AI Golden Record Pipeline
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486 Patterson Ave
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New York, NY, 1007
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Bagmane Laurel, Krishnappa
Garden, C V Raman Nagar,
Karnataka 560093, India
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1644 Platte Street
Denver, CO 80202
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The world of blockchain spans from total decentralization (referred to as “crypto-minimalism) to federated distributed ledgers to private cryptographically-secured databases. Across all of these use cases, digital trust is a core benefit of employing the crypto-based elements of a blockchain ledger. For an enterprise data environment, DLTs can lock transactions in a cryptographically-secured database in such a way that information can be verified and traced back to its originator with ease.
Every update to a ledger-backed database is timestamped and embedded into a “block” of data, cryptographically secured by a hashing process that incorporates the hash of the previous block, and joins the ledger as the next chronological update.
In the same way that blockchain provides digital trust for transactions between third parties, distributed ledger technologies leverage cryptography and hashing to build an immutable, verifiable audit trail for records in a database or application. These benefits can be leveraged practically for a developer building an app or integration, for departments of highly-regulated businesses conducting audits, or for data scientists building ethical and explainable AI.
Let’s look at 3 practical applications for ledger-backed data management for organizations:
Non-repudiation is a legal concept that means someone cannot deny the authenticity of something – a piece of information, a document, a signature, etc. Widely used in industries where trust is essential between parties, such as law, finance, or insurance, non-repudiation is an essential information security practice that provides proof of the origin and authenticity of information as it is exchanged between parties.
Blockchain provides a perfect platform for businesses to practice non-repudiation. The use of digital signatures and public/private key cryptography allows for information to be digitally verified by parties sending or receiving messages. As a result, organizations can adopt better non-repudiation mechanisms for digitally signing documents or retrieving verified messages, which increases the speed and scale of their third-party business dealings.
Having an immutable log of data changes provides immense benefits – developers can identify, review, and pull all of the changes to a database and make use of the historical information in another system. Because blockchain preserves every state to a ledger database, developers can capture those changes for review analytically or for use in another system. Developers can begin to ask the ledger for historical information, such as “What did the data look like at this point in time, and how has it changed since then?”
A blockchain ledger can also provide professionals in highly-regulated industries with data provenance guarantees and replayability for instant data audit and reporting. Financial services, healthcare, and other regulated systems can use ledger databases to reproduce data alongside a timestamp to prove compliance.
In the fields of machine learning and artificial intelligence, data scientists are increasingly concerned with the concept of “explainable AI,” a process in which humans can review, comprehend, and trust the output results of an algorithm. Explainable AI practices help data scientists retrace and explain the results of an AI algorithm, which allows for fairness and transparency in AI development.
If input data existed in a blockchain database system, AI professionals could build tools to audit the algorithm thoroughly to reveal important information on explainability. By providing an immutable and cryptographically-secured approach to data management, a blockchain structure delivers a historical lens for data scientists to review and assess.
Blockchain can also provide a defense against adversarial attacks to AI algorithms, fighting against “data poisoning” in which attackers will manipulate input data in order to modify the outcome of an algorithm. By leveraging blockchain’s source of truth and anti-manipulation cryptography, AI developers can guarantee that an algorithm is using authentic data from verified sources.
Leveraging a blockchain-secured database can provide organizations with a foundation for trusted and traceable information management. The applicability spans far and wide – from generalized data audit capabilities to industry-specific use cases such as digital evidence management systems (DEMs), AI Explainability systems, or compliance reporting. Whichever the scenario, blockchain can help move organizations away from “black-box” reporting and into a more transparent, accurate, and trusted system for data management.
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Partner, Analytic Strategy Partners; Frederick H. Rawson Professor in Medicine and Computer Science, University of Chicago and Chief of the Section of Biomedical Data Science in the Department of Medicine
Robert Grossman has been working in the field of data science, machine learning, big data, and distributed computing for over 25 years. He is a faculty member at the University of Chicago, where he is the Jim and Karen Frank Director of the Center for Translational Data Science. He is the Principal Investigator for the Genomic Data Commons, one of the largest collections of harmonized cancer genomics data in the world.
He founded Analytic Strategy Partners in 2016, which helps companies develop analytic strategies, improve their analytic operations, and evaluate potential analytic acquisitions and opportunities. From 2002-2015, he was the Founder and Managing Partner of Open Data Group (now ModelOp), which was one of the pioneers scaling predictive analytics to large datasets and helping companies develop and deploy innovative analytic solutions. From 1996 to 2001, he was the Founder and CEO of Magnify, which is now part of Lexis-Nexis (RELX Group) and provides predictive analytics solutions to the insurance industry.
Robert is also the Chair of the Open Commons Consortium (OCC), which is a not-for-profit that manages and operates cloud computing infrastructure to support scientific, medical, health care and environmental research.
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Founder, DataStraits Inc., Chief Revenue Officer, 3i Infotech Ltd
Sudeep Nadkarni has decades of experience in scaling managed services and hi-tech product firms. He has driven several new ventures and corporate turnarounds resulting in one IPO and three $1B+ exits. VC/PE firms have entrusted Sudeep with key executive roles that include entering new opportunity areas, leading global sales, scaling operations & post-merger integrations.
Sudeep has broad international experience having worked, lived, and led firms operating in US, UK, Middle East, Asia & Africa. He is passionate about bringing innovative business products to market that leverage web 3.0 technologies and have embedded governance risk and compliance.
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CEO, Data4Real LLC
Julia Bardmesser is a technology, architecture and data strategy executive, board member and advisor. In addition to her role as CEO of Data4Real LLC, she currently serves as Chair of Technology Advisory Council, Women Leaders In Data & AI (WLDA). She is a recognized thought leader in data driven digital transformation with over 30 years of experience in building technology and business capabilities that enable business growth, innovation, and agility. Julia has led transformational initiatives in many financial services companies such as Voya Financial, Deutsche Bank Citi, FINRA, Freddie Mac, and others.
Julia is a much sought-after speaker and mentor in the industry, and she has received recognition across the industry for her significant contributions. She has been named to engatica 2023 list of World’s Top 200 Business and Technology Innovators; received 2022 WLDA Changemaker in AI award; has been named to CDO Magazine’s List of Global Data Power Wdomen three years in the row (2020-2022); named Top 150 Business Transformation Leader by Constellation Research in 2019; and recognized as the Best Data Management Practitioner by A-Team Data Management Insight in 2017.
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Senior Advisor, Board Member, Strategic Investor
After nine years leading the rescue and turnaround of Banco del Progreso in the Dominican Republic culminating with its acquisition by Scotiabank (for a 2.7x book value multiple), Mark focuses on advisory relationships and Boards of Directors where he brings the breadth of his prior consulting and banking/payments experience.
In 2018, Mark founded Alberdi Advisory Corporation where he is engaged in advisory services for the biotechnology, technology, distribution, and financial services industries. Mark enjoys working with founders of successful businesses as well as start-ups and VC; he serves on several Boards of Directors and Advisory Boards including MPX – Marco Polo Exchange – providing world-class systems and support to interconnect Broker-Dealers and Family Offices around the world and Fluree – focusing on web3 and blockchain. He is actively engaged in strategic advisory with the founder and Executive Committee of the Biotechnology Institute of Spain with over 50 patents and sales of its world-class regenerative therapies in more than 30 countries.
Prior work experience includes leadership positions with MasterCard, IBM/PwC, Kearney, BBVA and Citibank. Mark has worked in over 30 countries – extensively across Europe and the Americas as well as occasional experiences in Asia.
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Chair of the Board, Enterprise Data Management Council
Peter Serenita was one of the first Chief Data Officers (CDOs) in financial services. He was a 28-year veteran of JPMorgan having held several key positions in business and information technology including the role of Chief Data Officer of the Worldwide Securities division. Subsequently, Peter became HSBC’s first Group Chief Data Officer, focusing on establishing a global data organization and capability to improve data consistency across the firm. More recently, Peter was the Enterprise Chief Data Officer for Scotiabank focused on defining and implementing a data management capability to improve data quality.
Peter is currently the Chairman of the Enterprise Data Management Council, a trade organization advancing data management globally across industries. Peter was a member of the inaugural Financial Research Advisory Committee (under the U.S. Department of Treasury) tasked with improving data quality in regulatory submissions to identify systemic risk.
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Turn Data Chaos into Data Clarity
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Pawan came to Fluree via its acquisition of ZettaLabs, an AI based data cleansing and mastering company.His previous experiences include IBM where he was part of the Strategy, Business Development and Operations team at IBM Watson Health’s Provider business. Prior to that Pawan spent 10 years with Thomson Reuters in the UK, US, and the Middle East. During his tenure he held executive positions in Finance, Sales and Corporate Development and Strategy. He is an alumnus of The Georgia Institute of Technology and Georgia State University.
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Andrew “Flip” Filipowski is one of the world’s most successful high-tech entrepreneurs, philanthropists and industry visionaries. Mr. Filipowski serves as Co-founder and Co-CEO of Fluree, where he seeks to bring trust, security, and versatility to data.
Mr. Filipowski also serves as co-founder, chairman and chief executive officer of SilkRoad Equity, a global private investment firm, as well as the co-founder, of Tally Capital.
Mr. Filipowski was the former COO of Cullinet, the largest software company of the 1980’s. Mr. Filipowski founded and served as Chairman and CEO of PLATINUM technology, where he grew PLATINUM into the 8th largest software company in the world at the time of its sale to Computer Associates for $4 billion – the largest such transaction for a software company at the time. Upside Magazine named Mr. Filipowski one of the Top 100 Most Influential People in Information Technology. A recipient of Entrepreneur of the Year Awards from both Ernst & Young and Merrill Lynch, Mr. Filipowski has also been awarded the Young President’s Organization Legacy Award and the Anti-Defamation League’s Torch of Liberty award for his work fighting hate on the Internet.
Mr. Filipowski is or has been a founder, director or executive of various companies, including: Fuel 50, Veriblock, MissionMode, Onramp Branding, House of Blues, Blue Rhino Littermaid and dozens of other recognized enterprises.
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Brian is the Co-founder and Co-CEO of Fluree, PBC, a North Carolina-based Public Benefit Corporation.
Platz was an entrepreneur and executive throughout the early internet days and SaaS boom, having founded the popular A-list apart web development community, along with a host of successful SaaS companies. He is now helping companies navigate the complexity of the enterprise data transformation movement.
Previous to establishing Fluree, Brian co-founded SilkRoad Technology which grew to over 2,000 customers and 500 employees in 12 global offices. Brian sits on the board of Fuel50 and Odigia, and is an advisor to Fabric Inc.
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Eliud Polanco is a seasoned data executive with extensive experience in leading global enterprise data transformation and management initiatives. Previous to his current role as President of Fluree, a data collaboration and transformation company, Eliud was formerly the Head of Analytics at Scotiabank, Global Head of Analytics and Big Data at HSBC, head of Anti-Financial Crime Technology Architecture for U.S.DeutscheBank, and Head of Data Innovation at Citi.
In his most recent role as Head of Analytics and Data Standards at Scotiabank, Eliud led a full-spectrum data transformation initiative to implement new tools and technology architecture strategies, both on-premises as well as on Cloud, for ingesting, analyzing, cleansing, and creating consumption ready data assets.
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Get the right data into the right hands.
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Wherever you are in your Knowledge Graph journey, Fluree has the tools and technology to unify data based on universal meaning, answer complex questions that span your business, and democratize insights across your organization.
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Fluree Sense auto-discovers data fitting across applications and data lakes, cleans and formats them into JSON-LD, and loads them into Fluree’s trusted data platform for sharing, analytics, and re-use.
Transform legacy data into linked, semantic knowledge graphs. Fluree Sense automates the data mappings from local formats to a universal ontology and transforms the flat files into RDF.
Whether you are consolidating data silos, migrating your data to a new platform, or building an MDM platform, we can help you build clean, accurate, and reliable golden records.
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