Data Visualizations for Blockchain Applications: What Developers Need to Know (Part 1)
By: Qlik Branch Staff
Tags: IoT, Data Visualization, Dataviz, Blockchain, Analytics

By Twain Taylor

While Blockchain is most commonly known as the platform behind cryptocurrency, increasingly, enterprises are seeing opportunities to leverage Blockchain to solve the complex challenges they face.

And as that happens, enterprises need better ways of interpreting and managing blockchain data. That is why data visualizations are playing increasingly important roles in enterprise blockchain applications.

In this two-part post, I discuss how enterprises are currently using (or at least experimenting with) blockchain applications and explain the role that data visualization is playing in enabling them to work more effectively with blockchain data.

The goal is to help developers who will be working on enterprise blockchain applications to understand how they can leverage data visualizations to perform this type of work more effectively.

Enterprise use cases of blockchain technology

Smart contracts

A smart contract is an application that contains a set of rules and penalties for a contract that parties agree to, and are enforced automatically. Smart contracts run on top of blockchain technology, and particularly leverage the distributed nature of blockchain to take into account the complexities of a contract, and execute it with high reliability.

For example, Walmart uses smart contracts built on the IBM Blockchain platform to track the freshness of its green food deliveries. It tracks these products using edge devices that send back data to an IoT backend.

GE uses smart contracts to track the amount of energy consumed from a source like a battery, and enables organizations to limit the amount of total energy consumed and ensure their batteries are healthy. Not only does the smart contract help to monitor, it also helps take action, and automates actions like these at scale.

Distributed applications

Blockchain greatly enhances application architecture by enabling distributed apps or DApps. DApps change the way data for applications is stored, accessed, and managed. Rather than having centralized data stores, DApps enable decentralized data stores that are highly resilient, and aren’t prone to failure.

IoT backend systems

Blockchain is also changing the way IoT systems function. With numerous edge devices that generate large quantities of data, IoT requires a software layer that can take into account this data and analyze it. Blockchain is the answer to data analysis for IoT. It can bring great visibility into machine-to-machine communication and enable use cases in supply chains (similar to the one we saw with Walmart earlier).

Security operations

Blockchain is being applied to solve the complex problem of security for modern cloud-native applications. In these applications, sensitive data is encrypted using Blockchain. Once this data is encrypted, its access and usage are governed with full transparency by the administrator. During an incident, it’s possible to identify any bad actors easily.

Healthcare data management

The healthcare sector handles a considerable amount of sensitive data, like patient health information (PHI) and electronic health records (EHR). This data needs to be managed with robust security and strong access controls. Blockchain applications can provide the level of security and access controls that healthcare applications need.

Financial transactions

In the banking sector, cross-border transactions are cumbersome. They take two or more days, require an intermediary agent to approve, and they are expensive. Blockchain is making these transactions faster and easier. It eliminates the need for a middleman, and lets transactions happen from one party to another.

Predictive analytics

Blockchain can be used to predict future scenarios and make projections because of the large quantities of data it deals with. Startups like Endor are pioneering this effort. Whether it’s to predict a possible security attack or a purchase by a consumer, blockchain is bringing new levels of accuracy to predictive analytics.

Data visualization for enterprise blockchain

Data plays a key role in numerous real-world applications for Blockchain in the enterprise. Analyzing data efficiently requires the use of data visualization. Let’s look at what matters when crafting visual dashboards and charts for blockchain applications.

Numerous data points

Simple bar charts are good for visualizing a few data points, but with Blockchain, you typically need to visualize numerous data points. This requires a chart type that can help visualize data at scale. An example of this would be a scatter plot chart which helps show concentration, and helps identify broad trends across large quantities of data.

Connections between pieces of data

In Blockchain, data is distributed, and there are connections between pieces of data that sometimes need to be analyzed. Visualization is a great tool for this, as it lets you see connections in an interactive and engaged way. A network chart is a great option for analyzing connections between pieces of data.

Source: AWS

Another important aspect of data visualization is the ability to drill down or zoom into more specific pieces of data from an overview level. This makes for an interactive data experience, and helps zero in on precise prices of data.

Progression over time

Blockchain records events in minute detail (for example, in an IoT application where a product is tracked across the supply chain using edge devices). Here, Blockchain can record every event in the journey of the product. This data can be visualized using flowchart-like diagrams — but further, they should allow deeper analysis by revealing smaller details about each event via drill- downs and zooming.

One example of this type of data visualization is seen in stock ticker apps where a stock symbol’s performance over the past 10 years can be plotted using a line chart. You can mouse over the chart to see the stock’s price on any single day during this time period. It’s a great way to see how a data point has progressed over time, and to deep-dive into any specific time period.

Predictive data visualization

The vast quantities of data in a blockchain application can be used in many predictive scenarios. To enable this, an analytics tool should have chart types that enable predictive visualization and features like trendlines. Charts that allow for user input (like visually adjusting the future projections on a chart) enable predictive analytics for Blockchain.

Threat analysis

When Blockchain is used for security purposes, it needs to enable investigation into incidents. This includes initial alerting of a security incident, further analysis of the attack surface, and possible remedial measures. Here, data visualization can help by surfacing outliers from normal data. Usually, security incidents result in abnormal behavior, and visualization helps spot this across a complex system.

Additionally, threat analysis requires real-time charts. With security, every second counts, and real-time charts give you the edge to identify the source and origin of the attack and respond quickly.

Exploratory data analysis

Blockchain has the ability to deliver new and surprising insights because of the depth of data it provides. Gleaning this kind of insight takes interactive data visualization. Rather than query-based visualization, you need interactive point-and-click and drag-and-drop interfaces that speed up data analysis.

In Part II of this series, we will cover developer priorities for blockchain data visualization and discuss how developers play a key role in defining how data is analyzed — and how the blockchain applications built are used.

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About the Author

Twain Taylor is an external paid contributor via Fixate.io. He began his career at Google, where among other things, he was involved in technical support for the AdWords team. His work involved reviewing stack traces and resolving issues affecting both customers and the Support team — and handling escalations. Later, he built branded social media applications and automation scripts to help startups better manage their marketing operations. Today, as a technology journalist, he helps IT magazines and startups change the way teams build and ship applications.