How data visualization can solve your Big Data ROI problem

Connected data is everywhere, and it’s growing at an exponential rate. It’s predicted that by 2025, there’ll be 175 zettabytes of data in the global datasphere.

At Cambridge Intelligence, we’ve found that for many organizations, ‘big data’ means collecting every bit of information available - call records, financial transactions, email traffic, etc. - then figuring out how to use it. It’s a costly challenge: once you’ve invested heavily in gathering the data, how do you uncover the value hidden inside it?

The first step is to get the data into a format that anyone can explore and understand. That’s where interactive data visualization comes in.

It’s the most effective way to bring your data to life, revealing patterns and connections that’d be difficult to find in millions of rows of raw data. The value comes from making the data accessible to users, turning something unusable into a powerful source of insight.

The big data explosion: data visualization brings connected data to life

Why visualize data?

Exploring data visually instantly makes sense, even to people who’ve never worked with complex connected data before. That’s because our brains are great at spotting patterns, but only when they’re presented in a tangible format.

Seeing this visualization for the first time - built using our KeyLines toolkit - you immediately spot connections between key people in the network even if you don’t understand the context yet

Most adults can only store between 4 and 7 items in their short term memory, so we’re definitely not big data creatures. It’s not enough just to present a huge dataset in a visual way; data visualization applications must also provide the tools to simplify complexity, filter out noise, and drill down on the right details.

By interacting with the data, changing the way it’s laid out, running sophisticated algorithms at the touch of a button, plotting the data onto maps, users gain much deeper knowledge and understanding.

What do we mean by data visualization?

In this article, we’re focusing specifically on connected data visualization, primarily:

  • Graph visualization - sometimes called link analysis or network visualization - is the process of visually presenting networks of connected entities as nodes and links. It goes beyond the ‘flat’ data model by creating a fully-interactive view. JavaScript and React developers use our KeyLines and ReGraph toolkits to create powerful graph visualization applications.

  • Timeline visualization focuses on presenting the order in which events occurred to uncover important patterns and connections. Sometimes it’s the sequence of events through time that’s the most important element in the data. You need a visual way to reveal the hidden stories. KronoGraph, our timeline visualization toolkit, is for building web-based timeline applications.

Combine both graph and timeline visualization, and you get a powerful 360-degree view of your dataset.

Data visualization at its best: a network chart to explore connections

and timelines to examine how and when events unfold

Who needs to visualize their data?

This style of data visualization isn’t new - law enforcement and government agencies have used visual link and timeline analysis for decades to help ‘join the dots’ in their investigations. But the visualization tools they used were inflexible, complex, and available to only a select few expert analysts.

What has changed in recent years is the availability of technology like ours that makes understanding connected data a simpler, scalable process.

For many years, Cambridge Intelligence’s technology has helped drive the success of organizations working in fraud detection, security and intelligence, and cybersecurity. We’re now working with many other industries who recognize the untapped possibilities in the connected data they’re collecting.

Broader domains including compliance, healthcare, business intelligence, supply chain management and IT infrastructure all benefit from exploring data and uncovering important insight.

Visualizing European energy infrastructure in its real-world context

is essential for managing and monitoring supply chain

Let’s take a closer look at two data visualization use cases of particular value to the Southeast Asian market: cybersecurity and blockchain.

Combating cyber threats

The growing threat of cyber attack means security is no longer just the concern of governments and law enforcement – it’s everyone’s responsibility.

INTERPOL’s recent Association of Southeast Asian Nations (ASEAN) Cyberthreat Assessment highlights the need for law enforcement agencies and the private sector to work together to tackle cyber crime. The threat from highly-organized cyber criminals is growing exponentially in ASEAN, and data visualization should be at the heart of every effective response to combat it.

Visualising attackers and victims in a data breach investigation helps

to identify trends and uncover active threats

Visualizing blockchain & cryptocurrency

The blockchain market in Southeast Asia is more advanced than in other major global regions, with many progressive fintech firms leading the way in the cryptocurrency space.

As it’s popularity grows, the challenge to protect cryptocurrencies from exploitation gets harder, and anti-money laundering compliance regulations get tougher. According to blockchain firm, Ciphertrace, 2019 saw a 533% increase in losses from cryptocurrency fraud, scams, and theft, totaling around $4.5bn.

Cryptocurrency data is connected by design, so it’s a perfect fit for data visualization. Through visualizing complex connections, you start to understand the exchange patterns and anomalies that exist in an ever-expanding network.

When you visualize a Bitcoin block you spot distinct shapes and patterns right away

The powerful graph data stack

According to a 2019 Gartner report, the graph technology market has huge growth potential.

Key to a successful graph data stack is the ability to integrate data visualization tools quickly and easily with any data source. That’s exactly what Cambridge Intelligence’s technology does.

Unsurprisingly for graph visualization, the most popular integration option is the graph database. Graph data is perfect for visualizing because the relationships in the data are as important as the data itself. And all the things we need to be able to visualize the data - connections, entities and properties - are built in already.

In Southeast Asia, we’re seeing significant growth in the graph technology market, in part driven by the rise of scalable and robust graph databases, particularly Neo4j, Amazon Neptune and CosmosDB. Through seamless integration with whichever graph database you choose, getting started with graph visualization has never been easier.

Integrating with a Neo4j graph database of Twitter data creates an effective graph

and timeline visualization for spotting patterns fast

Investing in your data

The future looks bright for data visualization as more and more Southeast Asian organizations recognize the need to get the right return on investment in data collection, storage and management.

With graph and timeline visualization, the focus is always on the most valuable element: the data itself. By making that data accessible and providing easy-to-use analytical capabilities, users can uncover hidden insight fast.




Joe Perry is the CEO an d Co-Founder of Cambridge Intelligence

Cambridge Intelligence is part of our Tech National International Growth Program in Singapore.

To find out more about our programs in Singapore, click here.

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