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Creating a clearly articulated data strategy—a roadmap of technology-driven capability investments prioritized to deliver value—helps ensure from the get-go that you are focusing on the right things, so that your work with data has a business impact. In this presentation, the experts at Silicon Valley Data Science share their approach for crafting an actionable and flexible data strategy to maximize business value.
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Data Governance can have a varied definition, depending on the audience. To many, data governance consists of committee meetings and stewardship roles. To others, it focuses on technical data management and controls. Holistic data governance combines both of these aspects, and a robust data architecture and associated diagrams can be the “glue” that binds business and IT governance together. Join this webinar for practical tips and hands-on exercises for aligning data architecture & data governance for business and IT success.
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Creating a clearly articulated data strategy—a roadmap of technology-driven capability investments prioritized to deliver value—helps ensure from the get-go that you are focusing on the right things, so that your work with data has a business impact. In this presentation, the experts at Silicon Valley Data Science share their approach for crafting an actionable and flexible data strategy to maximize business value.
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Learn how to execute a data governance strategy through creation of a successful business case and operating model. Originally presented to an audience of 400+ at the Master Data Management & Data Governance Summit. Visit www.datumstrategy.com for more!
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Organizations are faced with an increasingly complex data landscape, finding themselves unable to cope with exponentially increasing data volumes, compounded by additional regulatory requirements with increased fines for non-compliance. Enterprise architecture and data governance are often discussed at length, but often with different stakeholder audiences. This can result in complementary and sometimes conflicting initiatives rather than a focused, integrated approach. Data governance requires a solid data architecture foundation in order to support the pillars of enterprise architecture. In this session, IDERA’s Ron Huizenga will discuss a practical, integrated approach to effectively understand, define and implement an cohesive enterprise architecture and data governance discipline with integrated modeling and metadata management.
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This introduction to data governance presentation covers the inter-related DM foundational disciplines (Data Integration / DWH, Business Intelligence and Data Governance). Some of the pitfalls and success factors for data governance. • IM Foundational Disciplines • Cross-functional Workflow Exchange • Key Objectives of the Data Governance Framework • Components of a Data Governance Framework • Key Roles in Data Governance • Data Governance Committee (DGC) • 4 Data Governance Policy Areas • 3 Challenges to Implementing Data Governance • Data Governance Success Factors
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When starting or evaluating the present state of your Data Governance program, it is important to focus on best practices such that you don’t take a ready, fire, aim approach. Best practices need to be practical and doable to be selected for your organization, and the program must be at risk if the best practice is not achieved. Join Bob Seiner for an important webinar focused on industry best practice around standing up formal Data Governance. Learn how to assess your organization against the practices and deliver an effective roadmap based on the results of conducting the assessment. In this webinar, Bob will focus on: - Criteria to select the appropriate best practices for your organization - How to define the best practices for ultimate impact - Assessing against selected best practices - Focusing the recommendations on program success - Delivering a roadmap for your Data Governance program
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Create a policy of your data elements using Data Governance PowerPoint Presentation Slides. With the help of this data warehouse management PPT template, you can measure and capture the effectiveness of stored information. You can monitor the third-party data providers' performance by using a data management PowerPoint complete deck. If you want to highlight the importance of analytical activities and reporting issues, then use these data architecture PPT slides. There are several problems that companies suffer while gathering the statistics, thus describe that point with the help of an information governance PowerPoint presentation deck. By using our professionally designed business semantics management PPT visuals, you can compare the data in manually as well as in automated form. The data management framework PPT contains exclusive diagrams and high-grade icons with which you can make your presentation even more engaging. This data integration PowerPoint presentation comprises of a total of twenty-five slides. Therefore, download this ready-to-use data collection system PPT template and envelope the liquidities and accountabilities. https://bit.ly/3ku95BZ
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Data Governance
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There are several basic components that go into delivering a successful and sustainable data governance program. Many of these framework items can be developed using tools you already own and without going to great expense. Organizations swear by the items that will be discussed in this webinar. Join Bob Seiner for this month’s installment of the Real-World Data Governance series to learn about how to build and deliver immediate and future value from your Data Governance program through the delivery of items that will formalize accountability for the management of data and information assets. Bob will discuss these core components: Gaining Leadership’s backing and understanding Best Practice Analysis leading to Recommended Actions Operating Model of Roles & Responsibilities Communications Plan to improve awareness Action Plan / Roadmap to success
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What is a lasting solution to the sea of errors, headaches, and losses caused by inconsistent and inaccurate master data such as customer and product records? This is the data that your business counts on to operate business processes and make decisions. But this data is often incomplete or in conflict because it resides in multiple IT systems. Master Data Management (MDM)'s programs are the solution to this problem, but these programs can fail without the investment and involvement of business managers. Listen to Rob Karel, Forrester analyst, and Jignesh Shah from Software AG to learn about a new, process-driven approach to MDM and why it is a win-win for both business and IT managers. Visit us at http://www.softwareag.com Become part of our growing community: Facebook: http://www.facebook.com/softwareag Twitter: http://www.twitter.com/softwareag LinkedIn: http://www.linkedin.com/company/software-ag YouTube: http://www.youtube.com/softwareag
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Developing a Data Strategy for your organization can seem like a daunting task. The opportunity in getting it right can be significant, however, as data drives many of the key initiatives in today’s marketplace: digital transformation, marketing, customer centricity, and more. This webinar will help de-mystify Data Strategy and Data Architecture and will provide concrete, practical ways to get started.
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The Data Trifecta – Privacy, Security & Governance Race from Reactivity to Re...
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Building a Data Strategy – Practical Steps for Aligning with Business Goals
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Real-World Data Governance Webinar: Data Governance Framework Components
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DAS Slides: Building a Data Strategy - Practical Steps for Aligning with Busi...
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As businesses generate and manage vast amounts of data, companies have more opportunities to gather data, incorporate insights into business strategy and continuously expand access to data across the organisation. Doing so effectively—leveraging data for strategic objectives—is often easier said than done, however. This report, Transforming data into action: the business outlook for data governance, explores the business contributions of data governance at organisations globally and across industries, the challenges faced in creating useful data governance policies and the opportunities to improve such programmes.
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Federated data organizations in public sector face more challenges today than ever before. As discovered via research performed by North Highland Consulting, these are the top issues you are most likely experiencing: • Knowing what data is available to support programs and other business functions • Data is more difficult to access • Without insight into the lineage of data, it is risky to use as the basis for critical decisions • Analyzing data and extracting insights to influence outcomes is difficult at best The solution to solving these challenges lies in creating a holistic enterprise data governance program and enforcing the program with a full-featured enterprise data management platform. Kreig Fields, Principle, Public Sector Data and Analytics, from North Highland Consulting and Rob Karel, Vice President, Product Strategy and Product Marketing, MDM from Informatica will walk through a pragmatic, “How To” approach, full of useful information on how you can improve your agency’s data governance initiatives. Learn how to kick start your data governance intiatives and how an enterprise data management platform can help you: • Innovate and expose hidden opportunities • Break down data access barriers and ensure data is trusted • Provide actionable information at the speed of business
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FIMA's latest whitepaper evaluates how financial services companies are managing the challenges posed by data quality management. By analyzing which data types and data characteristics businesses are struggling with, it uncovers the true business costs associated with data quality. It will also gauge how data governance programs are maturing and how they are being measured. Finally, it assesses how data is being managed within financial institutions. Key findings include: Data quality has never been more important for financial institutions, but most of those companies feel their data is only mediocre: Quality data serves a myriad of central business goals, from risk reduction to increased productivity. Unfortunately, many businesses continue to struggle with data quality, despite the fact that four-fifths of them have it ranked as a top priority. The top two business functions impacted by poor data quality are regulatory compliance and risk management: Because these concerns tend to be the most important drivers of data quality, many financial institutions see data governance as a “must-do,” rather than a ROI-boosting activity. Furthermore, the vast majority of financial services companies can not quantify the business cost of poor data quality. Financial institutions vary greatly in the maturity of their data governance programs: Data governance cannot be overlooked – unsurprisingly, businesses with formalized data governance programs reported that their data was higher quality than most other groups. Data quality management requires close collaboration between business and IT leaders: That collaboration already exists for 83% of respondents in this study, who say that IT and business leaders work together to manage data quality in their organizations. However, the tools these businesses use to manage their data are not all equal, leading to an uneven allocation of resources.
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189 C H A P T E R 10 Information Governance and Information Technology Functions Information technology (IT) is a core function impacted by information gover-ynance (IG) efforts. IT departments typically have been charged with keeping the “plumbing” of IT intact—the network, servers, applications, and data—but although the output of IT is in their custody, they have not been held to account for it; that is, the information, reports, and databases they generate have long been held to be owned by users in business units. This has left a gap of responsibility for governing the information that is being generated and managing it in accordance with legal and regulatory requirements, standards, and best practices. Certainly, on the IT side, shared responsibility for IG means the IT department itself must take a closer look at IT processes and activities with an eye to IG. A focus on improving IT effi ciency, software development processes, and data quality will help contribute to the overall IG program effort. IT is an integral piece of the program. Debra Logan, vice president and distinguished analyst at Gartner, states: Information governance is the only way to comply with regulations, both cur- rent and future, and responsibility for it lies with the CIO and the chief legal offi cer. When organizations suffer high-profi le data losses, especially involv- ing violations of the privacy of citizens or consumers, they suffer serious repu- tational damage and often incur fi nes or other sanctions. IT leaders will have to take at least part of the blame for these incidents. 1 Gartner predicts that the need to implement IG is so critical that, by 2016, fully one in fi ve chief information offi cers (CIOs) will be terminated for their inability to implement IG successfully. Aaron Zornes, chief research offi cer at the MDM (Master Data Management) Institute, stated: “While most organizations’ information governance efforts have fo- cused on IT metrics and mechanics such as duplicate merge/purge rates, they tend to ignore the industry- and business-metrics orientation that is required to ensure the economic success of their programs.” 2 190 INFORMATION GOVERNANCE Four IG best practices in this area can help CIOs and IT leaders to be successful in delivering business value as a result of IG efforts: 1. Don’t focus on technology, focus on business impact Technology often enthralls those in IT—to the point of obfuscating the reason that technologies are leveraged in the fi rst place: to deliver business benefi t. So IT needs to reorient its language, its vernacular, its very focus when implementing IG programs. IT needs to become more business savvy, more businesslike, more focused on delivering business benefi ts that can help the organization to meet its business goals and achieve its business objectives. “Business leaders want t.
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Data governance, Information security strategy
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Data Governance Process
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the influencers, not the leaders. Also, the chair is not the executive sponsor 5. Manage the Data Lifecycle & Maintian transparency 6. Engage the Right Vendors can help streamline data governance policies better.
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Vasanthi Nagappan
Download now