information governance

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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: TopQuadrant     Published Date: Mar 21, 2015
Data management is becoming more and more central to the business model of enterprises. The time when data was looked at as little more than the byproduct of automation is long gone, and today we see enterprises vigorously engaged in trying to unlock maximum value from their data, even to the extent of directly monetizing it. Yet, many of these efforts are hampered by immature data governance and management practices stemming from a legacy that did not pay much attention to data. Part of this problem is a failure to understand that there are different types of data, and each type of data has its own special characteristics, challenges and concerns. Reference data is a special type of data. It is essentially codes whose basic job is to turn other data into meaningful business information and to provide an informational context for the wider world in which the enterprise functions. This paper discusses the challenges associated with implementing a reference data management solution and the essential components of any vision for the governance and management of reference data. It covers the following topics in some detail: · What is reference data? · Why is reference data management important? · What are the challenges of reference data management? · What are some best practices for the governance and management of reference data? · What capabilities should you look for in a reference data solution?
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data management, data, reference data, reference data management, top quadrant, malcolm chisholm
    
TopQuadrant
Published By: TopQuadrant     Published Date: Jun 11, 2018
Data governance is a lifecycle-centric asset management activity. To understand and realize the value of data assets, it is necessary to capture information about them (their metadata) in the connected way. Capturing the meaning and context of diverse enterprise data in connection to all assets in the enterprise ecosystem is foundational to effective data governance. Therefore, a data governance environment must represent assets and their role in the enterprise using an open, extensible and “smart” approach. Knowledge graphs are the most viable and powerful way to do this. This short paper outlines how knowledge graphs are flexible, evolvable, semantic and intelligent. It is these characteristics that enable them to: • capture the description of data as an interconnected set of information that meaningfully bridges enterprise metadata silos. • deliver integrated data governance by addressing all three aspects of data governance — Executive Governance, Representative Governance, and App
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TopQuadrant
Published By: ROKITT     Published Date: Apr 11, 2016
Few things benefit an organization as much as information governance. Data is now one of the most valuable holdings for any business, but unfortunately in many environments much of the data is ignored and its potential value lost. Ignored data is also inherently less secure than data that’s tracked. Businesses need a way to bring hidden data out of the shadows and make it safe and useful again. Data discovery facilitates unearthing previously unknown data relationships. Mapping data flow and data lineage helps make data safe, compliant, and auditable. Good metadata makes a system more navigable. All these tools make data more accessible to staff and more useful for capitalizing on business opportunities.
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ROKITT
Published By: Infogix     Published Date: Apr 21, 2017
Data Governance and GDPR go Together Like Peanut Butter and Jelly May 2018 might sound far away, but any organization that does business in the EU must be prepared on day one to comply with the new General Data Protection Regulation (GDPR). This regulation carries stiff penalties for non-compliance – first time violators should expect to pay up to the greater of 4% of global annual revenue or 20 million EUR in fines – so it behooves organizations to cross their i's and dot their t's in regards to their GDPR plan. One integral component that is vital is instituting data governance to understand the organization’s data from a business perspective. Learn more about "What is considered Personally Identifiable Information?”, “What are the GDPR compliance obligations?”, and “Why data governance is vital?” in an easy to read white paper titled: General Data Protection Regulation (GDPR) and the Vital Role of Data Governance.
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Infogix
Published By: BackOffice     Published Date: Apr 22, 2018
The success of a business is increasingly influenced by how effectively it utilizes data within strategic decision making & operations. But when a business views its critical data simply as a byproduct of business processes, and doesn’t value it as a business asset, it increases the risk of not being able to achieve its desired outcomes.
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BackOffice
Published By: TopQuadrant     Published Date: Jul 18, 2016
With information streaming in from more varied sources and at a faster pace than ever before, organizations are having an increasingly difficult time deriving accurate meaning from their data. Data governance systems that were once able to organize and process enterprise information are becoming too slow and limited.   Semantic information management makes it easier to reconcile data from different sources by compiling and organizing information about that data, its metadata. By connecting all kinds of data and metadata in a more accessible way, semantic information systems empower users, data stewards and analysts to unlock and use the true meaning and value of their organization’s data.     Learn more about the challenges in the evolving data landscape and how a semantic approach can help.
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TopQuadrant
Published By: TopQuadrant     Published Date: Aug 01, 2016
With information streaming in from more varied sources and at a faster pace than ever before, organizations are having an increasingly difficult time deriving accurate meaning from their data. Data governance systems that were once able to organize and process enterprise information are becoming too slow and limited. Semantic information management makes it easier to reconcile data from different sources by compiling and organizing information about that data, its metadata. By connecting all kinds of data and metadata in a more accessible way, semantic information systems empower users, data stewards and analysts to unlock and use the true meaning and value of their organization’s data. Learn more about the challenges in the evolving data landscape and how a semantic approach can help.
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TopQuadrant
Published By: Semarchy     Published Date: Aug 18, 2016
David Loshin reexamines the way we ingest, manage, consume, and transform data into actionable information and intelligence. Read how this industry expert makes the case for data governance with an unconventional business-first focus. The conventional wisdom on data governance proposes hierarchies, operating models, and processes for data policy definition and implementation. Unfortunately, poorly-designed and minimally-planned data governance processes are ineffective because they are bureaucratic and overwhelming. This is especially true when processes are imposed by fiat, take a long time, and don't result in any short-term improvement in information value. But proper data governance is a critical success factor for master data management! In this paper, we examine the motivations for coupling data governance with master data management and consider how to evolve data policies and processes to position master data management for success.
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Semarchy
Published By: Ted Hills     Published Date: Mar 29, 2016
NoSQL database management systems give us the opportunity to store our data according to more than one data storage model, but our entity-relationship data modeling notations are stuck in SQL land. Is there any need to model schema-less databases, and is it even possible? In this short white paper, Ted Hills examines these questions in light of a recent paper from MarkLogic on the hybrid data model. Ted Hills has been active in the Information Technology industry since 1975. At LexisNexis, Ted co-leads the work of establishing enterprise data architecture standards and governance processes, working with data models and business and data definitions for both structured and unstructured data. His book, NoSQL and SQL Data Modeling, was recently released by Technics Publications (http://technicspub.com).
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Ted Hills
Published By: NTT Data APAC     Published Date: Jan 16, 2019
NTT Data services has over 600+ BI experts and over 250+ implementations in India, receiving high accolades from Gartner and AMR research. NTT Data Services offers Industry focused offerings and pre-configured models. Some of our offerings include: - Guided Analytics Strategy - Proven Framework & Methodology for ‘C’ level executives - Solution lab for Co-Innovation and Proof of Concepts - Advisory Services - BI Transformations, Big Data Strategy, Information Governance, Health Checks - Proprietary Tools & Accelerators – System Optimization, Architect to Archive, User Adoption - Flexible Delivery - Rapid Development Factory, Shared Services Find more details in this deck.
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NTT Data APAC
Published 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
Published By: Zynapse     Published Date: Jun 16, 2010
Data Governance has emerged as the point of convergence for people, technology and process in order to manage the crucial data (information) of an enterprise. This is a vital link in the overall ongoing data management process for it maintains the quality of data and makes it available to a wide range of decision making hierarchy across an organization
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zynapse, erp projects, data information, data management, governance, mdm, master data management, odm, business intelligence, database development
    
Zynapse
Published By: Zynapse     Published Date: Sep 10, 2010
A whitepaper by Ventana Research discusses the need to combine business and technology in a unified approach for MDM implementations in diverse areas.
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zynapse, erp projects, data information, data management, governance, mdm, master data management, odm, business intelligence, database development, data integration
    
Zynapse
Published By: Zynapse     Published Date: Sep 10, 2010
A whitepaper by Ventana Research describing the role and importance of partnerships between business and IT in MDM strategy
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zynapse, erp projects, data information, data management, governance, mdm, master data management, odm, business intelligence, database development, data integration
    
Zynapse
Published By: Zynapse     Published Date: Sep 10, 2010
A 14-page whitepaper on how to achieve lower material costs and optimized inventory using Material Master Data Management
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zynapse, erp projects, data information, data management, governance, mdm, master data management, odm, mmdm, material, business intelligence, database development, data integration
    
Zynapse
Published By: Zynapse     Published Date: Sep 10, 2010
A 26-page information rich whitepaper on the business benefits, challenges and best practices of Material Master Data Management
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zynapse, erp projects, data information, data management, governance, mdm, master data management, odm, mmdm, material, business intelligence, database development
    
Zynapse
Published By: Zynapse     Published Date: Sep 10, 2010
UNSPSC enables preference item management, better spend analysis, supply standardization and information control. Whether you are deliberating on the need for a common product and classification standard for your company, or are an advanced UNSPSC adopter, we hope that "Adopting UNSPSC" will answer some of your questions and perhaps help you in some way to improve your purchasing and supply management processes.
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zynapse, erp projects, unspsc, data information, data management, governance, mdm, master data management, odm, mmdm, material, business intelligence, database development
    
Zynapse
Published By: Zynapse     Published Date: Sep 10, 2010
A step-by-step guide to create the right business case for all your Master Data Requirements.
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zynapse, erp projects, data information, data management, governance, mdm, master data management, odm, mmdm, material, tpm, business intelligence, database development
    
Zynapse
Published By: Zynapse     Published Date: Aug 17, 2010
An exclusive success story of a Fortune 200 enterprise. Learn how the master data management initiative delivered: . A unified view of the master data across the enterprise . Accelerated ROI realization from massive ERP investments . Inventory optimization by duplicate identification . Improved operational and process efficiencies
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zynapse, erp projects, unspsc, data information, data management, governance, mdm, master data management, odm, mmdm, material, business intelligence, database development
    
Zynapse
Published By: Zynapse     Published Date: Nov 01, 2010
The 4-undying reasons to take care of during an ERP Data Migration.
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zynapse, erp projects, unspsc, data information, data management, governance, mdm, master data management, odm, mmdm, material, business intelligence, database development
    
Zynapse
Published By: Zynapse     Published Date: Nov 08, 2010
A worldwide leader inSpend Management Software solutions: Zycus. Recognized as one of the Top 3 Global Market Leadersin Spend Management Domain by leading analysts and Industry observers
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zynapse, erp projects, unspsc, data information, data management, governance, mdm, master data management, odm, mmdm, material, business intelligence, database development
    
Zynapse
Published By: Zynapse     Published Date: Feb 02, 2011
A worldwide leader in Spend Management Software solutions: Zycus. Recognized as one of the Top 3 Global Market Leaders in Spend Management Domain by leading analysts and Industry observers
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zynapse, erp projects, unspsc, data information, procurement, information management, data management, governance, mdm, master data management, odm, mmdm, material, business intelligence, database development, data integration
    
Zynapse
Published By: Ricoh     Published Date: Sep 28, 2018
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Ricoh
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