Big data and IoT are entwined. How? Every device around us is connected to the cloud, sharing every minute bit of our data. Smart farming, e-health, smart retail, smart home, smart cities, smart environment are few applications of IoT in today’s world. A lot of data is generated from these applications that industries gather with the aim to improve their business workflows, enhance customer experience, and stay relevant in the ever-increasing competition. This means that IoT directly impacts data, making it swell in size, and companies should leverage new-age technologies to draw accurate insights from the data to make informed business decisions.
IoT combines the ability to gather and analyze data, communicate with connected devices, and trigger actions based on the analysis performed. The technology is mainly used to automate parts of businesses that require constant analysis and prompt responses. However, a business should realize the value of the wealth of data that is generated by the IoT network to perform its autonomous functions. Businesses can use IoT analytics as an upgrade to their existing big data initiatives.
It is crucial that data scientists and analysts take into account the existing biases and formulate remedial solutions for these. As hidden biases in big data are an impediment to accurate decision-making and can affect outcomes, it is paramount that business leaders and lead management members remain alert.
Behind every technological innovation that hits the market, there is a team of highly skilled professionals working jointly to make the innovation a success. And it is obvious that when technologies come in, employees are expected to update their knowledge and skills to be able to leverage the technology. From bridging the talent gap to incubating the right culture to modifying the infrastructure, every small thing should be taken into account when companies plan to harness the power of any new technology.
Fintech firms are increasingly escalating the pace of revolution with the help of cutting-edge technologies. They are now looking to combine two incredible technologies to become a differentiator in the competitive market. Robotic process automation (RPA) and AI have become a disruptive force in the fintech sector. Augmenting AI to a rule-based robotic process automation system gives rise to another tool that not only automates tasks but also possesses decision-making capabilities. All of this will in turn increase accuracy, boost productivity, and increase a company’s bottom line.
Data-driven marketing has been an effective marketing approach for several businesses. Organizations need to address customer concerns and generate a trustworthy and transparent approach towards data collection. Data has become so essential for businesses that startups are generating synthetic data to eliminate the cold start problem. Hence, numerous organizations in every industry sector are adopting a data-driven marketing approach to offer better products and services and ensure customer satisfaction. But, are there any negative implications of implementing data-driven marketing?
Despite rigorous research and aggressive adoption, IoT infrastructure faces major security issues. Hence, several researchers and developers are exploring enhanced security protocols provided by blockchain. Blockchain has already introduced a secure platform for cryptocurrency transactions. Similarly, the utilization of blockchain in IoT will lead to the development of distributed ledger for interfacing multiple connected IoT devices. With such an approach, data storage and networking of IoT-powered devices will be drastically improved.
Every organization has realized that data is an asset and utilizes crucial data in multiple applications. In data monetization, blockchain can be a major contributor due to its advanced applications and decentralized nature. With the help of blockchain, data monetization will be accessible to consumers soon. Using blockchain-based data monetization, consumers can monetize and negotiate the value of their data. Also, consumers can control which data can be collected by organizations to ensure data security and privacy.
The utilization of RPA in healthcare services can centralize and streamline different workflows. Shifting these routine tasks from human agents to bots can result in cost savings for healthcare providers. Also, automating crucial workflows will improve efficiency across the board. With this approach, healthcare professionals can spend the majority of their time on patient care and other critical activities. A major drawback of leveraging RPA in healthcare is that RPA can only process structured data and work with a rule-based approach. However, the advent of intelligent process automation (IPA) will make RPA smarter.
Though immersive technologies are still in their infancy, they have come a very long way already. This gives credence to the fact that AR and VR in the finance industry will have incandescent adolescence. Looking at the current advances, AR and VR seem to be the undeniable future game changers for the financial sectors. With its immersive experiences, AR and VR in the finance industry will allow various institutions to offer the ultimate customer experience, thus enabling them to thrive amidst cutthroat competition.