From contact tracing to personalised offers, there are many real-life examples of how data is crucial to modern society.
The good news is that there will be plenty of data available in the future, with data creation and replication expected to grow at a faster rate than installed storage capacity over the next five years. However, simply having a massive volume of data will not guarantee business success. Organisations will need to harness insights from the data to unlock its transformative value.
Singapore businesses have a long way to go in this aspect. Sixty-nine percent of local SMEs surveyed last year said they were not using data analytics tools, according to a joint study by Singapore Institute of Technology (SIT), RSM Singapore and the Institute of Singapore Chartered Accountants (ISCA). This could have led to missed revenue opportunities, which would in turn affect Singapore’s economic recovery as SMEs collectively contribute to nearly half of the country’s GDP.
As for adopters, many would have relied on traditional data analytics such as relational databases and data warehouses. While those solutions excel at collecting and processing data, they miss the relationships between data points to provide more in-depth insights.
This is where graph analytics can help. With graph technology, data is analysed in the form of a graph to look for relationships between entities such as people, transactions or organisations.
“Graph technology has the ability to connect multiple domains from traditional relational databases, offering the opportunity to shrink development cycles for data preparation, improve data quality, and identify new insights such as similarity patterns to deliver the next best action recommendation,” explains Joe Lee, vice president for Asia Pacific & Japan at graph database company TigerGraph.
Lee goes on to share that graph technology is already being used in our everyday lives. “Companies such as Facebook, Instagram and Twitter have been using graph databases and analytics to understand how users relate to each other and connect them with the right content,” he says. “For instance, when you visit LinkedIn and see first-, second- or third-degree connections, those results are from the social networking site’s network graph built on a graph database.”
Enhancing processes across industries
Besides social networking sites, organisations across industries can also use graph analytics to solve a myriad of business challenges.
Advertising, media and entertainment companies, says Lee, can use graph technology to build a 360-degree view of the relationships between customers, their purchase decisions and behavioural insights. This will enable them to better identify product and service recommendations that resonate best with the target audience.
As for healthcare and life sciences organisations, it is crucial for all parties to understand the relationships among patients and doctors, especially as they pertain to their wellness journey.
Using a graph database allows for cost savings due to reduction in inefficiencies, reduced healthcare fraud, improved patient satisfaction and even contact tracing.Joe Lee, vice president for Asia Pacific & Japan, TigerGraph
Other applications for graph analytics include monitoring and preventing cybersecurity incursion, and helping the human resources team understand the current and future skills needed to decide if they should add new headcount, train existing staff, or do both, says Nik Vora, APAC vice president at graph database management system provider Neo4j.
A smarter way of combatting fraud
Graph analytics has been particularly transformative in fraud detection and prevention for the financial services sector.
By being able to map relationships between data points — such as links between people, their mobile phones and bank accounts — financial institutions can uncover behavioural patterns and connections between entities that may well be hidden under millions of documents.Nik Vora, APAC vice president, Neo4j.
This is exemplified in the financial leaks exposed in The Panama Papers and FinCEN (Financial Crimes Enforcement Network) files. “Neo4j’s graph technology is behind the unravelling of the largest financial leaks in history exposed in The Panama Papers, which has recouped more than US$1.2 billion ($1.6 billion) of tax revenue across the world; and the FinCEN files that reportedly show that several global banks moved more than US$2 trillion of allegedly illicit funds over a period of nearly two decades,” Vora claims.
See: Only 20% of organisations in Singapore are analytics experts: Alteryx study
He continues: “Our graph super-scaling technology can process 1.2 trillion relationships under 20 milliseconds in real-time. [To give a sense of how powerful that is,] a graph of one trillion relationships can house a social graph detailing how every person on the planet (7.9 billion people in all) is connected. As such, it would have probably taken decades and hundreds, maybe thousands — instead of the handful of journalists — to break The Panama Papers and FinCEN file cases if Neo4j’s graph technology wasn’t used.”
Given the rise of fraud in Asia Pacific, financial services institutions should consider using graph analytics to stop fraudsters more effectively. Lee gives the example of Merkle Science, a predictive blockchain monitoring and investigative platform provider based in Singapore. By constructing a cryptocurrency network graph using TigerGraph’s graph technology, Merkle Science can analyse over 2.5 TB of data in real-time to better connect relationships that it was not able to do prior. This enables it to help customers better pre-empt and prevent financial crimes.
Making graph analytics work
According to both Lee and Vora, Asia Pacific has been receptive towards graph technology, as suggested by the increasing number of customers in the region for both companies. TigerGraph’s customers include Gojek and the Australian Taxation Office, while Neo4j serves AirAsia, Standard Chartered and StarHub, among others in the region.
What should organisations do to ensure they can reap the full benefits of graph analytics?
“Organisations should have a data strategy that includes graph data platforms and select a [graph technology] partner who can manage past, present and future data on any infrastructure — be it on-premises, cloud, or hybrid,” advises Vora.
For organisations intending to use graph technology for fraud prevention, he suggests partnering a vendor who leverages “a horizontal data platform that integrates data silos to allow interconnectivity of data points”. The partner should also “design processes based on insights from the data, and continue to evolve the data structure, format, and ways of evaluation as the data changes”.
Meanwhile, Lee recommends adopting a graph database platform that is an easy and seamless add-on to their existing data and IT architecture, can scale in real-time as needed, and is quick to derive value. Besides that, it should provide many out-of-the-box integrations with existing data sources or data lakes, and come with built-in enterprise-grade security.
“Graph analytics provides a very data-driven result for businesses to use as a recommendation engine or a next-best action. [As such, the platform used should also enable] new analytics models, such as machine learning and artificial intelligence, to be easily incorporated into data workloads,” he adds.
As data is the “new” business currency, Singapore businesses must leverage analytics if they have not done so, or risk being made redundant. Since traditional analytics tools can help harness insights only to a certain extent, they should consider adopting graph technology to connect the dots, analyse data, and gain deeper and perhaps fresh insights.
By doing so, they can unlock “the true value of data, which is in defining relationships, to uncover insights that drive tangible business solutions”, asserts Lee.