The Growing Demand for Data Roles: Overcoming the Challenges
In today's digital age, big data has become a prominent topic of discussion. Back in 2012, Paul Zikopoulos stated that a staggering 2.5 quintillion bytes of data were generated every day. Since then, the data explosion has transformed the business landscape, with data being captured from various touchpoints such as social media interactions, TV preferences, commuting routes, and even doorstep visitors.
The influx of data has led to significant changes in the business world, including improved efficiencies, enhanced data analysis capabilities, cost reduction, and faster data automation. However, this surge in demand for data-driven insights has created a pressing need for skilled professionals in the field.
The data explosion has brought about significant changes in the business world, leading to -
Improved Efficiencies and Efficacy:
Organisations strive to extract valuable insights from their data to enhance operational efficiency and effectiveness.
Enhanced Data Accessibility:
Advancements in data capture, storage, and accessibility have made it easier than ever before to analyse rich data sets.
The data explosion has brought about significant changes in the business world, leading to -
Improved Efficiencies and Efficacy:
Organisations strive to extract valuable insights from their data to enhance operational efficiency and effectiveness.
Enhanced Data Accessibility:
Advancements in data capture, storage, and accessibility have made it easier than ever before to analyse rich data sets.
Accessibility for Smaller Businesses:
Reduced costs and the availability of new software have democratized data analysis, enabling even smaller businesses to leverage their data assets without investing in extensive data infrastructure.
Data Automation:
Automation has minimised latency and ensured the availability of relevant data when needed, further enabling data-driven decision-making.
Reduced costs and the availability of new software have democratized data analysis, enabling even smaller businesses to leverage their data assets without investing in extensive data infrastructure.
Data Automation:
Automation has minimised latency and ensured the availability of relevant data when needed, further enabling data-driven decision-making.
The Growing Need for Data Roles:
According to a government report on quantifying the UK data skills gap in 2021, businesses were estimated to be recruiting for 215,000-234,000 roles requiring hard data skills, with data analysts being the most sought-after. However, it was found that less than half of these positions were successfully filled, indicating a growing shortage of qualified candidates. At Realise, we have over 25 years of experience in the Customer Analytics space, meaning we understand the challenge of finding individuals who possess a combination of data proficiency, IT literacy, and strong communication skills. This predicament is often referred to as the "Data Science Unicorn" challenge. While the talent was once available with the right incentives and development programs, a shift has occurred in recent years. Despite the steady number of Mathematical Science graduates, fewer of them are pursuing careers as Customer Analysts or Data Analysts.
The Appeal of Data Science:
The Harvard Business Review famously dubbed the "Data Scientist" as the sexiest job of the 21st century, which may explain the dwindling interest in the less glamorous Customer Analysis roles among fresh graduates. For businesses, this poses a significant challenge. Although there is a desire for data democratization, building capabilities to meet this demand has proven difficult, particularly for companies unable to offer competitive salaries or situated in less desirable locations.
Navigating the Challenge:
One potential solution for businesses is to empower their employees with data-driven tools and software. Many analytical, operational, and management information systems now incorporate embedded analytics and modelling features, enabling less data-savvy users to access the same level of data support without relying on a dedicated Data Team. While this approach holds promise and is likely to evolve with advancements like ChatGPT, the current lack of data literacy poses a hindrance. As a result, businesses often resort to "recruiting at any cost," prioritising quantity over quality in their hiring practices. While this may yield short-term success, it often leads to frustration and subpar outcomes in the long run, tarnishing the reputation of analytics as a whole.
Finding the Solution:
To address this challenge, a dual approach is necessary. Firstly, there must be an increased emphasis on attracting a larger pool of high-quality candidates to recognise the rewarding opportunities within the data sector. Additionally, investment in educational programs and initiatives should be made to encourage more graduates to pursue careers in data analytics. Without an ample supply of skilled and passionate professionals, businesses will inevitably become frustrated, and the sector as a whole may face jeopardy.
Conclusion:
The exponential growth of big data has brought about substantial changes in the business world. However, the demand for skilled data professionals has outpaced the supply of qualified candidates. To bridge this gap, businesses must focus on attracting and nurturing data talent while investing in educational programs that cultivate data literacy among graduates. Only by addressing this challenge can businesses harness the full potential of their data assets and secure a prosperous future in the ever-evolving landscape of data analytics.
According to a government report on quantifying the UK data skills gap in 2021, businesses were estimated to be recruiting for 215,000-234,000 roles requiring hard data skills, with data analysts being the most sought-after. However, it was found that less than half of these positions were successfully filled, indicating a growing shortage of qualified candidates. At Realise, we have over 25 years of experience in the Customer Analytics space, meaning we understand the challenge of finding individuals who possess a combination of data proficiency, IT literacy, and strong communication skills. This predicament is often referred to as the "Data Science Unicorn" challenge. While the talent was once available with the right incentives and development programs, a shift has occurred in recent years. Despite the steady number of Mathematical Science graduates, fewer of them are pursuing careers as Customer Analysts or Data Analysts.
The Appeal of Data Science:
The Harvard Business Review famously dubbed the "Data Scientist" as the sexiest job of the 21st century, which may explain the dwindling interest in the less glamorous Customer Analysis roles among fresh graduates. For businesses, this poses a significant challenge. Although there is a desire for data democratization, building capabilities to meet this demand has proven difficult, particularly for companies unable to offer competitive salaries or situated in less desirable locations.
Navigating the Challenge:
One potential solution for businesses is to empower their employees with data-driven tools and software. Many analytical, operational, and management information systems now incorporate embedded analytics and modelling features, enabling less data-savvy users to access the same level of data support without relying on a dedicated Data Team. While this approach holds promise and is likely to evolve with advancements like ChatGPT, the current lack of data literacy poses a hindrance. As a result, businesses often resort to "recruiting at any cost," prioritising quantity over quality in their hiring practices. While this may yield short-term success, it often leads to frustration and subpar outcomes in the long run, tarnishing the reputation of analytics as a whole.
Finding the Solution:
To address this challenge, a dual approach is necessary. Firstly, there must be an increased emphasis on attracting a larger pool of high-quality candidates to recognise the rewarding opportunities within the data sector. Additionally, investment in educational programs and initiatives should be made to encourage more graduates to pursue careers in data analytics. Without an ample supply of skilled and passionate professionals, businesses will inevitably become frustrated, and the sector as a whole may face jeopardy.
Conclusion:
The exponential growth of big data has brought about substantial changes in the business world. However, the demand for skilled data professionals has outpaced the supply of qualified candidates. To bridge this gap, businesses must focus on attracting and nurturing data talent while investing in educational programs that cultivate data literacy among graduates. Only by addressing this challenge can businesses harness the full potential of their data assets and secure a prosperous future in the ever-evolving landscape of data analytics.