Getting Future Ready with Big Data Analysis

By Professor Khalid Hussain, Dean of Faculty of Engineering and Information Sciences – University of Wollongong in Dubai

What’s the Big Data Craze?

Big data today is more than just a buzz word that seems to have captured everyone’s imagination – no matter where in the world they are based or what industry they are employed in. Industry influencers, academicians, and prominent stakeholders all agree that big data has become a game-changer in almost every modern sector over the past few years.

Big data describes the large amount of structured and unstructured data that is difficult to process using traditional databases. To gain a better understanding of how big data is impacting our everyday lives, consider the current COVID-19 pandemic. The almost real-time COVID-19 trackers are continuously aggregating data from sources around the world to help healthcare workers, scientists and policymakers find solutions globally. Big data is being used to save lives in the face of disasters, as well as to anticipate economic trends and predict consumer habits.

Big Data, Artificial Intelligence and Machine Learning

According to the ‘Big Data Market’ research report published by MarketsandMarkets, the global volume of big data is expected to grow in value from US$138.9 billion in 2020 to US$229.4 billion by 2025. The proliferation of big data has convinced entities to adopt solutions that help data engineers to simplify and manage their decision-making processes and fine-tune their strategies. Well-managed, trusted data leads to credible analytics and informed decisions. It is important for businesses to seize the full value of big data and base their decisions on its projections as opposed to merely relying on their instinct.

Artificial Intelligence (AI) is an area of expertise that many businesses value in this day and age. Most people are unaware that big data provides a solid foundation for companies that want to commence AI projects. AI builds on techniques and processes similar to those employed by organisations that leverage big data. Therefore, companies keen to integrate AI and Machine Learning (ML) into their operations would do well to establish a robust big data environment first.

ML is an AI application that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. ML forms a crucial part of the big data landscape, and together with AI, is set to become one of the most in-demand skillsets in the tech industry.

Data analysis, AI and machine learning enable a greater understanding of both the business and the industry, ensuring that companies make the right choices to help them grow. In order for organisations to remain competitive and stay informed in these ever-changing times, it is crucial that they implement these three components across their operations – these technologies are set to bring the magic of cutting-edge business applications to life. Furthermore, data-driven organisations are more consistent, profitable and generally perform better than their non-data driven counterparts. At the end of the day, data-driven decisions that leverage AI and ML, will always outperform intuition-based decisions.

Addressing the Skills Gap

Currently, there is a digital skills gap affecting multiple industries. What this means is the demand for experienced big data, AI and ML professions is higher than ever. Also, this deficit is occurring on a global scale and is not restricted to a particular country or industry. With careers that integrate these niche knowledge domains considered among the most sought after roles today, qualified professionals can choose from a plethora of opportunities available across multiple sectors such as banking, government, defence, healthcare, life sciences, information technology, media, transportation and logistics, to name a few.

Many universities in the UAE are increasing their offerings to address the skills gap in related sectors. Pursuing big data, AI and ML as academic disciplines can be a fun and rewarding investment. These sectors offer puzzles to decipher that require analytical and problem-solving skills that are not only relevant for careers related to big data, but also remain useful and practical for everyday tasks. In addition, studying big data, AI and ML opens multiple doors for graduates across a wide range of careers including big data miners and analysts, data engineers, data scientists, machine learning engineers and statisticians, among so many other evolving ones.

Finally, the opportunities that big data, AI and ML bring are capable of shaping the next big idea that could transform the way we live and work. No matter how much technology advances, businesses are always going to require professionals with analytical skills to improve their efficiencies and functionalities.

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