I am proud that some of these have been translated into Dutch, Italian, Spanish, Portuguese, and Mandarin. Other freely available data program resources are available to download here . Some books that may be of interest House of Structure by Warren Keuffel While old and a bit difficult to read, this is an important article describing the evolution of software development methods. (Originally published in Unix Review V2 N9 pp. 28-36 download a copy courtesy of the Internet Archive ) Page 28 - (Jump directly to page 28 29 30 31 32 33 34 35 36 ) Page 29 - (Jump directly to page 28 29 30 31 32 33 34 35 36 ) Page 30 - (Jump directly to page 28 29 30 31 32 33 34 35 36 ) Page 31 - (Jump directly to page 28 29 30 31 32 33 34 35 36 ) Page 32 - (Jump directly to page 28 29 30 31 32 33 34 35 36 ) Page 33 - (Jump directly to page 28 29 30 31 32 33 34 35 36 ) Page 34 - (Jump directly to page 28 29 30 31 32 33 34 35 36 ) Page 35 - (Jump directly to page 28 29 30 31 32 33 34 35 36 ) Page 36 - (Jump directly to page 28 29 30 31 32 33 34 35 36 )

I am proud that some of these have been translated into Dutch, Italian, Spanish, Portuguese, and Mandarin. Other freely available data program resources are available to download here . Some books that may be of interest Some books that may be of interest I am proud that some of these have been translated into Dutch, Italian, Spanish, Portuguese, and Mandarin. Other freely available data program resources are available here . Click any title below to learn more.

Data Governance Frameworks Collection A data governance framework is the collection of rules, processes, and role delegations that ensure privacy and compliance in an organization's enterprise data management. Since the start of the Data Governance movement several foundational frameworks have guided others. These are some of originals and some other examples. You can jump directly to each directly from the list below: • What is a framework used for ? • DMBOK Data Governance Context Diagram • The Data Governance Institute Framework • KiK Consulting DG Framework • NASCIO DG Implementation Framework • IBM Elements of Effective Data Governance • Model State Government Framework • Baseline Consulting DG Framework • UW–Madison Office of Data Management & Analytics Services • Info-Tech's Data Governance Framework Frameworks can provide: • A system of ideas for guiding subsequent analyses • A means of organizing measures, project data, and then assessing progress • Assistance evaluating priorities for data decision making • Multiple views into assessing overall functionality • The measures used to determine ROI • A means of assessing progress What is a framework used for? Back to Top ↑ DMBOK Data Governance Context Diagram Originator: dama.org copyright DAMA International–more at Technics Publishing or amazon.com ) Back to Top ↑ Back to Top ↑ The Data Governance Institute Framework Originator: Gwen Thomas – more at datagovernance.com Back to Top ↑ Back to Top ↑ KiK Consulting DG Framework Originator: Bob Seiner Back to Top ↑ Back to Top ↑ NASCIO DG Implementation Framework Originator: Steve B. Adler Back to Top ↑ Back to Top ↑ IBM Elements of Effective Data Governance Originator: Steve B. Adler Back to Top ↑ Back to Top ↑ Model State Government Framework Originator: Carlos Rivero – more Office of Data Governance and Analytics Back to Top ↑ Back to Top ↑ Baseline Consulting DG Framework Originator: Jill Dyché – more: Baseline Consulting Back to Top ↑ Back to Top ↑ UW–Madison Office of Data Management & Analytics Services A clear example from academia . Back to Top ↑ Back to Top ↑ More: InfoTech Info-Tech's Data Governance Framework Back to Top ↑

I am proud that some of these have been translated into Dutch, Italian, Spanish, Portuguese, and Mandarin. Other freely available data program resources are available to download here . Some books that may be of interest BigCo Case Study Originally appeared in the in the Journal of Information and Data Quality - click the image below to get the .pdf or just here . EXPERIENCE: Succeeding at Data Management-BigCo Attempts to Leverage Data In a manner similar to most organizations, BigCompany (BigCo) was determined to benefit strategically from its widely recognized and vast quantities of data. (US. government agencies make regular visits to BigCo to learn from its experiences in this area.) When faced with an explosion in data volume, increases in complexity. and a need to respond to changing conditions, Bigo struggled to respond using a traditional, information technology (IT) project-based approach to address these challenges. As BigCo was not data knowledgeable, it did not realize that traditional approaches could not work. Two full years into the initiative, BigCo was far from achieving its initial goals. How much more time, money, and effort would be required before results were achieved? Moreover, could the results be achieved in time to support a larger, critical, technology-driven challenge that also depended on solving the data challenges? While these questions remain unaddressed, those considerations increase our collective understanding of data assets as separate from IT projects. Only by reconceiving data as a strategic asset can organizations begin to address these new challenges. Transformation to a data-driven culture requires far more than technology, which remains just one of three required 'stool legx" (people and process being the other two). Seven prerequisites to effectively leveraging data are necessary, but insufficient awareness exists in most organizations-hence, the widespread misfires in these areas, especially when attempting to implement the so-called big data initiatives. Refocusing on foundational data management practices is required for all organizations, regardless of their organizationa!

I am proud that some of these have been translated into Dutch, Italian, Spanish, Portuguese, and Mandarin. Other freely available data program resources are available to download here . Some books that may be of interest TDWI Data Literacy Talk FORT LAUDERDALE Chapter Business: 00:01 Talk Begins: 23:23 ​ More than half of work is accomplished by knowledge workers–usually defined as those who must “think for a living” [Davenport, 2005]. I contend that all knowledge workers work with data. Since most learn about data individually (if at all), the opportunity to gain from communal or best practices learning has not been present. Most refer to this as a lack of data literacy. Whether applied at the individual or organizational level, literacy is a binary concept and our data needs are more varied. Data proficiency and data acumen are more descriptive/useful terms and these should also be used to describe today's organizational data knowledge requirements. This program will describe five specific data knowledge requirement levels and objective behaviors that must be demonstrated by those operating at each level. Lack of this data knowledge has so far hindered society from fully realizing our collective potential benefits. More importantly, organizations adopting these data knowledge requirements can directly and immediately improve organizational knowledge worker productivity. Delegates will: • Learn why the term data literacy is insufficient to describe the challenge and how the progression from literacy ➜ proficiency ➜ acumen is more operationally viable • Understand five data knowledge requirements levels in terms of their data leverage type, data skills type, ethical perspective and behavioral focus • Be able to match data knowledge requirements levels with types of organizational requirements • Begin to estimate the dollar ranges of potential knowledge worker productivity improvements in their organizations

Book a call w/ Peter! To book a call w/ Peter to discuss anything data, click a link, schedule a session! How do you think I have met so many interesting collaborators over the years? Click here to book a virtual session on my calendar. Zoom or TEAMS are automatically available as conferencing options. ​ if the available hours do not work for you, then please call, text or email me for other options

Monetizing Data Management What's the Return on Investment (ROI) on data management? Sound like an impossible question to answer? Not if you read this book and learn the value-added approach to managing enterprise resources and assets. This book defines the five interrelated best practices that comprise data management, and shows you how by example to successfully communicate data management ROI to senior management. The 17 cases we share will help you to identify opportunities to introduce data management into the strategic conversations that occur in the C-suite. You will gain a new perspective regarding the stewardship of your data assets and insulate your operations from the chaos, losses and risks that result from traditional approaches to technological projects. And you will learn how to protect yourself from legal challenges resulting from outsourced information technology projects gone badly due to incorrect project sequencing and focus. With the emerging acceptance and adoption of revised performance standards, your organization will be better prepared to face the coming big data deluge! The book contains four chapters: Chapter 1 gives a somewhat unique perspective to the practice of leveraging data. We describe the motivations and delineate the specific challenges preventing most organizations from making substantial progress in this area. Chapter 2 presents 11 cases where leveraging data has produced positive financial results that can be presented in language of immediate interest to C-level executives. To the degree possible, we have quantified the effect that data management has had in terms that will be meaningful to them also. Chapter 3 describes five instances taken from the authors' experiences with various governmental defense departments. The lessons in this section however can be equally applied to many non-profit and non-defense governmental organizations. Chapter 4 speaks specifically to the interaction of data management practices, in terms of both information technology projects and legal responsibilities. Reading it can help your organization avoid a number of perils, stay out of court and better vet contractors, experts and other helpers who play a role in organization information technology development. ​ 17 Case Studies Illustrating How Data Leveraging (Big and Small) Can Produce Quantifiable Results That Are of Keen Interest to C-Suite Occupants Check Price @ Amazon Buy this title direct from the publisher with a 20% discount using the code "anythingawesome" Check Amazon Reviews From the foreword by John Bottega : Data is the new currency. Yes, an expression that is being used quite a bit of late, but it is very relevant in discussing the importance of data and the methodologies by which we manage it. And like any currency, how we manage it determines its true value. Like any currency, it can be managed wisely, or it can be managed foolishly. It can be put to good use, or it can be squandered away. The question is-what factors determine the path that we take? How do we properly manage this asset and realize its full value and potential? In Monetizing Data Management, Peter and Juanita explore the question of how to understand and place tangible value on data and data management. They explore this question through a series of examples and real-world use cases to exemplify how the true value of data can be realized. They show how bringing together business and technology, and applying a data-centric forensic approach can turn massive amounts of data into the tools needed to improve business processes, reduce costs, and better serve the customer. Data monetization is not about turning data into money. Instead, it's about taking information and turning it into opportunity. It's about the need to understand the real meaning of data in order to extract value from it. And it's about achieving this objective through a partnership with business and technology. In Monetizing Data Management, the authors demonstrate how true value can be realized from our data through improved data centric approaches. ​

I am proud that some of these have been translated into Dutch, Italian, Spanish, Portuguese, and Mandarin. Other freely available data program resources are available to download here . Some books that may be of interest CDO Job Description Reporting to senior leadership , the CDO is the data leader responsible for evolving data practices to better support the organizational mission. Improving organizational data practices extends the CDO’s responsibilities to every knowledge worker in the organization. Empowering knowledge workers with better data practices is the single most important productivity improvement that organizations can make. The CDO is responsible for growing not just an organizational data team but for operationalizing an organization-wide conversation and focus on data innovation, improvement, and value. The CDO establishes, fiduciary responsibilities through stewardship, aimed at leveraging data assets and organizational capabilities and creating a climate of data sharing. Some of this can be accomplished by leading the organizational data governance program to effectiveness. The data leader will be required to understand how to appropriately incorporate change management capabilities to the substantive people, process, and ethical challenges that will support the new data focus. As an organization’s sole, non-depletable, non-degrading, non-rivalrous strategic asset, its data has likely been suffering from data debt . The CDO must nurture programs to improve useful subsets of organizational data and simultaneously reduce the impact of data debt. Data volume and debt necessitate prioritization and the CDO must incorporate a strategic approach to improving the value of an organization’s data. For data’s true value to become apparent, it needs to be understood as a defined part of the organizational value chain . The CDO is responsible for appropriate aspects of monetization to the organizations data. This requires architecting organizational data requirements in the context of present and future business operations. These requirements identify data products directly supporting business value. (There are more Chief Digital Officers than there are Chief Data Officers.)

I am proud that some of these have been translated into Dutch, Italian, Spanish, Portuguese, and Mandarin. Other freely available data program resources are available to download here . Some books that may be of interest Seven Sisters The seven sisters video is the most requested artifact in my collection. We have access to it courtesy of Dave Evans. It represents the most succinct articulation of MDM that I have run across.

Click to add , update or unsubscribe - subscribers will receive notice of upcoming webinars and other information! Stay In Touch or Unsubscribe? Peter Aiken, PhD is an acknowledged Data Management (DM) authority, an Associate Professor at Virginia Commonwealth University , President of DAMA International , and Associate Director of the MIT International Society of Chief Data Officers . For more than 35 years, Peter has learned from working with hundreds of data management practices in 30 countries including some of the world's most important. Among his 12 books are the first on CDOs (the case for data leadership), focusing on data monetization , on modern strategic data thinking and objectively specifying what it means to be data literate . International recognition has resulted in an intensive schedule of events worldwide. Peter also hosts the longest running data management webinar series hosted by our partners at Dataversity . Starting before Google, before data was big, and before data science, Peter has founded several organizations that have helped more than 200 organizations leverage data–specific savings have been measured at more than $1.5B USD. His latest is Anything Awesome . I am really old but I have seen lots of stuff - that gives me a good basis for comparing things. I like working with inspired individuals. I am a horse-husband and a musician. I’m great with deadlines and agreements. I have deep expertise in IT-related areas and am happy to share it. Biosketch I have been fortunate to visit many parts of the world and managed to collaborate with people and organizations in more than 30 countries 1. US 2. Great Britain 3. Scotland 4. Germany 5. France 6. Italy 7. Switzerland 8. Ireland 9. UAE/Dubai 10. Qatar 11. Thailand 12. Japan 13. Mexico 14. Canada 15. Finland 16. Chile 17. Colombia 18. Egypt 19. Turkey 20. Estonia 21. Netherlands 22. South Africa 23. Brazil 24. Australia 25. Saudi Arabia 26. UAE 27. Norway 28. Sweden 29. India 30. Kazahstan 31. Ecuador 32. Jamacia 33. China ​