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The document discusses the role and importance of a Chief Data Officer (CDO). A CDO champions data as a strategic business asset and driver of revenue. They identify how data can support business priorities, ensure the right data is collected, and wire the company to make data-driven decisions by eliminating semantic differences in enterprise data.
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Five steps to launch your data governance office
About the Webinar
DATAVERSITY and OONdada have teamed up to create a new, innovative Data Governance tool called DATAVERSITY DGO. This webinar will educate you on the philosophy behind that tool as it contains the processes, instructions, and guidance from the Data Governance Institute's Framework and Methodology.
In this webinar, you will learn the five fundamental steps to launching a Data Governance Office:
1. Establish Goals
2. Engage Stakeholders
3. Align Governance
4. Exercise Governance
5. Communicate Success
About the Speaker
Max Gano has an extensive background in data management, serving as Chief Data Architect for a Fortune 500 Bank. He is passionate about contributing to the increasing maturity of data management and governance practices as critical capabilities for any organization that seeks sustainable prosperity and growth. As the Principle Data Strategist for the Data Governance Institute, he worked with a range of major corporations and industry thought leaders to formulate successful strategies for governing and managing information and the operational processes required to achieve those objectives. With that goal in mind, Max has now turned his attention to establishing OONdada as a leader in online collaboration services.
Tag dg 101 march 2017
Data governance is a data strategy that incorporates disciplines like data quality, data management, data standards, policies, and business process management to support the business strategy. It applies these disciplines enterprise-wide with everyone involved to proactively govern data and maximize its value in supporting business goals.
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Five steps to launch your data governance office
About the Webinar
DATAVERSITY and OONdada have teamed up to create a new, innovative Data Governance tool called DATAVERSITY DGO. This webinar will educate you on the philosophy behind that tool as it contains the processes, instructions, and guidance from the Data Governance Institute's Framework and Methodology.
In this webinar, you will learn the five fundamental steps to launching a Data Governance Office:
1. Establish Goals
2. Engage Stakeholders
3. Align Governance
4. Exercise Governance
5. Communicate Success
About the Speaker
Max Gano has an extensive background in data management, serving as Chief Data Architect for a Fortune 500 Bank. He is passionate about contributing to the increasing maturity of data management and governance practices as critical capabilities for any organization that seeks sustainable prosperity and growth. As the Principle Data Strategist for the Data Governance Institute, he worked with a range of major corporations and industry thought leaders to formulate successful strategies for governing and managing information and the operational processes required to achieve those objectives. With that goal in mind, Max has now turned his attention to establishing OONdada as a leader in online collaboration services.
Tag dg 101 march 2017
Data governance is a data strategy that incorporates disciplines like data quality, data management, data standards, policies, and business process management to support the business strategy. It applies these disciplines enterprise-wide with everyone involved to proactively govern data and maximize its value in supporting business goals.
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Which comes first the chicken or the egg? Or better yet The Data Strategy or the Chief Data Officer? A guide to a data strategy in a Big Data world.
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Visit www,masterdata.co.za/index.php/data-governance-solutions
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Data lineage is a regulatory and internal requirement with potential to deliver significant operational and business benefits, but financial institutions can find it difficult to implement and complex to maintain as systems and regulatory requirements themselves, change quickly. The importance of understanding where the true source of the data is coming from, where the data flows to and what has changed cannot be overstated. The webinar defines data lineage and discuss implementation through the eyes of those that have implemented and sustained successful lineage solutions with significant benefits.
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Chief Data & Analytics Officer Fall Boston - Presentation
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Chief Data Officer: Evolution to the Chief Analytics Officer and Data Science
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Data Science in Action for an Insurance Product - Shawn Jin
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Univ guion
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Alvaro gimenez
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1. Undescended testis occurs when the testis follows the normal path of descent but fails to reach the scrotum. Retractile testis involves a hyperreflexic cremaster muscle. Ectopic testis deviates from the normal path of descent.
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Organizations need to tap into the huge potential of their vast volumes of data, but a use case tactical approach is not going to work. Instead, they need to work in the definition of a data strategy linked to the most relevant goals for the enterprise.
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This document provides information on data governance and discusses several challenges and approaches to data governance. It discusses that 80% of enterprise data is unstructured and spread across many sources like web data, enterprise applications, emails, and social media. Governing such diverse data assets is a complex long-term journey. It also discusses why data governance is needed, challenges of data governance, and different routes and frameworks to conduct data governance assessments and develop solutions. These include using cases studies, lean six sigma methodology, enterprise data architecture approaches, and linking data governance with machine learning. The document concludes by emphasizing structure of data, experimenting with different assessment and solutioning methods, and leveraging machine learning as a new capability.
Securing big data (july 2012)
This document discusses securing big data as it travels and is analyzed. It outlines some of the key challenges organizations face with big data including increasing volumes of data from various sources, managing data privacy, and optimizing return on investment from big data analytics. Effective data governance is important for managing data as an asset and meeting regulatory compliance. However, many companies struggle with data governance due to short-term priorities and political issues. An iterative approach focusing on specific data sets can help companies start seeing results more quickly from data governance.
Chief Data Officer (CDO) Organization Roles
If your Company wants to treat Data as an Asset, it needs a Chief Data Officer to initiate significant changes in the Roles and Responsibilities of the Data Governance, IT Data Management and Business Analyst Data Scientist organizations. This presentation describes how the resulting organizations might look and behave.
Data Integrity: From speed dating to lifelong partnership
Governance has little to do with governance…it’s about delivering and demonstrating value. It’s one thing for your colleagues to intellectually believe in the value of data, good data, and governed data, but it’s another thing entirely to have them emotionally engaged and excited to be involved. In this presentation from the CDO Sit-Down series, Shaun Connolly, Vice President of International Strategic Services, shares his thoughts and experience on approaches to win over reluctant leaders and business teams and describe the key components of successful programs.
Business Intelligence and Analytics Capability
Business intelligence and analytics both refer to maximize the value of your data to make better decisions, ALTEN CAlsoft Labs helps
enterprises accelerate business intelligence by providing the most comprehensive, integrated and easy-to-use reporting and analytics features with its industry specific analytics solutions and best in-class technology.
Is Your Agency Data Challenged?
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
BUSINESS INTELLIGENCE (BI) - Definition, Process, and Benefit
have you known what business intelligence is? the process? and also the benefit for your decision making. business intelligence become completely useful information to be a supporting system for decision making
Business intelligence by fakhri helmy
business intelligence definition, process, and benefit for supporting decision making. Created by Fakhri Helmy Dipstrategy - Digital Agency Jakarta
Today's Chief Data Officer: 3 Types of CDOs, Key Challenges, and Opportunitie...
In this presentation we examine the 3 types of Chief Data Officers that are common in the industry today. We discuss their responsibilities, key challenges, and present ideas for having an meaningful impact. A great overview of the CDO role and how this executive position can contribute to the success of your business.
Accenture Big Data Expo
This document discusses Accenture's approach to data modernization. It outlines key trends in data-driven organizations, including democratizing data, incorporating new data sources, focusing on advanced analytics, adopting big data and hybrid architectures, and changing skills requirements. The document then presents a high-level 9-step approach to agile analytics that engages stakeholders, identifies value opportunities, formulates hypotheses, understands data sources, defines models, prepares data, prototypes and iterates, pilots and executes projects, and delivers actionable insights. It also notes some common challenges organizations face in data transformation, such as unrealistic technology expectations, inadequate delivery approaches, skills gaps, and poor data governance. Finally, it poses questions to help organizations assess their readiness
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Why cdo
- 1. Why CDO? CDO is… Business Voice of Data Champion of Data as a Strategic Business Asset and Driver of Revenue Business Driver Value Data as a Corporate Asset and Revenue Generator Effective use of Data to Gain Competitive Edge Eliminate any Semantic Differences among Enterprise Data Galvanize Governance as a Shared Service Smart Data Innovation Open Data Policy Role of CDO Identify how data can be used to support the company's most important priorities • understand when business units should be looking for answers in the company's data Engender the company to collect the right data • ensure that processes are being instrumented and all necessary data is being captured and stored • create the data production line, allowing the company to move seamlessly from collection (big data, digital data) to insight Ensure the company is wired to make data-driven decisions • ensure that business units across the organization communicate effectively by eliminating data semantic disparity - taxonomies, glossaries, business dictionaries, metadata management, and information rationalization