A discussion around graph technology with Giulia Rotondo head of partnerships and alliances at Linkurious.
In our digitised world, it is increasingly challenging to break down data silos and make sense of the ever-growing amounts of data. Analysing complex connected data requires a new approach. For both LARUS and Linkurious, next-generation graph technology is a key part of the solution.
This technology helps companies, public organisations, and non-profit organisations to swiftly and accurately uncover otherwise hidden insights in their data, enabling groundbreaking findings and allowing them to make more informed business decisions, faster.
Linkurious is a software company that provides enterprise-ready graph intelligence solutions that empower data professionals, analysts and investigators to easily find their way in complex connected data and surface key information.
In this interview, we will be speaking with Giulia Rotondo, head of partnerships and alliances at Linkurious, about the importance of reducing complexity in analysing systems, the benefits of graph visualisation and how the partnership between LARUS and Linkurious can help organisations to make sense of their data.
We will also be discussing the latest trends in the graph landscape and how this technology is evolving to meet modern organisations’ needs. Enjoy the read!
Can we start with an explanation of why reducing complexity is so important when it comes to analysing data?
Organizations across industries are dealing with increasing complexity in their data management. They have more data than ever on their hands, which is coming from more sources than ever, and that data may be siloed, stored in a variety of systems and in different formats. Data professionals and analysts are often left with limited access to their data because they lack a solid data governance strategy. Being ill-equipped to harness their data efficiently, they may turn to time consuming manual processing to conduct any in-depth analysis.
The technology organizations are using to manage and analyze their data shouldn’t add complexity; they should make data more manageable, more accessible and easier to analyze. The best technology should help both technical and non-technical users make sense of the complexity within their data, and turn that complexity into actionable insights.
From your experience, what are some of the biggest challenges organisations face when trying to make sense of their data?
Organizations must first de-silo data from legacy systems and centralize it. It requires using data management and data science techniques to ingest, process, store vast amounts of data, all while integrating new approaches like graph technology or AI and machine learning. These processes can be daunting: organisations don’t necessarily have the skills, resources and time to manage their data. Organisations can also be risk averse, adding another layer of difficulty to the task of data management.
Organizations must also implement the appropriate tools and processes to enable analysts to visualize, explore and analyze the data quickly and efficiently, surface key insights that can deliver value for the business.
So, while organisations may be sitting on a gold mine of data, making sense of it is no easy task. It has to be part of a mid- to long-term business strategy, approved by top management and supported by a dedicated and skilled data and analytics functional team, often under the supervision of Chief data & analytics officer (CDAO). But there is a lot of very promising innovation happening in the realm of big data as well as more and more seasoned data professionals that may make these challenges less daunting.
How can graph technology help organisations better understand their data?
First, graph technology is a paradigm shift in the way we approach data. It focuses not only on individual data points, but also on relationships, making it possible to build and analyse entire networks of data, at scale. No other technology offers this kind of approach.
Graph visualisation in particular is a way of presenting data in a way that mirrors the way people think. The human brain processes visual information much faster than written information, so visually displaying connected data ensures faster and more intuitive comprehension. That in turn reduces the time it takes to gain key insights that enable you to make decisions and take action.
Because of the nature of graph data, graph visualisation also makes it simple to see and understand the full context around data points. By visualising all the connections within the data, it’s easy to identify trends, patterns, and correlations.
Finally, visualising graph data makes it intelligible to anyone, not only data scientists. You don’t need to be a technical user or a developer to explore, analyse, gain important insights, and see the bigger picture within a graph. A picture really is worth a thousand words.
LARUS and Linkurious have helped many organisations better understand their data. Can you walk us through a case study that’s particularly striking?
LARUS and Linkurious have had the opportunity to work together to provide Sogei and the Italian Revenue Agency with a new decision support system for the discovery of tax evasion.
In this notable case, LARUS and Linkurious joined forces to address the complex challenge of tax evasion detection, a critical issue for Revenue Agencies. The existing methods for identifying tax evasion often faced hurdles due to the intricate web of relationships between subjects involved in risky or suspicious behavior. This challenge required a new approach that could uncover hidden connections and patterns within the data.
Together, we leveraged the power of graph technology to create a cutting-edge decision intelligence system. This system empowers analysts at the Italian Revenue Agency to overcome the hurdles of tax evasion by providing a visual interface to analyse relationships between various subjects, helping to identify potential risk patterns that might indicate tax evasion.
Through this collaboration, a graph-based approach was adopted to represent the interconnected relationships among individuals, businesses, transactions, and other relevant entities. The system enabled analysts to quickly identify unusual connections, spot anomalies, and recognize patterns that might indicate potential tax evasion activities.
This case study also proves the great impact of graph visualisation in complex data analysis. Our partnership also showcased the potential of combining domain expertise with advanced graph intelligence technology.
What are some of the latest trends in graph technology, and how is Linkurious staying ahead of the curve?
Graph technology is undergoing a process of democratisation, moving from an audience of early, tech savvy adopters to a larger audience of business users who don’t necessarily have a technical background. As a result, graph databases combined with graph visualisation tools are being adopted in more and more organisations, who are using it for a broader range of projects to enable non technical business users to interact with the data and harness it without the need of data science knowledge. Among our own clients, we have Volvo Cars deploying graph for projects ranging from visualising data around the implementation of vehicle functionalities to managing developer workflows, as well as Cisco, using graph visualisation for advanced organisational network analysis.
The trend is to build tools and apps that are both powerful and easy to use, that make it easy for users to gain key business insights on a daily basis. These tools must come with beautiful UI/UX and advanced analytics.
With the adoption of cloud technology more broadly, moving towards SaaS solutions may also be the next thing to accelerate the adoption of graph technology.
What value can graph visualisation add when integrated with other analytical tools and techniques? Let’s analyse the Galileo.XAI case.
Galileo.XAI, LARUS’ cutting-edge platform designed for the analysis of complex datasets, incorporates the power of Linkurious for graph visualisation. This synergy, originating directly from the partnership between LARUS and Linkurious, clearly demonstrates how representing data in the form of graphs can significantly enhance our comprehension of complex information. By visualising data as interconnected nodes and edges, Linkurious integration in Galileo.XAI’s enables users to delve into the complex relationships and interdependencies that might otherwise remain concealed in traditional data representations. This dynamic visual approach amplifies users’ ability to extract meaningful insights from complex datasets, facilitating a deeper understanding of its underlying patterns and structures.
Furthermore, the blending of graph visualisation with Galileo.XAI‘s capabilities has far-reaching implications for decision-making processes. In the realm of predictive analysis, the integration of graph visualisation with predictive modelling takes data-driven insights to the next level. By combining the visual representation of interconnected data with advanced predictive algorithms, the platform becomes capable of uncovering complex trends, patterns, and correlations that might otherwise go unnoticed.
This comprehensive perspective enhances the accuracy of predictive analysis, enabling more precise forecasts and projections. As a result, organisations using Galileo.XAI and its integrated graph visualisation tools are empowered to make more accurate predictions, optimise strategies, and capitalise on emerging opportunities.
What advice would you give to organisations looking to incorporate graph technology into their data analysis strategies?
My advice would be to make the leap and to try it. One of the advantages of graphs is that it is extremely flexible, so you can make it work to your advantage for so many different use cases. Besides, one of the benefits of using a tool like Linkurious Enterprise is that it can integrate with other software, so it’s easy to add to your existing tech stack. Adding graph visualisation to data analysis strategies doesn’t have to require a huge overhaul of your current tools.
Depending on the size of the organisation and its technical resources, it can be a good idea to start small. Because graph technology has so much potential, it can be tempting to integrate it everywhere. But starting with one graph project is a good way to master the technology and fine-tune your use of it, before rolling it out to other projects.
It can also be a big help to have some internal graph champions within an organisation, ideally along with the sponsorship from top management. Because graph technology is relatively new, having a few people on the team to lead graph projects and foster the adoption of graph within an organisation can really contribute to the success of such a project.
Looking ahead, what do you see as the future of graph technology and its role in helping organisations make sense of their data?
Graph technology is still relatively new, so we’re only seeing the tip of the iceberg in terms of its potential. We have clients all across industries – from manufacturing to anti-fraud to cybersecurity – getting an enormous amount of value from graph technology as it helps them streamline processes, manage risks, and more.
Graph technology is of course just one part of larger tech stacks aiming at enhancing business and decision intelligence in the enterprise. Interoperability and flexibility of graph technology will therefore be key in making it a more central part of IT systems alongside the existing proven systems and seamlessly integrating it in current workflows.
The adoption and implementation of graph technology is still too often limited to large organizations. We think that as more organisations start adopting graphs, others will see the value in it. At Linkurious, we’re participating in the process in our own way. From the beginning, part of the company vision has been to democratise the use of graph data through graph visualisation. We’re helping to do that by creating a powerful software that’s also accessible even to non-technical users. In the future, we see graph visualisation becoming a go-to tool used on a daily basis by millions of business users.
The discussion with Giulia Rotondo from Linkurious sheds light on the vital role of graph visualisation in navigating the increasingly complex and interconnected world of data. Linkurious, through its enterprise-ready graph intelligence solutions, empowers both technical and non-technical users to unravel the intricate relationships within data, uncover hidden insights, and facilitate informed decision-making.
In our opinion graph visualisation emerges as a transformative paradigm that not only presents data in a way aligned with human cognition but also accelerates comprehension. By focusing on relationships and visualising data as interconnected nodes and edges, graph technology enables a holistic understanding of complex networks. This approach transcends traditional textual representations and empowers users to identify patterns, trends, and correlations with greater speed and accuracy.
The collaboration between LARUS and Linkurious exemplifies the practical application of graph visualisation. The case study of Sogei showcases how organisations can leverage this technology to extract meaningful insights from intricate datasets, enhancing decision-making processes. Furthermore, the evolving trends in graph visualisation point toward democratisation, with a broader audience embracing its power for diverse projects. As graph technology integrates with predictive analytics and other analytical tools, its potential to enhance accurate forecasting and strategy optimization becomes increasingly evident.
To organisations considering the incorporation of graph visualisation, the advice is to take the leap and explore its flexibility. Starting small and having internal advocates can pave the way for successful integration, allowing organisations to harness graph technology’s full potential.
In a world of burgeoning data complexity, graph visualisation offers a transformative path toward clarity, actionable insights, and data-driven decision-making. As technology continues to evolve, its role in shaping the landscape of data analysis and organisational strategies is set to expand, making the journey toward data enlightenment both exciting and promising.