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Data Quality

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ALSO CALLED: Data Quality Control, Information Quality, Data Quality Assurance, Data Content Quality
DEFINITION: Data quality is the reliability and effectiveness of data, particularly in a data warehouse. Data quality assurance (DQA) is the process of verifying the reliability and effectiveness of data. Maintaining data quality requires going through the data periodically and scrubbing it. Typically this involves updating it, standardizing it, and de-duplicating records to create a single view of the data,  … 
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Data Quality Reports
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Business value key to data governance software selection
sponsored by SearchDataManagement
EBOOK: Data governance software evaluation and selection encompass several critical business considerations beyond features and functionality.
Posted: 12 Jan 2017 | Published: 06 Jan 2017

SearchDataManagement

Analyst Report: Data Quality Tools
sponsored by Trillium Software
RESEARCH CONTENT: Access the report to learn how a leading data quality solution can help you achieve your long-term strategic objectives.
Posted: 02 Dec 2016 | Published: 23 Nov 2016

Trillium Software

Strategies For Effective Big Data Governance And Supporting Analytics Programs
sponsored by IBM
EGUIDE: Governing large and varied sets of big data is difficult. In this expert e-guide, Dr. Anne Smith, Principal Consultant at Alabama Yankee Systems, LLC reveals 7 best practices for instituting effective policies for governing sets of big data. Plus, learn how a solid data governance plan sows the seeds for a successful self-service analytics program.
Posted: 02 Dec 2016 | Published: 02 Dec 2016

IBM

Data Preparation: How To Prepare For BI Success
sponsored by Yellowfin
WHITE PAPER: Discover how a built-in data preparation module can eliminate the cost of using two BI products, and reduce integration challenges. Then, learn about how you can leverage a metadata layer in your BI so that any changes made will be uniformly reflected across all content, and more.
Posted: 29 Nov 2016 | Published: 29 Nov 2016

Yellowfin

The Future of Model Risk Management for Financial Services Firms
sponsored by SAS
WHITE PAPER: This white paper covers the current state of model risk management (MRM) for financial firms, as well as posits some ideas about what the future of financial modeling is going to look like. Inside you'll learn about the impact that new regulatory developments for banks has had on MRM, 5 important new features of modeling technology, and more.
Posted: 10 Nov 2016 | Published: 10 Nov 2016

SAS

A Path to Good Risk Taking Through Data Analytics
sponsored by SAS
WHITE PAPER: This white paper explores the strategic benefit of making analytics an integral part of your risk management plan. Inside, learn 11 principles for enhancing risk management and the way banks are currently leveraging analytics for risk assessment. You'll also find some risk management success stories.
Posted: 10 Nov 2016 | Published: 10 Nov 2016

SAS

Best Practices for Modernizing Enterprise Decision Making
sponsored by SAS
WHITE PAPER: In this resource, 3 professors share insights and best practices for improving your organization's data-informed decision making. Discover the importance of visualizing data, tailoring analytics reports to meet specific needs, cultivating a culture of data-informed decision making, and more.
Posted: 08 Nov 2016 | Published: 08 Nov 2016

SAS

Unleash Transformational Business Change by Modernizing Your Database Technology Platform
sponsored by Cintra/Oracle
WHITE PAPER: Access this white paper to learn why many organizations struggle to develop an integrated technology strategy, and how a strong Oracle database could drive your company's digital transformation. Inside learn the quantifiable benefits of moving to a hyper-converged platform, a strategy for modernizing your Oracle database, and more.
Posted: 07 Nov 2016 | Published: 07 Nov 2016

Cintra/Oracle

Gaining Support for ITAM: Improve IT Operations Through Data Curation
sponsored by BDNA
VIDEO: Tune into this webinar to learn how to enforce enterprise-wide data consistency and improve IT operations with robust ITAM that transforms multi-source data into actionable business insight.
Posted: 03 Nov 2016 | Premiered: 31 Jul 2016

BDNA

Clean Data in Cloud Analytics Removes The Divide Between User and Data
sponsored by SAP
EGUIDE: In this expert e-guide, learn how cloud analytics removes the barrier between business workers and important data. Discover why you should use only quality data in your cloud analytics, and how software platform company ServiceChannel eased the burden on their IT department by deploying a cloud BI platform.
Posted: 02 Nov 2016 | Published: 02 Nov 2016

SAP

Getting a Grip on Content: Empowered Content Collaboration in the Cloud
sponsored by IBM
RESOURCE: Access this resource for insight into how collaboration capabilities can turn content into a competitive advantage and striking the balance between content security and access. Additionally, discover resource requirements for deploying an ECM tool, and learn more about cloud-based content management implementation.
Posted: 19 Oct 2016 | Published: 31 Dec 2015

IBM

Machine Data Analytics Drives the Success of DevOps
sponsored by Splunk
WHITE PAPER: This white paper explores how a consolidated data analytics platform based around the use of machine data can help you foster an agile and responsive DevOps culture. Discover how you can create a tight feedback loop that measures, reports, and ultimately, demonstrates the success of DevOps.
Posted: 14 Oct 2016 | Published: 14 Oct 2016

Splunk

Managing A Strong Data Governance Program
sponsored by TechTarget
RESOURCE: Developing a successful data governance strategy requires careful planning, the right people and appropriate tools and technologies. In this expert guide, Data Governance 101: Build Your Program, explore best practices for managing data governance projects, the role of data stewards and the benefits of adopting data stewardship programs.
Posted: 04 Oct 2016 | Published: 04 Oct 2016

TechTarget

Taking Your Enterprise Data Governance Plan Up a Notch
sponsored by Veritas
EGUIDE: In this expert e-guide, we explore how to create an enterprise data governance framework. Uncover some strategic best practices for big data governance so that you can boost data quality and prevent critical inconsistencies.
Posted: 10 Oct 2016 | Published: 05 Oct 2016

Veritas

How to Narrow Down Your Choices for Buying a Data Governance Tool
sponsored by Veritas
EGUIDE: In this expert e-guide, we explore key evaluation factors for selecting the right data governance tool to suit the needs of your organization. Find out which metrics matter most when it comes to picking your tool, like handling metadata objects, managing data quality, addressing unstructured data, and more.
Posted: 10 Oct 2016 | Published: 05 Oct 2016

Veritas

How To Know If Your Organization Is Ready For Data Governance Software
sponsored by Veritas
EGUIDE: It's important to ensure your organization is ready for a governance tool, or your software purchase is likely to fall flat. This e-guide takes a look at three different scenarios where data governance tools are often used to help you determine if your organization is ready for data governance software.
Posted: 10 Oct 2016 | Published: 05 Oct 2016

Veritas

How to Select the Right BI Analytics Tool
sponsored by NEC Corporation of America
EGUIDE: This expert e-guide will help you to decide which type of BI analytics platform is right for you, and the best way you can implement it. Find out if your business is in need of a large program, or if a newer, smaller platform is best. Then learn how to compile a checklist of the capabilities your new analytics program must have.
Posted: 29 Sep 2016 | Published: 29 Sep 2016

NEC Corporation of America

Gathering, Organizing, and Presenting Your Data
sponsored by NEC Corporation of America
EGUIDE: In this expert e-guide we walk you through the best way to organize and present your data, and explain how you can access large amounts of information rapidly. You'll learn how to create a collaborative data governance program, implement data visualization techniques, avoid inconsistent analysis by removing the need for data sampling, and more.
Posted: 29 Sep 2016 | Published: 29 Sep 2016

NEC Corporation of America

How to Optimize Your Master Data Management Strategy
sponsored by IBM
EGUIDE: This expert e-guide explores an integrated approach to master data management (MDM) that incorporates an enterprise data governance program. Inside, you'll find out how to optimize your data quality strategy and learn how to garner business support for your MDM initiative.
Posted: 26 Sep 2016 | Published: 21 Sep 2016

IBM

Simplifying and Accelerating Master Data Management
sponsored by Information Builders
WHITE PAPER: Many MDM projects are failing due to time and effort requirements. This white paper discusses the problems that face traditional MDM approaches and data mastering innovations. Leverage best practices and new technology to improve the view of your data across the enterprise.
Posted: 30 Aug 2016 | Published: 31 Dec 2015

Information Builders

The Top 5 "Worst Practices" In Business Intelligence
sponsored by Information Builders
WHITE PAPER: Even the best-run businesses in the world can commit the common missteps that lead to lukewarm BI performance. This white paper identifies and explores the 5 "worst practices" that contribute to poor BI deployments. Find out how they negatively impact BI from both a technology and a business perspective and learn how to avoid them.
Posted: 30 Aug 2016 | Published: 30 Aug 2016

Information Builders

Information Management and MDM: Getting the Most from Clinical Data
sponsored by Information Builders
WHITE PAPER: This white paper examines the obstacles healthcare payers experience when planning and implementing a strategy for collecting, managing, and exchanging clinical data for value-based care. Discover how to unlock truly actionable data with an integrated approach to information management, data quality, master data management, and more.
Posted: 29 Aug 2016 | Published: 29 Aug 2016

Information Builders

The 8 Worst Practices in Master Data Management and How to Avoid Them
sponsored by Information Builders
WHITE PAPER: This white paper explores the 8 "worst practices" of master data management. Find out how to navigate these obstacles on the road to a successful MDM and data governance program for big data.
Posted: 29 Aug 2016 | Published: 29 Aug 2016

Information Builders

7 Key Challenges to Value-Based Care: Ensuring Patient-Centered Care With Information Management
sponsored by Information Builders
WHITE PAPER: This white paper explores how to address some of the challenges of moving towards value-based healthcare with a strategy for improving the way patient data is collected, managed, and exchanged. Access now to find out more about an integrated approach to master data management, data quality, information management, and more.
Posted: 29 Aug 2016 | Published: 29 Aug 2016

Information Builders

6 Issues That Can Derail Your Big Data Initiative
sponsored by Information Builders
WHITE PAPER: 55% of big data projects are never finished. Your Hadoop ecosystem is more important to these projects than you may realize, so it's important to fully understand the role it plays. This white paper discusses the 6 primary issues that are knocking big data projects off the tracks, and how to get your data management back on track.
Posted: 26 Aug 2016 | Published: 26 Aug 2016

Information Builders
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DATA QUALITY DEFINITION (continued): …  even even if it is stored in multiple disparate systems. There are many vendor applications on the market to make this job easier. Because data quality is so important from a business perspective, many large companies employ a data steward to be in charge of data quality. In spite of this, Gartner Inc. forecasted that 25% of critical data within Fortune 1000 companies would continue to be inaccurate through 2007. A Gartner study says that poor quality customer data costs U.S. business an estimated $611 billion dollars a year in postage, printing, and staff overhead.Getting started with data quality … 
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