The finance industry is deeply affected by many global events such as the pandemic, convergence of industries, and rapid technological evolution driving digitization. The profitability of these businesses depends a lot on eliminating risks and closely following and interpreting various market trends. Data analytics helps financial institutions turn massive amounts of unstructured customer and transaction data into valuable insights. These insights help businesses understand many key business aspects.

A bank’s success depends a lot on its risk management abilities. Whether loans or investments, data analytics helps banks better analyze their credit risks through risk modeling. These models help banks implement fraud detection and management measures and assess operational and liquidity risks in-depth to safeguard their businesses.

On the performance side, banks can become hyper-productive by assessing their KPIs through various visual metrics to understand which aspect needs more attention. In-depth sales and revenue performance analysis help make better and informed decisions to drive growth through data analytics.

Retail industry is becoming a leading AI adopter specially to enhance their customer experience and optimize adverting campaigns. Retailers have always been laser-focused on putting the right products in the hands of the right consumers. Predictive data analytics are now being used to not only offer to buy recommendations (such as the next best offer on a shopping site) but also to hyper-personalize the entire customer experience online.

Analytics is also used to optimize pricing. Data Science can identify a sudden drop in sales of a particular item and offer more incentivizing pricing to boost sales back up.

It is imperative for online businesses to collect, process, and analyze customer data to personalize their customers’ shopping experiences. By customizing the experience, vendors can make recommendations and increase the likelihood of further sales.

Aerospace and Defense (A&D) OEMs are under constant pressure to innovate, adapt, and overcome industry challenges. The need to reduce component size, weight, cost, and time-to-market without compromising safety and security is a significant challenge. These critical requirements, combined with the increased demand for digital transformation and expanding customer expectations, have placed immense pressure on suppliers to optimize business operations and processes.

Nuon takes pride in partnering with the world’s leading A&D companies to deliver value-driven and outcome-based digital solutions. Nuon provides innovative solutions to overcome complex problems, and allow our customers to sustain a competitive advantage.

Nuon’s team of engineers work with data to help stakeholders understand what affects manufacturing and operations. Identifying things like equipment downtime, inventory levels, and maintenance costs help companies streamline inventory management, and risks, to create maximum efficiency.

Accelerating cost savings, improving performance and developing localized products are critical areas of focus OEMs must address. With the new era of industrialization, OEMs and operators are betting on digital solutions that are agile, effective, and customized to meet dynamic market demands.

Nuon’s experience in Data Science, AI and expertise in digital technologies provides us with a unique edge-comprehensive knowledge of how machinery works in connected environments. We help heavy equipment, industrial, and automotive customers embrace digitalization and maximize value across the product life cycle, from concept initiation to aftermarket services along with value added analytics, IoT, smart embedded systems.

Businesses utilize analytics to optimize their supply chains by analyzing data related to inventory levels, supplier performance, transportation logistics, and demand forecasting. By identifying inefficiencies and bottlenecks in the supply chain, companies can reduce costs, improve product availability, and enhance overall operational efficiency.

The future of supply chain management is set to be transformed by the growing use of data science and analytics. The potential applications of data science in the supply chain are vast, and businesses that embrace this technology will likely gain a competitive advantage over their peers. As companies continue to invest in data science and analytics capabilities, we can expect significant advancements in supply chain management in the coming years.

Data has now become central to the energy sector to reduce its reliance on fossil fuels and promote sustainability. Data analytics is used to identify ways to improve efficiency and make the industry more sustainable. Data based solutions help reduce costs, optimize decision-making and improve overall monitoring.

Data analysis and computational models can determine the highs and lows of power usage, as well as when there is a surplus, by collecting data on usage and combining it with other sensory information. Data science is seen as a key enabler to help decarbonize global energy use.