data governance program

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Published By: DATAVERSITY     Published Date: Jun 14, 2013
This report analyzes many challenges faced when beginning a new Data Governance program, and outlines many crucial elements in successfully executing such a program. “Data Governance” is a term fraught with nuance, misunderstanding, myriad opinions, and fear. It is often enough to keep Data Stewards and senior executives awake late into the night. The modern enterprise needs reliable and sustainable control over its technological systems, business processes, and data assets. Such control is tantamount to competitive success in an ever-changing marketplace driven by the exponential growth of data, mobile computing, social networking, the need for real-time analytics and reporting mechanisms, and increasing regulatory compliance requirements. Data Governance can enhance and buttress (or resuscitate, if needed) the strategic and tactical business drivers every enterprise needs for market success. This paper is sponsored by: ASG, DGPO and DebTech International.
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data, data management, data governance, data steward, dataversity, research paper
    
DATAVERSITY
Published By: CA Technologies     Published Date: Oct 22, 2015
As the interest in managing information and enforcing corporate data management policies increases, data governance programs to manage data sets are becoming more and more vital to the business operation. However, in this rush for data governance programs, sometimes the true utility and importance of metadata can be missed. In this white paper, David Loshin of Knowledge Integrity, Inc. discusses the importance of data governance and the role of metadata management as a way to empower data governance and enforce data policies.
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white paper, metadata, data management, data modeling, david loshin, data governance, data governance strategy
    
CA Technologies
Published By: First San Francisco Partners     Published Date: Sep 03, 2014
This white paper discusses how awareness, ownership and accountability are key to activating and engaging people to adopt new data governance initiatives and the related policies and processes. It provides you with information on how your organization can ensure that the data stewards adopt the new data governance policies and processes.
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data, data management, data governance, data governance program
    
First San Francisco Partners
Published By: CA Technologies     Published Date: Dec 03, 2015
This 2nd paper in a 3-part series by David Loshin explores some challenges in bootstrapping a data governance program, and then considers key methods for using metadata to establish the starting point for data governance. The paper will focus on how metadata management facilitates progress along three facets of the data governance program including assessment, collaboration and operationalization.
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CA Technologies
Published By: CA Technologies     Published Date: Feb 25, 2016
As combinations of both internal and externally-imposed business policies imply dependencies on managed data artifacts, organizations are increasingly instituting data governance programs to implement processes for ensuring compliance with business expectations. One fundamental aspect of data governance involves practical application of business rules to data assets based on data elements and their assigned values. Yet despite the intent of harmonizing data element definitions and resolution of data semantics and valid reference values, most organizations rarely have complete visibility into the metadata associated with enterprise data assets.
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CA Technologies
Published By: Embarcadero     Published Date: Feb 28, 2013
A recent Data Governance Benchmarking Survey reported that only 23% of organizations have a reasonable command of data compliance. A shockingly low number. We as data professionals cannot solve the problem alone.
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white paper, dataversity, data governance, karen lopez, embarcadero, data management
    
Embarcadero
Published By: DATAVERSITY     Published Date: Jun 17, 2013
This report analyzes many challenges faced when beginning a new Data Governance program, and outlines many crucial elements in successfully executing such a program. “Data Governance” is a term fraught with nuance, misunderstanding, myriad opinions, and fear. It is often enough to keep Data Stewards and senior executives awake late into the night. The modern enterprise needs reliable and sustainable control over its technological systems, business processes, and data assets. Such control is tantamount to competitive success in an ever-changing marketplace driven by the exponential growth of data, mobile computing, social networking, the need for real-time analytics and reporting mechanisms, and increasing regulatory compliance requirements. Data Governance can enhance and buttress (or resuscitate,if needed) the strategic and tactical business drivers every enterprise needs for market success.
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research paper, data, data management, data governance, data steward
    
DATAVERSITY
Published By: SAS     Published Date: Aug 28, 2018
With the amount of information in the digital universe doubling every two years, big data governance issues will continue to inflate. This backdrop calls for organizations to ramp up efforts to establish a broad data governance program that formulates, monitors and enforces policies related to big data. Find out how a comprehensive platform from SAS supports multiple facets of big data governance, management and analytics in this white paper by Sunil Soares of Information Asset.
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SAS
Published By: IBM     Published Date: Jul 26, 2017
Business leaders are eager to harness the power of big data. However, as the opportunity increases, ensuring that source information is trustworthy and protected becomes exponentially more difficult. If not addressed directly, end users may lose confidence in the insights generated from their data—which can result in a failure to act on opportunities or against threats. Information integration and governance must be implemented within big data applications, providing appropriate governance and rapid integration from the start. By automating information integration and governance and employing it at the point of data creation, organizations can boost confidence in big data. A solid information integration and governance program must become a natural part of big data projects, supporting automated discovery, profiling and understanding of diverse data sets to provide context and enable employees to make informed decisions. It must be agile to accommodate a wide variety of data and seamle
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mdm, big data, automation, organization
    
IBM
Published By: MarkLogic     Published Date: Jun 21, 2017
Global financial organizations are facing increasing demands from the business for more granularity, transparency, reporting and security. If you’re on the IT side, you know this adds a different set of ‘mores’ to the equation: More duplication, delays, and people. What’s the net-net? More cost and more risk. You can balance the scales to satisfy those demands. And it starts with thinking differently about data management. Our financial services technology experts will explore the implications of governance, risk and compliance (GRC) imperatives. You’ll learn: • Why data is at the heart of an effective and dynamic GRC strategy • Why technological capabilities used to enable standard GRC programs can reduce transparency and prevent you from gaining a holistic view of your data • A new approach to data can provide the business with complete transparency • Review a sample regulatory reporting architecture Stop burning time on tooling — and start building a dynamic GRC strategy that can
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banking, financial services, data management, silos, data strategy, transparency, data governance, regulation, data architecture, compliance, reporting
    
MarkLogic
Published By: SAS     Published Date: Jun 06, 2018
Written by Jill Dyche and Kimbery Nevala, 10 Mistakes to Avoid When Launching your Data Governance Program lays out a comprehensive list of issues that can trip up an organization as it gets started with DG. Learn how to use good judgment and sound decision making to sidestep these common issues.
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SAS
Published By: SAS     Published Date: Mar 14, 2014
Judgment is a process and not a single event. Good judgment and sound decision making are at the heart of data governance.
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sas, data governance, data management, data measurement, governance policy, payback, tactical, structured, data center
    
SAS
Published By: SAS     Published Date: Mar 14, 2014
This Q&A with Tom Davenport, Director of Research for the International Institute for Analytics (IIA), will help you understand how analytics is evolving, where you need to go, and how to get there.
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sas, data categorization, retrieval and quality, data visualization, data governance program, data management, data quality, business objectives, quality data, accuracy, lineage, structural consistency, relevant metrics, analytics, analytical study, visualization deployment, deployment, institute for analytics, analytical applications, business intelligence
    
SAS
Published By: SAS     Published Date: Mar 14, 2014
This paper explores the challenges organizations have today in implementing a data governance program via an actual business case. It highlights SAS technology that can help you solve many of those challenges.
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sas, data categorization, retrieval and quality, data visualization, data governance program, data management, data quality, business objectives, quality data, accuracy, lineage, structural consistency, relevant metrics, business relevance, visualization deployment, deployment, institute for analytics, data center
    
SAS
Published By: SAS     Published Date: Mar 14, 2014
This report examines how data visualization can help organizations unleash the full value of information, and outlines key considerations to guide the solution evaluation process.
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sas, data categorization, retrieval and quality, data visualization, data governance program, data management, data quality, business objectives, quality data, accuracy, lineage, structural consistency, relevant metrics, business relevance, visualization deployment, deployment, institute for analytics, data center
    
SAS
Published By: SAS     Published Date: Mar 14, 2014
Managing expectations before, during and after the adoption of visualization software is crucial. Users should know what the rollout process will look like and how it will take place, and have clear goals for using the tool. Make sure that the desired outcome isn’t just look-and-feel. Creating beautiful charts and graphs is not a substitute for practical business decisions.
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sas, data categorization, retrieval and quality, data visualization, data governance program, data management, data quality, business objectives, quality data, accuracy, lineage, structural consistency, relevant metrics, business relevance, visualization deployment, deployment, institute for analytics, data center
    
SAS
Published By: SAS     Published Date: Mar 14, 2014
This paper explores ways to qualify data control and measures to support the governance program. It will examine how data management practitioners can define metrics that are relevant.
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sas, data quality, business objectives, quality data, accuracy, lineage, structural consistency, relevant metrics, business relevance, measured value, emergent patterns, quality metrics, potential classifications, data analyst, scorecard, reporting the scorecard, improve scorecard, business process
    
SAS
Published By: SAS     Published Date: Mar 14, 2014
Jill Dyche and SpectraDynamo explains the importance of understanding how to manage data and issues regarding data categorization, retrieval and quality.
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sas, data categorization, retrieval and quality, spectradynamo, telemetry data, data governance program, data management, data quality, business objectives, quality data, accuracy, lineage, structural consistency, relevant metrics, business relevance, measured value, emergent patterns, quality metrics, data center
    
SAS
Published By: IBM     Published Date: Jul 05, 2018
IBM® Information Governance Catalog helps you understand your information and foster collaboration between business and IT by establishing a common business vocabulary on the front end, and managing data lineage on the back end. By leveraging the comprehensive capabilities in Information Governance Catalog, you are better able to align IT with your business goals. Information Governance Catalog helps organizations build and maintain a strong data governance and stewardship program that can turn data into trusted information. This trusted information can be leveraged in various information integration and governance projects, including big data integration, master data management (MDM), lifecycle management, and security and privacy initiatives. In addition, Information Governance Catalog allows business users to play an active role in information-centric projects and to collaborate with their IT teams without the need for technical training. This level of governance and collaboration c
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IBM
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