Enterprise Blockchain in 2020: Challenge 1 – Data Availability

As enterprises move from exploration towards proofs-of-concept and beyond, six common challenges to overcome have emerged in order to successfully deploy. Today, we take a look at the lack of data availability on blockchains for enteprise decision-making and operational use.

This post is the first ‘chapter’ in a series of articles written in collaboration between a blockchain platform vendor Fluree and a systems integrator, Codete. Drawing from collective expertise from both a technology vendor and a software development company perspective, we’ll provide insight into overcoming common hurdles in implementing blockchain technology and best practices for operational success in DLT projects.  



Challenge 1: The Lack of Data Availability for Decision Making

Many of us who have worked in enterprises for much of our careers know that at most companies, data resides all over the place. Often the solution to reign in the data silos involves large IT infrastructure projects that attempt to bring enterprise employees and decision-makers to a single source of truth. However, these solutions were often built on top of relational databases, with rigid data syntax and patterning requirements that mandate the use of middleware. These implementations often cost tens of millions of dollars, and an army of certified third-party implementation consultants to deliver results.

Blockchain technology was promised to eliminate these data silos and was pitched as the “single source of truth” silver bullet. However, as we now know, the implementation of the technology in practice has fallen well short of this goal. In many of these implementations, the actual data storage must be separated from the blockchain ledger because of the burden that data “on-chain” brings with regard to the speed/complexity of access to the data.

This, in turn, drives the need for application tier logic and third-party libraries to be deployed in order to connect the execution of queries and transactions with the data store(s) themselves. In many cases, this is not a single data store, but rather disparate data warehouses, data lakes, and other data silos within the organization and with business partners. This disunion of siloed information makes it very challenging for decision-makers to glean appropriate data in a timely manner for decision making. Folks are left scratching their heads: “Why did we add blockchain, to begin with?”

In order for Blockchain to provide its full return-on-investment to digital enterprises, data and metadata need to be efficiently queryable by users without having to learn a new way of thinking and platform-specific “language.” But how? 

This requires building your blockchain solution on data standards that are extensible and interoperable for spanning legacy data stores as well as new modern data structures. In this way, you can not only leverage the data residing in the blockchain, but also its many inherent traceability benefits; where all activities on the platform — including the provenance of the data and with user roles, rules, and authorization — are controlled and visible at the data layer itself. One key standard for data interoperability is RDF (Resource Description Framework), a W3C-endorsed model for information that simplifies and enables data interchange. 

In our experience at Fluree, storing data in RDF on-chain with privacy controls baked in helps solve some of these key integration issues. No sticky integrations or extra layers  —  just one, queryable blockchain data store optimized for enterprise applications. To support this, we developed an integrally linked FlureeDL (Distributed Ledger) and FlureeDB (Graph Database) data management platform, whereby data stored in the graph database is one and the same as the transactional records stored in the blockchain ledger. With Fluree, the data is stored as extended RDF-triples — on Fluree time and metadata elements are added to the RDF subject-predicate-object model to facilitate full history and metadata addition. 

With this, the database can be queried seamlessly with other data sources via SPARQL queries as if the data were co-resident on the same platform. RDF format is especially useful in preparing enterprise data for business intelligence operations and Master Data Management analysis.  

Additionally, since the time-domain is represented in every data change, historical reviews for analysis, to support compliance, and for auditing are possible. This brings actionable data to the enterprise decision-makers that need it.



Fluree is a blockchain-backed data management platform. Founded in 2016 by Flip Filipowski and Brian Platz, Fluree is headquartered in Winston-Salem North Carolina. The Fluree platform organizes blockchain-secured data in a highly-scalable, highly-insightful graph database — allowing businesses to develop applications with foundational data-centric trust, interoperability, and security. Fluree has experience in working with partners, like Codete, in developing next-generation applications, interoperable data sources, and data-driven ecosystems for a variety of industries and enterprises.

Codete is an IT consulting and software development company. Since 2010, we’ve been supporting businesses worldwide in gaining competitive advantage by means of modern technology. Codete has over 10 years in the market and has completed over 100 projects for enterprise clients. The company now employs over 150 IT professionals delivering full-stack solutions for advanced data management and reporting. Codete leverages the right technologies to meet different client needs and has worked with a diverse group of technology providers, including Fluree, to provide optimal solutions. 

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