The Data Doctrine™ V2 Objective measures for improving data outcomes It is fine to say that "we want to be data-centric, data-first, data-driven, data provocateurs but without commonly agreed upon definitions and objective measures, it is all just hand waving, isn't it? ​ Directly building on the original agile manifesto . Todd and Peter spent some time producing the first version. Published in 2017, hundreds have joined various efforts to improve our collective understanding of what are the concrete steps required to achieve better data outcomes. We have updated the original and are anxious for feedback from the community. We are uncovering better ways of developing IT systems by doing it and helping others do it. Through this work, we have come to value: • data programmes - driving IT programs • informed information investing - over technology acquisition activities • stable, shared organizational data - over IT component evolution • data reuse - over the acquisition of new data sources While there is value in the items on the right, we value the things on the left more Several of our colleagues have had complimentary thoughts in this area also, please check their efforts out as well (links and more below) Visit and learn more about the data-centric manifesto The Data-Centric Manifesto Dave McComb and his team have been at this for many years. His need for this change is an excellent straight forward argument for clearer thinking on this subject. Visit and learn more of the leader's data manifesto The Data-Leader's Manifesto A group including Nina Evans, John Ladley, Danette McGilvary Kelle O'Neal James Price, and Tom Redman published in 2017 and have garnered hundreds of signatures of support. ​ Data-centric computing - Wikipedia article Database-centric architecture - Wikipedia article Introduction to Data-Centricity by Kevin Doubleday - The Data-Centric Architecture treats data as a valuable and versatile asset instead of an expensive afterthought. Data-centricity significantly simplifies security, integration, portability, and analysis while delivering faster insights across the entire data value chain. This post will introduce the concept of Data-Centricity and lay the framework for future installments on Data-Centricity. Data-centric Architecture — A Different Way of Thinking - Data-centric architecture (or model) is a solution that addresses the issues of conventional capital project methodology and delivers positive results. Data-centric execution architecture has been around for a few years and is becoming more popular in the energy sector, where many owners and operators work with a specialized system integrator. Why and how to adopt a data-centric architecture - Data has become one of the most valuable assets in the enterprise. IT teams must make changes -- both culturally and technically -- to ensure their strategy reflects that. The Difference Between Data-centric and Data-driven by Carol Dunn - The recommendation that companies become more data-centric sounds like a great idea. Most companies have the ability and means to accumulate data – in some ambitious cases that turns out to be LOTS of data. Basically, such companies are driven by data. But that’s not the same as being data-centric. Additional recommended reading

Music Like Homer Simpson, I play bass . I love music of all kinds and have enjoyed many musical adventures with colleagues over the years–some of our best jams have been a conferences! There is also a special collection dedicated to Michael Gee , a great guitarist with whom I played for 20+ years. Gettin Weir'd @ Gypsy Sallie's (2017) RIP Rob Crosby Playing at Wings/San Antonio (2002) Smokin' Neocons (2008) Disband @ Terry's Wedding (1998) Gettin' Weird (2018) Whiskey Creek (1976) Family Jewels (1984) Gettin' Weird, Baltimore (2018) Playing @ Wings/San Antonio (2002) DAMA Homemade Jam (2008) Gettin' Weird @ 8 X 10 Club (2017) Playing at Wings/San Antonio (2002) DAMA Homemade Jam (2009) The Band House (2008) DAMA Homemade Jam (2009) Gettin' Weird Annapolis (2018) Gettin Weir'd T-Shirt Playing @ Wings/San Antonio (2002) Some barn dance (unknown date) Mature Life (1980) DAMA Homemade Jam (2010) Playing w/ Gettin' Weird, VA Beach (2019) Playing with Tom Potter and friends (2018) Erika Rosenberg (2015)

Awards I have been fortuate to award, receive and I am grateful for the recognition of colleagues - thank you very much! 25+ years listings in various Who's Who including: Outstanding Intellectuals of the 21st Century, The Dictionary of International Biographies, Emerging Leaders in America, America’s Registry, Executives and Business, Science and Engineering, Finance and Industry, American Education, and other compilations.

[ Bad Data ] + Anything Awesome [ will always yield ] Bad Results Data must be the heart and foundation of all organizational planning and operational efforts Since 1981, I have been helping people and organizations around the world with data and data leadership challenges . I have shared my accumulated knowledge far & wide and provided opportunity for others to do so also. [ Uttering my name three times generally causes me to appear virtually or in person ]. Some modest contributions in the form of data management resources collection exist at this site but of more use is our community of collaborators . Join us for monthly DataEd webinars . Anything Awesome's purpose is to connect your organization with needed data resources. ​ These have ranged from student/class research projects at Virginia Commonwealth University ( where I am tenured ) to sponsored research. I have participated in ten, multi-year immersions with organizations ranging from Walmart to Deutsche Bank to Wells Fargo to the Department of Housing and Urban Development to Nokia to the US Army–in the process literally saving organizations a total of more than $1.5 billion (USD) ! ​ Anything Awesome is partially owned by VCU and exists to help organizations connect with resources that can assist them with their data challenges . Please do continue to bring me your data challenges of all shapes and sizes and I will connect you with capabilities that can help. Book an office 1/2 hour or just pick up the phone . If this seems vague, it is intentional because there are literally so many options . This is the best way to keep attention focused on the fuel that awesome things consume–your data ! Because it is always true that ...

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 My Career in Data Our good friends at Dataversity.net have a great podcast series that they invited me to speak on - from their program: ​ In our fifth episode we talk with Dr. Peter Aiken–Associate Professor at Virginia Commonwealth University, Associate Director of the MIT International Society of Chief Data Officers, and past president of DAMA International–about his winding road in data management and why he changed his mind about being an attorney!

Speaking (Its Alive) Often I'm asked to supply speaking samples–here are a few. I generally made a presentation each week for more than 20 years! Below are a few that have been recorded over the years. • [ Bad Data ] + Anything Awesome [ will always yield ] Bad Results • Data Literacy for Knowledge Workers • Exorcising the Seven Deadly Data Sins • Achieving Data Acumen • MIT Information Quality 2013 • Triple Play: Leveraging data requires leadership, value & strategy • Rethinking data education: data asset management requires business ownership ​ Bad Data+Anything Awesome will always yield Bad Results: Data Management from a Global Perspective Shanghai Data Exchange Back to Top ↑ Data Literacy for Knowledge Workers Fort Lauderdale Back to Top ↑ DAMA Mexico Exorcising the Seven Deadly Data Sins Back to Top ↑ Achieving Data Acumen: Improving Workforce Data Literacy (and therefore performance!) Online Somewhere Back to Top ↑ MIT Information Quality 2013 MIT Back to Top ↑ Triple Play: Leveraging data requires leadership, value & strategy Columbia Back to Top ↑ Rethinking data education: data asset management requires business ownership Las Vegas 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 Why "Anything Awesome?" that this is a concise [ ~ 1 minute] explanation as to why I find working on this end of these challenges is most rewarding! (you should also enjoy the accompanying audio-sampled in homage to deep thoughts on complex challenges)-so don't forget to turn up the sound!) (you may need to click play below)

Data Strategy and the Enterprise Data Executive Pervasive, data is a unique organizational resource, and this distinction warrants its own strategy. Data, representing your single non-depletable, non-degradable, durable strategic asset, is likely also your most poorly leveraged and underutilized organizational asset. Lack of talent, barriers in organizational thinking, and seven specific data sins prevent most organizations from benefiting fully from their data asset investments. Solving these prerequisites will allow your organization to: • Improve your organization's data; • Improve the way your people use data; and • Improve the way your people use data to achieve your strategy. This method better focuses data and thinking in direct support of strategic objectives. After eliminating necessary prerequisites, organizations can develop a disciplined and repeatable means of improving their data, literacy, standards, and controls using data governance practices. Once in place, the process (based on the theory of constraints) becomes a variant of lather, rinse, and repeat. Several complementary concepts covered include: • An overview of data strategy prerequisites; • A repeatable process for identifying and removing data constraints; • Why data strategy is necessary for effective data governance; • Balancing operational results with capability development; • An objective definition of data-centric thinking; and • Ways to monetize these efforts. Ensuring that Business and IT are in Synch in the Post-Big Data Era Check Price @ Amazon Buy this title direct from the publisher with a 20% discount using the code "anythingawesome" Check Amazon Reviews

Besides the VCU Business School Executive Educational Programs, my colleagues and I have presented executive education programs for companies including: Proctor & Gamble Nokia Walmart US DoD eBay Central European Bank Federal Reserve Bank CapitalOne Deutsche Bank Merck & Company Adastra World Bank Group Mattel Boeing US CentCom (for more detail on this sample offering click the .pdf ➜ many other configurations are possible including as part of a data leadership/mentoring program) Executive Education

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 What is Data? (based on definitions by Dan Appleton from Data-Driven Prototyping Datamation November 1983) 80% of data is ROT ​ The only argument I ever get is that "Our data is closer to 90% ROT" With 5 to 10 times as much chafe as wheat, organizations can benefit tremendously by taking a data centric approach to organizational improvement. Turns out to be all about demonstrating what happens in the organization when better data practices yield improvements . Some just do not understand data! I took this picture of a door at a resturant one day - it just doesn't seem to be the right combination? The Hitchhikers Guide to the Universe has a subplot that revolves around the fact that the meaning of life is 42. Let’s start at the most granular level–data is any combination of a fact and a meaning. For years we have asked groups: what does the number 42 mean? The answer is usually shouted back as: it's the meaning of life! A bit of explanation to the group and now we all share an understanding that 42 (fact) can be paired with a (meaning) “it (42) is the meaning of life.” That combination of fact and meaning constitutes a bit of data. Data is not the new Oil ​ Applying these same concepts to data makes little sense. The relative cost of acquiring data is most expensive the first time one uses it. Costs diminish with each subsequent reuse. Therefore, organizations are encouraged and financially rewarded to reuse data. (While Stylumia were not the first to coin this phrase, I did grab their very nice picture.) Oil’s value is based on scarcity. Data does not work this way, and applying these same concepts to data makes little sense in the information economy (see Barlow 1994 and the Atlantic's excellent roundtable on the subject). The relative cost of acquiring data is most expensive the first time one uses it. Costs diminish with each subsequent reuse. Data increases in value the more it is reused. Therefore, organizations are encouraged and financially rewarded to reuse data. Image from: https://medium.com/stylumia/data-is-not-the-new-oil-its-the-new-soil-212cf9ae2e4f