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
Denver, CO 80202
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Lange Dreef 11
4131 NJ Vianen
It was fall 2008, and Eliud Polanco had a problem. The financial crisis had just hit. Polanco, a data & analytics expert, was sifting through endless Excel spreadsheets and mainframe printouts to figure out the risk exposure to the large, global universal bank where he worked. The spreadsheets contained information about the financial products sold and traded, as well as risk forecasts and models produced by quants—quantitative analysts who wrote code for pricing, high-speed trading and profit maximization. Not only was the data within the mainframe reports and spreadsheets complex, but they were spread out around the world.
This was in one of the largest Banking institutions in the world, with offices in 100+ countries and hundreds of thousands of employees. Branches, departments, and countries had their own systems that were designed to make day-to-day life easier for the functions where people worked in. When you zoomed out and tried to look at all those systems as a whole, however, things grew chaotic.
One of Polanco’s first steps was to put everything in a data warehouse, which then evolved into one of the largest data lakes at the time. He then methodically tried to query and sort the data using every analysis tool on the market. All of them came up short.
It wasn’t terribly surprising. Master data management, the ability to view, manage, and analyze all data from a single pane of glass, has always been an elusive goal. Big, complex organizations have data in an array of siloes, from cloud applications like Salesforce to custom-built, department-specific ERPs. Trying to work with all the data in one place requires automation, and that, in turn, leads to unanticipated consequences. Software updates changing data is a common example. Approximately 62 billion hours of data and analytic work “are lost annually worldwide due to analytic inefficiencies,” according to the Data and Analytics in a Digital-First World report.
Polanco decided to build his own master data management platform. The software should help him understand not only the big picture of the organization’s data, but enable him to dig into specifics without getting mired in bug fixes. Wall Street has long been a first mover in AI- and machine learning applications, and Polanco took that innovative mindset into his platform, using unsupervised machine learning to crawl data, and supervised machine learning to ask humans the right questions about that data.
The result was ZettaLabs, now Fluree Sense. By taking advantage of two kinds of machine learning, Fluree Sense organizes even the most diverse and chaotic data to 90th percentile accuracy. When you send a query, an unsupervised machine learning algorithm crawls data sets in your data lake and aggregates together potential answers. Next, a supervised machine learning algo does entity resolution, grouping together names, addresses, etc and so on that seem to refer to the same person or object. The algo then creates questions for humans to answer, and fires them off to subject matter experts. The experts respond, the algo learns, and Fluree Sense serves up your data on a color-coded plate.
In a company as complex as the large global Bank, ZettaLabs/Fluree Sense was a boon. Polanco was able to complete the seemingly impossible organization of quant data. He also realized that many other big organizations had chaotic data sets, and built a company around his software. Zettalabs/Fluree Sense went on to be used for fraud and money laundering risk detection as well as for customer-facing purposes, such as new customer acquisition, upsell/cross-sell opportunities, and customer delinquency/churn.
Fluree has long known that organizations are going from data as a byproduct—where it is stuck in cloud instances and other siloes—to data being the product. Those organizations that can leverage data effectively will come out ahead in the transition to Web3. Designed for Web3, Fluree lets users wrap policy around data for permissions, allow machines to collaborate around data, lets users time travel to verify and validate data during different moments in time, as well as other data-centric features.
An ecosystem of startups and enterprise and governmental pilot programs flourished on Fluree. Big, complex organizations with legacy data, however, still had their mess of existing data to figure out. ZettaLabs was designed to figure out a mess of existing data, providing a bridge between legacy data infrastructure and data-centric Web3.
“Dealing with legacy infrastructure is one of the biggest challenges for modern businesses, but nearly 74% of organizations are failing to complete legacy data migration projects today due to inefficient tooling and a lack of interoperability,” said Fluree CEO and Co-Founder Brian Platz. “By adding the ZettaLabs team and product suite to our own, Fluree is poised to help organizations on their data infrastructure transformation journeys by uniquely addressing all major aspects of migration and integration: security, governance, and semantic interoperability.”
“We developed our flagship product, ZettaSense, to ingest, classify, resolve and cleanse big data coming from a variety of sources,” said Eliud Polanco, co-founder and CEO of ZettaLabs, who will become Fluree’s president. “The problem is that the underlying data technical architecture—with multiple operational data stores, warehouses and lakes, now spreading out across multiple clouds—is continuing to grow in complexity. Now with Fluree, our shared customer base and any new customers can evolve to a modern and elegant data-centric infrastructure that will allow them to more efficiently and effectively share cleansed data both inside and outside its organizational borders.”
Digital transformation is a journey that often takes multiple years. Clean data by collecting, integrating, reconciling, and remediating it across the organization is the gargantuan first step—and a massive technical challenge. Most big organizations have multiple databases and operational data stores, much of it containing low-quality data. Even after purchasing data warehouses and governance tools, organizations find their analytics stymied by data quality.
Then there are cultural challenges. Business units often have their own data stores that are custom configured, often in SaaS software such as a Salesforce instance. Merging that instance into an organization-wide process and workflow is an interruption to daily life—and threatens the KPIs of that business unit. Imagine you’re a salesperson with a quota to reach, and IT comes in wanting to reconfigure your Salesforce for a few months. The resistance is understandable but also delays digital transformation.
Fluree Sense solves the problem by getting data activation-ready within weeks, not months. The machine learning algorithm crawls data lakes, automatically integrating and cleansing data. The combination of supervised- and unsupervised ML quality assures 90% of data, leaving a far reduced human workload. Cleaned and quality-assured data becomes available to the entire organization, accelerating the move to modern data-centric architecture.
With Fluree Sense, you can:
For a large enterprise, data migration costs up to $150 million. Fluree Sense can successfully operate at a small fraction of that cost. Organizations can consolidate business data from various stores—sometimes dozens of warehouses—onto the single cloud that is their data lake. Fluree Sense organizes and cleans it in one place, with a small team using low- and no-code software to manage data. Time-to-value from raw data to business consumption is reduced from months to weeks. Data scientists, analysts, and business users can access data through tools such as Tableau, Synapse, and Databricks – or, in the near future, a secure Fluree Core instance for a true ASOT (authoritative source of truth).
There is also an easy path to Fluree’s Web3 features, which include data audit and compliance solutions, verifiable credentials, data-centric applications, decentralized apps, and enterprise knowledge graphs. By making data usable and freeing it to be applied in Web3 architectures, Fluree Sense is shortening the timeline to digital transformation and making even the most chaotic data architectures Web3-ready.
To learn more about the Fluree Sense product, sign up for our webinar: Introduction to Fluree Sense.
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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.
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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