This future may be closer than many think. The prevalence of remote and hybrid working introduced by the pandemic has accelerated the adoption of cloud computing technologies. Companies had to redeploy their employees in 2020 and 2021, and their infrastructure also had to shift to fit the new reality. “If you look back at the history of cloud, I think you'll see that pandemics accelerated the adoption of this technology by several years,” Amazon's Jassy said at the end of 2020.
maintain control
Improper data management poses significant business risks. And increasingly, that danger comes from within corporate walls. Staff can put your organization at risk by leaking or disclosing sensitive data to the public, whether intentionally or accidentally. In the first quarter of 2021 alone, 57 per cent of cybersecurity incidents reported to the UK data protection regulator were caused by insiders.
To protect your business information, it's important to effectively control data flows and who has access to your data. Refinitiv's real-time data access control system allows businesses to manage who has access to what data, create an auditable record of who can publish specific types of data, and gain overall control over their data. You can manage it. The system can also identify users who have access to certain types of data, but are not actually using the data. This reduces the risk of data leakage, whether intentional or not.
Leverage your data
Burak Tutar has a clear idea of what his future holds. “Our five-year vision is for us to have a fully automated data and execution system, maintained by data engineers, with traders only involved in the co-development of strategies,” along with quantitative analysts. says Tutar, founder of AI commodity trading company Vitus Commodities.
Central to this future vision is the use of artificial intelligence and machine learning. Tutar said the company, which focuses on energy markets, uses AI to build predictive models that can predict wind direction over the medium term. It relies on accurate weather forecasts (which are notoriously difficult to get right), but also manages the data, utilizes cloud computing, and runs machine learning systems on top of it. It also depends on the ability to deploy.
If successful, it could lead to more accurate and cheaper pricing.
Forecasting, automated enterprise decision-making, and ultimately automated energy networks. Tutar said commodity trading firms and Wall Street banks are making “some effort” to add fundamental data (real-time information about the world, such as oil supply levels provided by satellite imagery and sensors) to trading settings. However, he added that these were “inadequate”. “The main reason for this is simply organizational memory and a ‘this is how we do business’ approach,” he says.
To reach a stage where cloud, big data, and AI can be successfully leveraged, organizations need to have the platforms and staff with the necessary skills to do so. Data ingestion or ingestion is important for this. Refinitiv says its Refinitiv Data Management Solution (RDMS) can provide standardized data that enterprises can bring into their business through the cloud through simple API integration. You can push all your data to a data warehousing system or create one from scratch.