Innovation in Asia is booming and fast-paced. New technology trends are constantly changing the way organisations interact with internal and external audiences, as well as impact how businesses compete against each other. Analysing and acting on big data enables businesses to under stand the value of their data and realise the importance of analytics in providing a competitive edge, drive new business opportunities, leverage current and upcoming customer needs, and optimise internal operations. How ever, while most companies are aware of the need to have a data strategy, many are still struggling to find the right platform to support their big data requirements, or hardly realise how to actually use this data.
As the volumes and typesof data are increasing, keeping up with the pace of this growth is critical to having a successful and meaningful big data and analytics strategy. Data sources, such as web applications, social media, sensors, and machine logs, coupled with new applications emerging from the Internet of Things (IoT), are driving this complexity further. The impact of IoT is already taking place in a wide range of industries- from retail and financial services to telcos and healthc are - and the growth of connected devices is contributing to the complexity of data to manage.
Another issue to consider is that the diverse data sources mentioned above are also often geographically distributed. Organizations are sending their data to the closest data centre for low latency, which can create a delay if any enterprise applications or analytics are applied to the data. Additionally, although data is generated continuously from these new sources, current data management approaches are usually set to processdata a predetermined frequency. By implementing a platform that will store, update, analyse and act on data in real time, organisations will become capable of harnessing the full power of big data. Finally, many organizations may try to extend an existing system by deploying data transport systems and data processing systems in separate clusters.
Recognizing these concerns, organizations have begun to rely on Converged data Platfrom which I anticipate will revolutionise the big data industry. A converged data platform will become a key trigger for big data decision makers and data analytics users in the following ways, such as:
- Reduces architectural complexities by unifying files, database tables, and data streams. A converged data plat form brings together batch and streaming analytics in place by eliminating data movement.
- Enables continuous real-time data processing to avoid delayed processing and insights.A converged data platform helps organisations in any industry continuously collect, analyse and act on data-in-motion and data-at-rest.
- Handles data diversity and geographic dispersion. With a converged data platform, data created at multiple geographical locations can be processed in real time and organizations canreceive a complete,continuous state-of-the-business picture and improve responsiveness to critical events.
With the growing amount and complexity of big data that organisations will have to work with in the future, having a converged data platform will pave the path for achieving better results. If your organisation wants to remain competitive in an increasingly fast-paced technology environment, continually optimising your internal processes by leveraging a converged data platform model should be a key part of your data strategy.