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Welcome to part 1 of Fluree’s Data-Centric Series, where we peel back the layers of the data-centric architecture stack to explain its relevance to today’s enterprise technologies and shifting digital industry needs. At its core, Fluree is built around the concept that in order for data to be increasingly available, interoperable, and fundamentally usable—data must be backed with total provenance, security, and trust.
This first installment focuses on data “trust” and its impact across the broad spectrum of enterprise data management. Organizations are increasingly describing themselves as “data-driven,” which begs a few questions: what data is being used to “drive” the organization forward? Where did it come from? Can it be trusted? Could it have been manipulated by a third party, an admin, a SaaS middleware, or a central authority? Who can access it? Who has accessed, copied, or distributed it? What is the entire CRUD history?
As elusive as the term can be in a technical setting, we can agree that information being deployed in an operational or analytical setting should have a high degree of “trust.”
Here’s a checklist for what “trust” means to us at Fluree:
Summed up, trusting your data means you have complete control over and visibility into how your organization’s data is created, accessed and used across its entire lifecycle. Data-Centric trust involves securing CRUD operations across all data assets, managing attack surface visibility, and laying the foundation for complete “data audit trails.” In turn, data-centric trust allows the organization to scale security and compliance alongside new digital innovations.
We can think of trust as a key factor for conducting successful transactions between stakeholders in any given group (individual, enterprise, government), as well as any permutation of interaction (individual<>enterprise, government <> enterprise, enterprise<>enterprise, so on and so forth.)
Today, we’ll focus on a few areas that affect enterprises:
Executives have dozens of high-powered analytics tools at their disposal – so why do they continue to rely on “gut instinct” to make decisions? Mostly because they don’t trust the sandbox: If you can’t fully trust your data, you most likely won’t let data lead decisions for your company.There are three dimensions to data trust that must be satisfied:
Erosion of any of these three dimensions introduces risk to an organization.
With regulation around data ownership and privacy rapidly approaching the global market, organizations will need a solid plan on how to address these new pressures.
We spend hundreds of billions of dollars a year on auditing costs. A large amount of that cost is spent on simply verifying the validity around records to comply with various categories of compliance (Vertical and Horizontal).
Horizontally, PII compliance will need to scale alongside digital initiatives. Companies are already scrambling to satisfy GDPR and CCPA, and it will only get worse with “data-driven” innovation.
“The new European data privacy legislation is so stringent that it could kill off data-driven online services and chill innovations like driverless cars, tech industry groups warn.” Natasha Singer, NYT
“The new European data privacy legislation is so stringent that it could kill off data-driven online services and chill innovations like driverless cars, tech industry groups warn.”
Vertically, there are an array of industry regulations spread across the spectrum of digital maturity: HIPPA laws in healthcare or airworthiness compliance mandated by the FAA. In any of these cases, as technologies replace existing manual processes with data-centric processes, these compliance regulations must be accounted for digitally.
Instead of a never ending threat, these data regulations can be seen as an opportunity to re-imagine enterprise-wide data strategy with data quality, trust, and integrity in mind.
Integrating the tenets of data-centric trust into an enterprise GRC (Governance Risk and Compliance) strategy will be core to survival and success. Specifically, using temporal dimensions to managing data (see time travel with Fluree) allows companies to prove they were in compliance at all times versus a snapshot of times. Ledger-based data management systems like blockchain technology have the potential to automate much of these emerging data governance and compliance needs.
Data is becoming more collaborative as organizations realize the value of sharing information internally and externally to collectively solve problems. At the same time, industries are increasingly becoming “data ecosystems” with various levels of permissioned data sharing: supply chains, insurance companies, banks, and other industries that run on data are breaking down their four walls in the name of greater transparency, collaboration, and efficiency.
With this increase in collaboration comes a greater mandate to build systems for trusted data sharing. Here are a few examples of applied trust in data sharing:
Enterprises will increasingly need to share trusted data in real-time while managing associated risks such as inaccurate or manipulated data. Practicing data-centric trust in business ecosystems will greatly reduce the friction, time, and cost associated with validating, operationalizing or analyzing third party data. In turn, we can realize the benefits of more seamless data exchange (better customer outcomes, more reliable predictive models, more accurate shared databases, etc.)
Machines are making more and more autonomous decisions, drawing from more sources of data. Shouldn’t those decisions have a foundation of trusted and secure data? Machines will increasingly need to verify the validity, origin and integrity of the data they use to make operational decisions.
In terms of AI explainability, data-centric trust allows for a complete audit trail into why a decision was made.
In terms of AI security, we must build tools to fight against “data poisoning,” an emerging attack pattern that involves maliciously manipulating source data to affect the outcome of an algorithm.
As an operational data store, Fluree embeds trust directly into data. Fluree transactions include the following elements (in RDF-style):
Fluree then signs each transaction with the submitter’s unique key. Before committing the transaction, Fluree checks the transaction against various categories of rules (schema, validity, permission, and duplicate checks).
Fluree then combines transactions into immutable time-stamped ‘blocks’ and locks each block in via asymmetric cryptography (Sha3-256) for complete data integrity. This immutable ledger of data allows us to categorically prove time and source for every datum in the system (read more about Fluree’s unique architecture on our documentation site).
This process provides a few key outcomes for data:
Thanks for taking the time to read about trust, the first layer of Fluree’s Data-Centric architecture. Check out our post on the next layer, Semantic Interoperability.
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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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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.
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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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