In the race towards more advanced technologies, the capabilities that were once indistinguishable from magic are now becoming a reality. But what good is all this speed and information if we can’t extract insight from it?
Enterprises are now turning to graph databases to help make sense of their data, and Neo4j has emerged as one of the major players in this space.
Frontier Enterprise recently interviewed Alyson Welch, Chief Revenue Officer of Neo4j, to talk about the importance of graph databases in this era of big data, how to overcome challenges in implementing graph technology, and the trends that will drive the growth of graph technology, among others.
With your extensive experience in the technology industry, how do you see the role of technology evolving in driving revenue growth for enterprises? What are the key technological trends that companies should be paying attention to, especially in ASEAN?
I expect to see the role of technology in driving revenue growth for enterprises continue to evolve and become even more critical in the years to come. Businesses that embrace these changes and invest in the right technologies will be better positioned to achieve long-term success.
Examples of such technology include the adoption of graph technology, cloud-based solutions, as well as AI and ML to help streamline operations, increase overall efficiency, create personalisation, and improve customer experience. These will help businesses develop a point of difference from their competitors.
As the business landscape becomes increasingly complex and data growth explodes, leading governments and enterprises across the globe and in ASEAN, such as DBS Bank and Standard Chartered Bank in Singapore, are rapidly adopting connected data strategies and leveraging graph technology.
We expect graph adoption and innovation to accelerate across ASEAN, with the region leading many of graph technology’s most innovative use cases in future based on three trends.
- The first is ASEAN’s role as part of the fastest-growing region for AI in the world, fuelling an aggressive transformation of its digital economies into data economies. Graph is foundational to AI/ML, with every leading platform now incorporating graph at its core.
- Secondly, the anticipated publication of ISO’s first standard for Graph Query Language — an initiative supported by several key contributors — means the graph market is standardising, which is positive news for all users.
- Lastly, the continued explosion and complexity within and across data connections will only increase in a dynamic geopolitical and economic environment.
ASEAN is at the forefront of all these trends, especially as it is one of the most dynamic and innovative regions globally, and home to one of the world’s most diverse populations.
In the highly competitive enterprise technology space, how can companies differentiate themselves from their competitors and provide unique value to their customers? What role does emerging technology play in this process?
Companies need to leverage what they do better than anyone else to provide real value to their customers. They need to execute as impactfully and efficiently as possible to set themselves apart from the competition. Companies that differentiate themselves by offering a clear, explicit, and unique value proposition, as well as meeting and exceeding their customers’ needs, are more likely to succeed in the highly competitive enterprise tech space.
To develop the skills needed to fulfil business demands, a program called Graphs4APAC Initiative was recently launched in Indonesia (Graphs4ID) with BRIN and KORIKA, and in Singapore (Graphs4SG) with Temasek Polytechnic. The program aims to equip current and future professionals with the latest mission-critical graph technology tools, courses and certifications, books and online resources, as well as software to practise what they learn
By fostering collaboration between industry and academia, this initiative will promote the growth of data science and create a steady supply of graph data platform experts for the future.
The COVID-19 pandemic has accelerated the adoption of digital technologies across all industries. How can enterprises leverage these technologies to drive revenue growth and improve their overall business operations in the post-pandemic era?
The most innovative companies leverage economic turmoil to their advantage, focusing on what differentiates them in delivering growth to drive success.
Enterprises need to be agile and learn how to scale and transform in periods of growth and uncertainty, such as the 2008 global financial crisis, the dot-com bust, and the COVID-19 pandemic. They also need to know how to optimise and adapt for the long term.
We saw tech companies in ASEAN step up to this challenge by demonstrating their nimbleness in working through difficult situations while remaining more globally minded than companies in other regions, which has served them well during these tumultuous periods.
The most successful companies ensure their systems are built to manage and automate complexity by design, versus reactively, particularly by navigating the complexity of connections within data. Downturns also favour the prepared.
Today’s digital environment has made it increasingly complex, painstaking, slow, and expensive to navigate and understand the relationships across billions of data connections, especially in challenging economic conditions. We can expect this to only increase. It is exactly this complexity that graph technology is uniquely positioned to solve these issues.
How can companies stay ahead of the curve and adopt emerging technologies, such as AI and ML, to optimise revenue and compete in a crowded market? What specific strategies have you found to be most effective in implementing these technologies?
Staying current with emerging technologies and trends is crucial for companies to remain competitive and relevant in today’s ever-evolving digital landscape. Identifying and adopting new technologies that make business sense can give companies a significant advantage in innovation, efficiency, and cost-effectiveness.
New technologies and processes that are beneficial to the business also deliver significant opportunities for growth and enhance customer experiences. Ignoring or being unaware of these levers can lead to significant risks, such as losing market share, missing out on new revenue streams, and falling behind competitors. Take the example of Kodak. A failure to recognise that online photo sharing would largely replace, instead of merely complement, its print business led to its eventual demise.
Strategies such as conducting market research and analysis, attending industry conferences and events to learn about emerging technologies and trends, gaining insights from industry experts, monitoring influential news outlets, and leveraging tech forecasting tools are all crucial in deciding whether to implement certain technologies.
As CRO for Neo4j, I find that I learn the most from listening to our customers, understanding their market, their pain points and how we can help, and by working together are the best ways we can all stay ahead of the curve.
Graph technology has the potential to transform the way enterprises manage and analyse their data. What challenges should ASEAN companies be prepared to face when implementing graph technology, and what strategies have you found to be most effective in overcoming these challenges?
The nature of data has transformed significantly over the years. Today, enterprises have many more data connections and metadata, which are much more complex to deal with.
While it’s a pain point for the enterprise, it presents a huge opportunity for graph technology companies as businesses seek greater value from leveraging the connections and context in data at scale. Connected data is everywhere, and graph databases are vital to understanding these connections.
While graph technology offers significant benefits, companies should be prepared to address technical skills, integration, cost, and adoption challenges to successfully implement and leverage the technology.
The way to overcome these issues is to partner with a graph technology provider who understands your business challenges and works in tandem to overcome them. It’s important to find a partner who looks beyond the relationship as a mere transaction.
With your extensive experience in enterprise technology and revenue growth, what trends do you predict will drive growth in the graph technology space in the coming years? What are some key areas of growth and innovation that companies should be paying attention to, and how can they position themselves for success in this evolving landscape?
As data connections continue to increase and become more complex, companies are leveraging graph technology to help solve their most pressing business challenges, or as a way to innovate. From generative AI, fraud detection, identity and access management, risk and compliance, customer analytics to supply chain, graph databases have a unique ability to find hidden relationships and patterns across billions of data connections.
Research firm Gartner predicts that graph technologies will be used in 80% of data and analytics innovations by 2025, up from 10% in 2021, to facilitate rapid decision-making across enterprises.
Many contemporary data challenges can be solved with graphs at data engineering, data science, and user levels. While graph databases were previously utilised in a small number of critical systems, including the manufacturing and transportation of medicines during the pandemic, we’ll see their usage increase in the coming years and become more widespread across a wide variety of sectors.
Furthermore, as AI becomes more mainstream, enterprises will continue looking for the best ways to take advantage of knowledge graphs for ethical AI. Organisations can strengthen their accuracy for responsible decision-making and enhance explainability by leveraging the context that graphs provide.
With cost efficiencies at the top of mind for many enterprises, we anticipate open-source adoption to increase as developers and data scientists seek more cost-effective solutions to solve existing and new data and analytics problems.
And lastly, digital twins will continue to increase in popularity thanks to its broad functional versatility. A digital twin is a virtual representation of a physical object, process, service, or environment that behaves and looks like its counterpart in the real world. It sends and receives data and feedback in real time using simulation, ML, and reasoning to help businesses with their decision-making. Whether it’s the construction, supply chain, or cybersecurity sectors, digital twins offer analytical capabilities, enabling organisations to gain complete visibility into their inventory, networks, vulnerabilities and more.