governance

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Published By: SailPoint     Published Date: Feb 08, 2011
This paper introduces a next generation of provisioning solution that offer a more strategic and sustainable approach.
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sailpoint, legacy provisioning solution, user lifecycle management, governance, compliance, identity management, corporate governance
    
SailPoint
Published By: Wisegate     Published Date: Nov 02, 2011
IT and security execs share practical advice on what it takes to lead a successful IT implementation and lessons learned from from the trenches.
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governance, risk and compliance (grc), identity and access management (iam), it project management, it best practices
    
Wisegate
Published By: Red Hat     Published Date: Sep 25, 2014
As a strategic partner in your business, you face increasing demands from your line-of-business leaders for new functionality and advanced capabilities, which you must deliver with a constrained IT budget. What could you do to meet these expectations and add value to the business if you could contain costs, increase operational efficiency, and do more with less? You need to overcome several challenges. The cost of software licensing management is rising as a result of maintaining proprietary platforms or legacy technology, making it difficult to modernize your datacenter and migrate to more cost-effective solutions. You’re likely burdened by regulatory compliance mandates, which create enforcement, reporting, and auditing expenses. And, like 67% of IT organizations, your budget is probably shrinking. Red Hat can help. Red Hat® Enterprise Linux® gives you the high-value subscription model, built-in governance processes, and simplified migration path you need to aggressively lower your
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increased demands, functionality, software licensing management, proprietary platforms, legacy technology, datacenter, it organization, it management, enterprise applications, data management
    
Red Hat
Published By: MarkLogic     Published Date: Jun 19, 2017
Integrate your data silos to finally navigate the data maze. This comprehensive white paper addresses a key element in any GRC program: regulatory compliance. Download this paper to learn about the costs, current practices, and associated risks. We’ll also recommend a technologically-enabled approach and highlight its main business benefits for financial services, insurance, and energy companies. Overview Executive Summary Compliance Requirements A Recommended Approach Business Benefits Regulatory Compliance Solution Architecture Related Materials
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banking, financial services, data management, silos, data strategy, transparency, data governance, regulation, data architecture, compliance, reporting, energy, insurance
    
MarkLogic
Published By: MarkLogic     Published Date: Jun 19, 2017
There is opportunity in the ongoing turbulence throughout the financial industry; however, regulatory and compliance challenges absorb resources and distract focus away from growth. Download white paper to learn about a smart approach to data and innovative tools that build resilience into a business looking to not just weather the storm, but seize the advantage. Overview: - Executive Summary - Challenges of Financial Markets Today - The Need for a 360-View of Data - How to Deliver: Increased Transparency Adapt to Evolving Regulations Improve Compliance and Lower Cost - Solution Architecture for Regulatory Reporting - Case Study: Adapting to Regulatory Complexity "Disparate systems led to frequent cycles spent correcting errors within the data”.
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banking, financial services, data management, silos, data strategy, transparency, data governance, regulation, data architecture, compliance, reporting
    
MarkLogic
Published By: MarkLogic     Published Date: Jun 21, 2017
Remember Y2K – the IT “problem” that should have brought businesses to a screeching half? Despite the hype, the preparation led to widely documented business benefits and uncovered new opportunities that transformed organizations worldwide. Similarly in today’s highly regulated Financial Services industry, enabling GRC by integrating data from silos can be the driver for future business use cases like machine learning and anti-fraud detection services. GRC can be your catalyst for new opportunities. Listen in as our panel of financial services experts discuss the keys to reinventing your data strategy. We’ll cover: How to align your GRC strategy with a business transformation agenda How to ensure your organization’s approach to data management isn’t just a one-off solution, but a comprehensive one adaptable to changing regulations How to navigate the increasing regulatory demands for granular data security How to turn your compliance spend into new opportunities to earn revenue
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banking, financial services, data management, silos, data strategy, transparency, data governance, regulation, data architecture, compliance, reporting, business transformation, fraud, digital transformation
    
MarkLogic
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: Mimecast     Published Date: Oct 11, 2018
Information management is getting harder. Organizations face increasing data volumes, more stringent legal and regulatory record-keeping requirements, stricter privacy rules, increasing threat of breaches and decreasing employee productivity. Companies are also finding that their old-fashioned, legacy archive strategies are increasingly ineffective. This is driving many organizations to rethink their approach, developing more modern Information Governance strategies.
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Mimecast
Published By: Okta     Published Date: Jul 25, 2016
Current Identity Governance and Administration (IGA) solutions have optimized heavily for complete customization, leaving customers with full flexibility in designing rules and workflows. The problem is that it takes these solutions too long to deploy, at too high a cost, and rarely do they deliver on the ROI that was originally anticipated. Okta believes there is a better way, and a way to reach a much broader set of organizations, by building a cloud-based IGA product that is optimized for out-of-the-box capability and is easily configurable.
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okta, best practices, technology, optimization, identity governance, cloud computing, business technology
    
Okta
Published By: Veritas     Published Date: May 12, 2016
Nearly 70% of all stored data contains no legal, regulatory, or business value. Intelligence about your information’s age, location, and ownership provides the roadmap to effective decision-making.
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Veritas
Published By: Palo Alto Networks     Published Date: Sep 30, 2016
Traditional antivirus (AV) is not the solution to preventing security breaches on the endpoint – it is the problem. AV is no longer effective at stopping today’s cyberthreats. Although AV satisfies many regulatory, governance and compliance requirements, it saddles organizations with hidden costs while providing little to no real security value.
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palo alto, antivirus, security, security value, prevention
    
Palo Alto Networks
Published By: IBM     Published Date: Jan 19, 2017
This ebook takes you on a journey to discover a cloud-based content management solution that provides greater visibility and collaborative control over business content. Meet Mike, an IT Solutions Executive, looking for an innovative way to collaborate that's secure, easy to use, immediate and accessible -- all while meeting strict governance policies.
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ibm, analytics, ecm, box, box for it, content, cloud, content management, enterprise applications, business technology
    
IBM
Published By: IBM     Published Date: Jan 19, 2017
The outcome of any big data analytics project, however, is only as good as the quality of the data being used. As big data analytics solutions have matured and as organizations have developed greater expertise with big data technologies he quality and trustworthiness of the data sources themselves are emerging as key concerns. 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.
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ibm, analytics, ecm, data, big data, information governance, enterprise applications, data management, business technology
    
IBM
Published By: IBM     Published Date: Jan 19, 2017
With organizations keeping larger and larger quantities of data the question will come up that given dropping storage costs, does uncontrolled data growth even matter? It does matter, and in this IBM publication featuring Gartner research you will learn about this ever growing problem and ways for information managers to address solutions.
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ibm, analytics, data, ecm, big data, information governance, enterprise applications, data management, business technology
    
IBM
Published By: IBM     Published Date: Jan 19, 2017
The benefits of moving data to the cloud are touted everywhere, but doing so without an information governance plan in place can cause more problems than it solves. Information governance (IG) is increasingly cited as one of the top five initiatives for companies to tackle over the next two years.
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ibm, analytics, ecm, information governance, cloud, enterprise applications, data management, business technology
    
IBM
Published By: IBM     Published Date: May 23, 2017
This paper is on impact of the new features now available with version 11.1. It covers the use of DB2 within hybrid cloud environments.
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encryption, application development, operating system, market intelligence, data governance, data migration, data quality, ibm
    
IBM
Published By: IBM     Published Date: Aug 23, 2017
Banks today are continuously challenged to meet rigorous regulatory requirements. They must implement strict governance programs that enable them to comply with a wide variety of regulations stemming from the financial crisis that began in 2007, including the DoddFrank Act, Basel Committee on Banking Supervision regulations, the General Data Protection Regulation (GDPR), the Revised Payment Services Directive (PSD2) and the revised Markets in Financial Instruments Directive To keep pace with regulatory changes, many banks will need to reapportion their budgets to support the development of new systems and processes. Regulators continually indicate that the banks must be able to provide, secure and deliver high-quality information that is consistent and mature.
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risk mitigation, data aggregation, risk reporting, banking
    
IBM
Published By: IBM     Published Date: Aug 24, 2017
Data governance is all about managing data, by revising that data to standardize it and bring consistency to the way it is used across numerous business initiatives. What’s more, data governance ensures that critical data is available at the right time to the right person, in a standardized and reliable form. A benefit that fuels better organization of business operations, resulting in improved productivity and efficiency of that organization. Thus, the importance of proper data governance cannot be understated. The concepts of data governance have evolved, where the first iteration of data governance, often referred to as version 1.0, focused on three simplistic elements: objectives, structure and processes; having a limited focus and scope due to its tactical usage. The opportunity from the growing value of data in the realm of analytics, business intelligence, and generating insights was left unrealized. Today, organizations are moving towards what can be called Data Governance 2.0,
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ibm, unified governance strategy, data management, data governance
    
IBM
Published By: IBM     Published Date: Oct 17, 2017
Banks today are continuously challenged to meet rigorous regulatory requirements. They must implement strict governance programs that enable them to comply with a wide variety of regulations stemming from the financial crisis that began in 2007, including the DoddFrank Act, Basel Committee on Banking Supervision regulations, the General Data Protection Regulation (GDPR), the Revised Payment Services Directive (PSD2) and the revised Markets in Financial Instruments Directive (MiFID2). Many of these new regulations are spurring banks to rethink how data from across the enterprise flows into the aggregated risk and capital reports required by regulatory agencies. Data must be complete, correct and consistent to maintain confidence in risk reports, capital reports and analytical analyses. At the same time, banks need ways to monetize, grant access to and generate insight from data
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IBM
Published By: Druva     Published Date: Sep 27, 2017
Blue Hill Research examined how organizations are gaining greater value from their archive of user data, converging data availability, archiving and governance to increasingly meet their wider corporate needs. Learn how unifying data availability and governance is bringing increased utility to organizations.
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archiving, modern data, business cloud
    
Druva
Published By: Druva     Published Date: Nov 09, 2018
The rise of virtualization as a business tool has dramatically enhanced server and primary storage utilization. By allowing multiple operating systems and applications to run on a single physical server, organizations can significantly lower their hardware costs and take advantage of efficiency and agility improvements as more and more tasks become automated. This also alleviates the pain of fragmented IT ecosystems and incompatible data silos. Protecting these virtualized environments, however, and the ever-growing amount of structured and unstructured data being created, still requires a complex, on-prem secondary storage model that imposes heavy administrative overhead and infrastructure costs. The increasing pressure on IT teams to maintain business continuity and information governance are changing how businesses view infrastructure resiliency and long-term data retention—they are consequently looking to new solutions to ensure immediate availability and complete protection of the
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Druva
Published By: Fiserv     Published Date: Mar 02, 2018
Corporate governance. Capital Requirements. Information Security. Identifying and measuring potential risks help you connect the dots to create a sound ERM program for your organization. In today’s environment of security regulations and requirements, organizations must take a comprehensive approach to ERM to identify and mitigate potential threats. Risk is cumulative, and unidentified weaknesses can quickly spiral out of control, resulting in costly solutions that can lead to reputational damage. The first step in designing a sound ERM program is to understand which components are needed and how to implement them. Ten Steps to Enterprise Risk Management: A Comprehensive Approach Reveals the Big Picture, provides a straight-forward approach to creating a reliable, yet flexible program to address existing threats with the ability to adapt to emerging ones. In the end risk management is everybody’s job – do you have a plan in place to help your employees manage unpredictable threats and
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corporate governance, capital requirements, information security, erm program, enterprise risk management
    
Fiserv
Published By: IBM     Published Date: Jul 09, 2018
As the information age matures, data has become the most powerful resource enterprises have at their disposal. Businesses have embraced digital transformation, often staking their reputations on insights extracted from collected data. While decision-makers hone in on hot topics like AI and the potential of data to drive businesses into the future, many underestimate the pitfalls of poor data governance. If business decision-makers can’t trust the data within their organization, how can stakeholders and customers know they are in good hands? Information that is not correctly distributed, or abandoned within an IT silo, can prove harmful to the integrity of business decisions. In search of instant analytical insights, businesses often prioritize data access and analysis over governance and quality. However, without ensuring the data is trustworthy, complete and consistent, leaders cannot be confident their decisions are rooted in facts and reality
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IBM
Published By: Group M_IBM Q418     Published Date: Oct 02, 2018
Across enterprises of all kinds, data is multiplying rapidly in both quantity and variety. Across multi-cloud environments, new sources are exponentially increasing the growing stream of information, including the Internet of Things, social media, mobile devices, virtual reality implementations and optical tracking.
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Group M_IBM Q418
Published By: Group M_IBM Q418     Published Date: Oct 15, 2018
The enterprise data warehouse (EDW) has been at the cornerstone of enterprise data strategies for over 20 years. EDW systems have traditionally been built on relatively costly hardware infrastructures. But ever-growing data volume and increasingly complex processing have raised the cost of EDW software and hardware licenses while impacting the performance needed for analytic insights. Organizations can now use EDW offloading and optimization techniques to reduce costs of storing, processing and analyzing large volumes of data. Getting data governance right is critical to your business success. That means ensuring your data is clean, of excellent quality, and of verifiable lineage. Such governance principles can be applied in Hadoop-like environments. Hadoop is designed to store, process and analyze large volumes of data at significantly lower cost than a data warehouse. But to get the return on investment, you must infuse data governance processes as part of offloading.
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Group M_IBM Q418
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