In 2024, the widespread adoption of data-driven technologies, or datafication, has significantly transformed the landscape of connected devices, particularly in how we handle the vast amounts of data they produce. Datafication has accelerated the proliferation of connected devices, integrating them into our daily lives in ways previously unimaginable. These devices, imbued with sensors and IoT capabilities, now generate colossal volumes of real-time data.
Ashher Zafar, Chief Technology Officer, PlanckDOT, says, “All aspects of our lives, business and society are today being turned into quantifiable and usable data. The fact is the datafication of everything is a reality we must live with today. Datafication helps us derive insights, make informed decisions, optimise, and automate processes, and create new devices and software products. It is forecasted that by the end of 2024, globally 147 zettabytes of data would be created and consumed.”
He further adds that the widespread adoption of data-driven technologies has transformed the landscape by enabling enhanced connectivity, real-time analytics, and personalised user experiences. The outcome is an advanced ecosystem comprising intelligent and responsive devices. The integration of AI and ML technologies makes it possible to analyse large data sets, to make the analysis more accurate and in-depth, and then generate predictions. AI also can be used for augmented analytics, automating repetitive tasks like data preparation, providing advanced analysis capabilities, and simplifying the overall analytics workflow. Various analytics and business intelligence tools help to extract actionable insights from data.
Raveen Beemsingh, CTO, Leadzen.ai points out several key areas where this transformation is evident:
– Enhanced data processing and analysis: Previously, the challenge with connected devices was the overwhelming volume of real-time data they generated. To manage this, compromises were made in computation and data comprehension, focusing only on the most relevant data. However, with the advent of advanced data-driven technologies, it has become easier to process and make sense of this extensive data efficiently. This capability has enabled more comprehensive utilisation of data, leading to richer insights and better decision-making.
– Increased intelligence and autonomy: The integration of artificial intelligence (AI) into connected devices has become more prevalent, leading to smarter and more autonomous systems. These devices are now capable of making informed decisions and learning from data, enhancing their functionality and user experience. This AI integration, often referred to as AIoT (Artificial Intelligence of Things), has led to the development of devices that are not only connected but also intelligent.
– Expansion of IoT devices: The Internet of Things (IoT) has expanded exponentially, with over 207 billion devices connected globally by the end of 2024. This includes a wide range of devices, from everyday consumer items to industrial machinery. The IoT ecosystem has grown to encompass a diverse array of devices, each generating data that can be used to improve efficiency, functionality, and user experience.
– Healthcare revolution: In the healthcare sector, IoT devices have become instrumental in remote monitoring and diagnostics. The integration of generative AI with these devices has enabled the transformation of patient data into actionable insights, significantly advancing healthcare delivery and patient care.
– Edge computing: The adoption of edge computing, where data processing occurs closer to the data source rather than in a centralised cloud-based system, has gained momentum. This shift is particularly crucial in scenarios that require real-time processing and low-latency responses, such as in autonomous vehicles and industrial automation.
Enhanced consumer experience: In the consumer space, the proliferation of smart, connected devices has led to more personalised and responsive user experiences. From smart homes to wearable technology, devices are increasingly tailored to individual preferences and needs, driven by the data they collect and analyse.
– Retail and industrial applications: In retail, IoT technologies have been widely adopted for inventory management, customer experience enhancement, and operational efficiency. Similarly, in industrial settings, connected devices play a crucial role in optimising manufacturing processes, predictive maintenance, and supply chain management.
The evolving nature of cyber threats, increasing volume and complexity of data demands constant adaptation of security measures. Addressing this challenge requires a holistic and adaptive approach, safeguarding user data from potential breaches and implementing robust consent management mechanisms is a critical step.
“As a Chief Product and Technology Officer, navigating the potential of datafication reveals several significant challenges for companies, along with opportunities for growth,” says Karan Rai, Chief Product and Technology Officer, Ennoventure Inc. “One major obstacle is the effective management of extensive data. Companies often struggle with organising, storing, and processing this data efficiently. However, this challenge presents an opportunity to invest in robust data infrastructure, leveraging cloud solutions and advanced data management tools,” he adds.
Rai further mentions that another challenge lies in data quality and reliability. Inaccurate or incomplete data can lead to flawed insights and decisions. He says, “Nevertheless, this challenge opens doors for companies to invest in data cleansing tools, implement stringent quality control measures, and adopt AI-driven techniques to enhance data accuracy. We view this challenge as an opportunity to develop data governance frameworks that prioritise data integrity, thereby strengthening the reliability of insights derived.”
“Another pivotal challenge is the presence of data integration issues and siloes. Overcoming these obstacles and establishing a unified data landscape is essential for deriving meaningful insights,” says Srikanth Doranadula, Group Vice President, Cloud Technology, Oracle India. “Skill gap and shortage of talent is another challenge in the realm of data analysis and utilisation. To address this, companies must invest in comprehensive training programs and upskilling initiatives for their workforce. This proactive approach ensures that the workforce is equipped to handle the complexities associated with data utilisation,” he adds.
Transforming these challenges into opportunities yields several strategic advantages. Mastery of data security and privacy can serve as a potent differentiator, attracting both customers and partners. The application of data-driven insights contributes to operational efficiency by optimising processes, reducing costs, and enhancing decision-making capabilities. Also, leveraging data for innovation facilitates the creation of new product and service offerings, paving the way for entirely novel revenue streams.
“In 2024 and beyond we would be moving towards a more evolved dynamics of interaction between humans and technology in a more interactive, intuitive and natural manner using more of voice and gesture controls,” predicts Zafar. This shift has huge and not totally perceivable implications for businesses. The future would see interfaces with user-friendly experiences which would be created using AI perfectly designed to understand and anticipate user needs and aimed at multifold enhancement in customer satisfaction.
“However, the increased connectivity will also create a need for robust cybersecurity measures. As the number of connected devices grows, the potential attack for cyber threats increases,” shares Doranadula.
Businesses are needed to adapt their strategies to harness the benefits of evolving human-technology interaction. Embracing innovation, staying agile in adapting to technological advancements, and ensuring a user-centric approach will be crucial for businesses to thrive in this interconnected landscape.
With the increasing prevalence of datafication in 2024, Rai suggests several ethical considerations that are crucial for businesses to address to ensure responsible and secure utilisation of data in the connected devices ecosystem:
– User privacy protection: Obtain informed consent, transparently communicate data collection practices, and provide users with control over their data, including clear policies on storage, sharing, and retention
– Data security measures: Implement robust encryption techniques, enforce strict access controls, and regularly update security protocols to prevent breaches and unauthorised access, ensuring data integrity and confidentiality
– Fairness and bias mitigation: Vigilantly avoid perpetuating biases in algorithms or data sets that could result in discriminatory outcomes. Regular audits and diverse data sourcing can help mitigate biases and ensure fairness in data usage
– Cultural emphasis on ethical data practices: Foster an organisational culture that prioritises ethical decision-making regarding data. Offer comprehensive training on data ethics and compliance to employees at all levels, encouraging a commitment to ethical data handling
– Viewing ethics as essential, not optional: Encourage businesses to perceive ethical considerations not merely as compliance but as a commitment to building trust with users. This approach ensures sustainable and responsible data utilisation within the connected devices ecosystem
By addressing these considerations, businesses can unlock the benefits of datafication while upholding user trust and contributing to a healthy connected devices ecosystem.
In Zafar’s words, “We must use technology but must not succumb to it. Technology is here to change mankind in ways never before.”
