data governance strategy

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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: Reltio     Published Date: Nov 16, 2018
Modern Master Data Management (MDM) is more than an extension of your data governance strategy. See how Reltio is taking MDM to the next level with its data platforms in AWS and Google Cloud.
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Reltio
Published By: Bitwise     Published Date: Apr 30, 2018
Organizations that adopt an enterprise data lake model for real-time, self-service and advanced analytics require a fresh approach and outlook to develop a Data Governance strategy as Hadoop changes the way that organizations ingest and store data, as well as how business partners access and use data. This paper outlines pillars for Hadoop Data Governance and Security that provide a framework that can be applied to any company.
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Bitwise
Published By: Group M_IBM Q1'18     Published Date: Jan 04, 2018
For data-driven businesses, cloud can be a boon. Data can be found, processed and managed on the cloud without an investment in local hardware infrastructure, but what does that mean to information trust and governance? When data comes from cloud-based sources, IT needs a plan for data integration and security. Download this insightful white paper and learn the four key priorities you must consider when developing your IT strategy to promote good hybrid information governance. Learn the blend of process, organizational and technical enablers that will allow you to move to a hybrid environment with speed and confidence.
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data-driven business, cloud, information trust, information governance, data integration, data security, it strategy
    
Group M_IBM Q1'18
Published By: Hitachi Vantara     Published Date: Mar 20, 2018
Digital transformation is disrupting traditional, tried-and-true business process and leaving many enterprises scrambling for alternatives. Although the customer remains king for business success, data is quickly becoming an organization’s most strategic asset for reaching, interacting with and retaining customers. With ransomware attacks on the rise, a strict regulatory environment, and nimble, competitive upstarts entering the market, protecting and extracting value from your most strategic asset is a business imperative — and a formidable challenge.
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Hitachi Vantara
Published By: SAS     Published Date: Apr 16, 2015
The framework presented here is a way to avoid data dysfunction via a coordinated and well-planned governance initiative. These initiatives require two elements related to the creation and management of data: • The business inputs to data strategy decisions via a policy development process. • The technology levers needed to monitor production data based on the policies. Collectively, data governance artifacts (policies, guiding principles and operating procedures) give notice to all stakeholders and let them know, “We value our data as an asset in this organization, and this is how we manage it.”
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SAS
Published By: IBM     Published Date: Oct 13, 2016
Cloud-based data and processing services present too much opportunity for organizations to ignore. How can organizations realize the obvious financial benefits of the cloud while ensuring information culled from cloud sources is secure and trustworthy? Good hybrid information governance implies several priorities for IT and the business which are based on these foundational pillars: - Broad agreement on what information means - Clear agreement on how owned information assets will be maintained and monitored - Standard practices for securing strategic information assets - Enterprise data integration strategy
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ibm, trusted data, big data, governance, data governance, data management, business technology, data center
    
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: Reltio     Published Date: Nov 20, 2018
Modern Master Data Management (MDM) is more than an extension of your data governance strategy. See how Reltio is taking MDM to the next level with its data platforms in AWS and Google Cloud.
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Reltio
Published By: SAP     Published Date: Mar 24, 2011
The list of initiatives that are data-enabled-indeed, data-intensive-vary from company to company, from industry to industry. But the common denominator is an increasing awareness that these and other programs can't succeed without clean, meaningful, and available information. In this white paper, Baseline Consulting's Jill Dyché discusses how the data conversation is changing from philosophical questioning to hard-core tactics, from "What do we need?" to "Where do we start?" It covers the most common reasons for data governance failure, as well as the components of data governance that will inform the right strategy and give companies a means of determining where and how to begin their data governance journeys.
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data governance, data governance failure, data governance initiative, business intelligence, database development, data integration, data mining, data quality, database security, data warehousing
    
SAP
Published By: SAS     Published Date: Aug 28, 2018
Starting data governance initiatives can seem a bit daunting. You’re establishing strategies and policies for data assets. And, you’re committing the organization to treat data as a corporate asset, on par with its buildings, its supply chain, its employees or its intellectual property. However, as Jill Dyché and Evan Levy have noted, data governance is a combination of strategy and execution. It’s an approach that requires one to be both holistic and pragmatic: • Holistic. All aspects of data usage and maintenance are taken into account in establishing the vision. • Pragmatic. Political challenges and cross-departmental struggles are part of the equation. So, the tactical deployment must be delivered in phases to provide quick “wins” and avert organizational fatigue from a larger, more monolithic exercise. To accomplish this, data governance must touch all internal and external IT systems and establish decision-making mechanisms that transcend organizational silos. And, it must provi
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SAS
Published 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.
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ibm, big data, 9sight consulting, data, it management, maximize business, deployment, business opportunities, big data usage, data warehouse, data center, business analytics, big data offerings, core business data, analytic data, puredata system, data virtualization, data integration, data types, data quality
    
IBM
Published By: Box     Published Date: Jun 22, 2018
These days, everyone's talking about digital transformation. But exactly how does your company get there? Capture is a great place to start — in fact, it's one of the most critical steps to take as you move your business into the digital age. Whether it’s simply using OCR to make content more easily discoverable, adding and enhancing metadata to drive specific processes, or classifying content from the onset for better information governance, capture adds a ton of value to your existing content assets. This ebook details our key takeaways from AIIM's Industry Watch Report, Improving Business Operations in 2017: Capturing Vital Content. We share how cloud-based capture tools are replacing the longstanding legacy of paper-based processes to streamline and speed up the way you do business. Download the ebook to learn: • How the latest capture innovations can support your digital strategy • 5 business processes that benefit most from advanced capture technologies • The key benefits of c
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