jul 06, 2016
Built using the IBM® InfoSphere® Information Server, IBM BigInsights® BigIntegrate and BigInsights BigQuality provide the end-to-end information integration and governance capabilities that organizations need.
Tags : ibm, big data, ibm infosphere, ibm biginsights, ibm bigintegrate, ibm bigquality, data management, data quality
     IBM
By: IBM     Published Date: Jul 08, 2016
Big data analytics offer organizations an unprecedented opportunity to derive new business insights and drive smarter decisions. The outcome of any big data analytics project, however, is only as good as the quality of the data being used. Although organizations may have their structured data under fairly good control, this is often not the case with the unstructured content that accounts for the vast majority of enterprise information. Good information governance is essential to the success of big data analytics projects. Good information governance also pays big dividends by reducing the costs and risks associated with the management of unstructured information. This paper explores the link between good information governance and the outcomes of big data analytics projects and takes a look at IBM's StoredIQ solution.
Tags : ibm, idc, big data, data, analytics, information governance
     IBM
By: IBM     Published Date: Oct 13, 2016
Data quality and master data management in a hybrid environment
Tags : ibm, mdm, big data, ibm infosphere
     IBM
By: IBM     Published Date: Oct 18, 2016
Big data analytics offer organizations an unprecedented opportunity to derive new business insights and drive smarter decisions. The outcome of any big data analytics project, however, is only as good as the quality of the data being used. Although organizations may have their structured data under fairly good control, this is often not the case with the unstructured content that accounts for the vast majority of enterprise information. Good information governance is essential to the success of big data analytics projects. Good information governance also pays big dividends by reducing the costs and risks associated with the management of unstructured information. This paper explores the link between good information governance and the outcomes of big data analytics projects and takes a look at IBM's StoredIQ solution.
Tags : ibm, idc, big data, data, analytics, information governance
     IBM
By: IBM     Published Date: Jan 27, 2017
Cloud-based data presents a wealth of potential information for organizations seeking to build and maintain a competitive advantage in their industry. However, as discussed in “The truth about information governance and the cloud,” most organizations will be confronted with the challenging task of reconciling their legacy on-premises data with new, third-party cloud-based data. It is within these “hybrid” environments that people will look for insights to make critical decisions.
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     IBM
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