Leveraging the Transformative Power of Data Architecture in 2024

In summary, in 2024, companies would have to navigate a landscape where data is continuing to increase in value as a strategic asset

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Data monetisation

Data architecture

Businesses worldwide are embracing digital transformation in response to changing times, resulting in a surge of data. The growing variety of data sources, sets, and formats is putting a strain on older systems struggling to connect different applications. Moreover, businesses are dealing with additional challenges, such as scaling, rising costs, and operational stress due to caching systems built on top of operational data platforms. To address these challenges, businesses are turning to advanced data management solutions that can handle increasing volumes and types of data. These solutions leverage technologies such as cloud computing, big data analytics, and artificial intelligence to enable seamless integration and analysis of diverse data sources. The growing reliance on digital technologies in 2024 and beyond, would require robust and reliable data architectures. 


As technology evolves, it has become imperative to have a solid data architecture that serves as the backbone for innovation, analytics, and digital transformation efforts. Yet many of today’s IT infrastructures struggle to effectively manage current digital resources and are ill prepared for future ones. Frequently, these structures face fragmentation due to differences in technologies and architectures, proprietary systems, organizational silos, and geographical distances.

The solution lies in real-time data management platforms that not only accelerate IT modernization but also bring enterprise data strategies to reality. With its consistently high performance and availability, robust security, and reduced server footprint, real-time data management can support the most demanding, data-intensive workloads. According to 'The Speed to Business Value', a study by KX and the Centre for Economics and Business Research (CEBR), 80% of companies surveyed report revenue uplift due to real-time data analytics. In this article, we will discuss how real-time data analytics is supporting data infrastructure developments and the key technologies that organizations need to focus on.

  1. Real-time Graph and Vectors: Industries are witnessing a shift towards real-time identity graphs and vectors, especially in areas like fraud detection and recommendation engines. Organizations are increasingly adopting graph data models to power business-critical applications. While a scalable, high-performance graph database makes it easier to build and run applications, an advanced vector database makes it easier to store and query data with many attributes. With these databases seamlessly operating at scale, applications can deliver blazing-fast insights, empowering businesses to make smarter decisions in real time.

For instance, in the financial sector, real-time identity graphs play a crucial role in detecting and preventing fraudulent activities and ensuring secure transactions. In e-commerce, recommendation engines powered by real-time data enhance customer shopping experience, offering personalized product suggestions based on user behavior. 

  1. Real-time Data Empowering Super Apps: Super apps that offer a variety of services within a single platform are becoming prominent. Post COVID-19, numerous stand-out super apps have emerged in Southeast Asia. These apps have evolved from payment apps into all-in-one services that allow users to manage everything, from housekeeping to insurance. And creating seamless real-time experiences is a crucial part of these modern app developments.

Thus, real-time data access is vital for super apps to deliver customized and relevant services, such as personalized content, recommendations, and transactional information. It facilitates the development of super apps by enabling storage and synchronization of data across devices in real time. This functionality is particularly valuable for scenarios where multiple users require access to and simultaneous updates of data — for instance chat applications, collaborative tools, and multiplayer games.

  1. Optimizing Infrastructure and Cost: In today’s digital landscape, success rates of modern tech products depend on efficient collection and use of big data, and more importantly, on the database infrastructure to store, process, and analyze it. Thus, including database infrastructure costs in their unit economy is becoming increasingly critical for all businesses. Many companies frequently underestimate the cost of these operations. Therefore, companies across industries are increasingly focusing on optimizing data architectures to manage costs efficiently. This is particularly crucial in sectors with high data volumes, such as telecommunications and finance. For them, having a dependable real-time infrastructure layer is essential, as the infrastructure is the underlying foundation for the capabilities required to deliver real-time experiences.  

Optimizing the infrastructure involves streamlining data storage and ensuring quick and cost-effective access to information. This is done by redesigning the cloud architecture, real-time data infrastructure, and data pipelines. It's a strategic move to prevent unnecessary expenditures, enhance operational efficiency, and meet environmental goals by reducing carbon footprint associated with excessive infrastructure.

  1. DBaaS (Database as a Service): DBaaS is a cloud computing managed service that provides various database services without the overhead of typical database management. It offers a cost-effective way for database users to build scalable applications with a fraction of the servers and operational overhead required with traditional data solutions, leading to increased popularity of DBaaS in the industry. When merged with real-time data, the capabilities of DBaaS is enhanced, as it provides immediate data access, improves performance, and supports responsive analytics. Particularly in industries like IT and finance, where data management is intricate, real-time DBaaS provides a solution for organizations to focus on their core competencies while ensuring their data platforms are efficiently handled. The real-time nature of these databases aligns well with business’ dynamic and agile requirements. 

In summary, in 2024, companies would have to navigate a landscape where data is continuing to increase in value as a strategic asset. Changes are occurring in the technology infrastructure landscape, driven by shifts in business requirements that impact data requirements, edge environments, and connectivity. 

These changes are driven by the rising demand for real-time data analysis and the need for businesses to quickly adapt to changing market conditions. As a result, industries are investing heavily in data management systems and technologies that can handle large volumes of data and provide fast and reliable connectivity. Additionally, the rise of edge computing enables industries to process data closer to its source, reducing latency and improving overall performance. As industries adapt to digital transformation, persistent investment in robust data infrastructure underscores its indispensable role in shaping a competitive, agile, and resilient business environment in 2024. 

The article has been written by Aveekshith Bushan, VP, APAC region, Aerospike

DQ Online