Local or Cloud
AI/ML Data Cleansing
Golden Record Pipeline
486 Patterson Ave
Winston-Salem, NC 27101
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11 Park Place
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
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Lange Dreef 11
4131 NJ Vianen
We don’t have to be industry analysts to know that better data equals better decisions.
Today, we’ll look at 5 ways blockchain technology can improve enterprise data quality and data management to make a lasting impact on a company’s operational success.
Working towards a distributed, verified system of record for better master data management.
Good master data management is part technology and part strategy – it involves building a comprehensive data management framework wherein critical data is integrated and leveraged as a single point of reference across the digital enterprise.
But in many cases, the enterprise is riddled with data silos, resulting in duplication of records and inaccurate or incomplete sets of information. These visibility issues are multiplied with the complexity of new business activity; for example, a merger or acquisition where sales, marketing, HR, financial and customer data is inconsistent in format, duplicated, and needs serious integration processes.
Blockchain technology can provide a single source of data truth for the data-driven enterprise – as one trusted and distributed system of record. We can crush data silos by logging master data on a distributed blockchain ledger and allowing our suite of applications to connect to and leverage this validated information.
In cases of multiple stakeholders (i.e. separate applications, separate business units, or even separate corporate entities), a distributed blockchain allows credentials/based access management for secure collaboration on master data. If we can trust and verify the data at its operational layer, we can build frictionless data pipelines to its relevant consumers.
The auditors are back – and it’s time to scramble to reproduce financial reports and email threads.
For many highly-regulated industries (Aerospace, Financial Services including Insurance and Banking, Healthcare), this scenario is a quarterly reality. And in all of these cases, the intended outcome is to reproduce data alongside a timestamp to prove compliance.
Blockchain technology provides turnkey compliance to every record in a system: by cryptographically hashing every transaction to the prior transaction, a blockchain database provides a native audit trail of verified transactions. This allows you to mathematically prove the legitimacy of data, its original source, its timestamp, and its complete historical path of changes through time.
In fact, the Fluree system natively provides “Time Travel Query,” a powerful query expression that can reproduce — and prove– any state of the database down to the millisecond. It’s like a highly-tamper proof git, but for all of your data.
Where did that data come from?
Sometimes databases are more like black boxes than sophisticated systems of record: update-and-replace with no notion of temporal state or original provenance. The average enterprise deploys 200+ SaaS apps – each with its own ‘black box.’ Furthermore, that ‘black box’ data is often replicated and ingested into new systems or data lakes for analysis and further operational application; visibility is eroded at every stage of reuse. In many cases, our mission-critical applications are leveraging data that, quite frankly, cannot be traced back to its original source.
Blockchain brings end-to-end traceability to every piece of data in your system — a guaranteed chain-of-data-custody. This means you instantly have visibility to data’s origination (SaaS or user) and you can track its complete path of changes across its lifecycle.
With Fluree, the traceability of changes are tied to digital signatures — including even third-party applications that sit between clients and data. How’s that for visibility?
Deliver trusted data across borders.
In today’s enterprise, information needs to traverse boundaries. Healthcare patient records need to be piped between carriers and hospitals. Government institutions need to securely share records between various agencies. Insurance carriers need to collaborate around claims data and contracts. Data is more useful and effective in the hands of many.
Blockchain technology can provide a trusted foundation for secure, real-time data collaboration across boundaries (application, organization, or even industry borders). With a unique structure of data ownership where various stakeholders have direct visibility into digital records, and even a vote on their validity, blockchain allows for every stakeholder across the data value chain to contribute to trusted sets of shared information. With real-time data visibility, stakeholders can more efficiently optimize business processes and make dynamic decisions.
If machines are going to be making more of our business decisions, shouldn’t they have access to trusted, tamper-proof data?
This particular use case might not be highly-relevant to enterprises that have not dipped the proverbial toe into production machine learning. But for those that have: the idea of explainable AI, or understanding the path of decision-making, is important. In extreme cases, like autonomous vehicles, explainable AI is essential. To bring back a metaphor from above, machine learning architects need a better way to explain results apart from opening the proverbial ‘black box.’
As more and more machine learning implementations make their way into the operational world, preserving data integrity and provable history will be a top priority; with more production deployments there will be more adversarial attacks.
Blockchain’s cryptography provides data with tamper-resistance for complete traceability into (a) how it got there and (2) its chain of updates through time. If we can arm the sources powering machine learning applications with this level of data integrity, replayability, and traceability, we can better understand causation in our models and protect them against “data poisoning” or other versions of data manipulation.
Fluree’s temporal dimension to data certainly provides this guarantee of instant and comprehensive replayability. Read more about time travel here.
At the end of the day, no matter which data management technology solutions you are deploying, better data equals better business decisions. Leaning into blockchain technology can increase the quality of your data and augment its value across the enterprise.
By arming data with native traceability, interoperability, context, and security — Fluree is enabling a new class of data-driven applications. Read more here, or sign up for free here!
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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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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.
Build your Verifiable Credentials/DID solution with Fluree.
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.
Build real-time data collaboration that spans internal and external organizational boundaries, with protections and controls to meet evolving data policy and privacy regulations.
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.
Our enterprise users receive exclusive support and even more features. Book a call with our sales team to get started.
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