Published on July 17th, 2019 | by Bibhuranjan0
8 Reasons Why Jobs in IT and Data are in Demand
A 2017 report from Glassdoor showing the 50 best jobs listed a data scientist as the first best job in Australia. This is the second time this position had clinched the first position. The results only echo the growing demand for professionals who have pursued IT-related courses like data analytics, BI engineering and database administrator, to mention a few. Glassdoor ranks the best jobs based on three factors, and these include the number of job openings, annual salary and job satisfaction. The job score for all these factors surpassed other job openings hence, the first position. This surge is not going to taper off given the increasing number of organisations looking for analytics professionals. The text highlights reasons for the growth in IT and data jobs.
Shortage of Talent
Companies are looking for professionals who understand numbers and can communicate the results effectively. While there are computer science programs on offer, it will take time to meet the exponential supply. Besides, big data and analytics courses have only been introduced in mainstream education recently. Due to the scarce talent pool of people who can combine these two skills, experts predict that the salaries for data scientists will grow by 6%.
Demand is not restricted to Tech Giants
A while ago, the services of a data scientist were only demanded by big tech firms like Facebook and Google. This trend has changed over time as smaller organisations realise the value of making informed decisions both for the business, and their customers. For example, Roofstock has developed a rental property calculator that provides their customers with easy and insightful data.
Companies that make data-informed decisions are 5% more productive than their counterparts. It explains the growing need for small companies to look for professionals who can sift through data and provide useful insight into the business to create a competitive edge.
Problems in Data Organisation
Companies are looking for professionals who organise large chunks of data and prepare it for analysis. Cybersecurity is also an important aspect for many businesses. It involves long, tedious processes of translating system codes. Data scientists are well-equipped in handling such tasks, saving organisations the high cost that comes with inaccurate information.
High Salary Aspects
The high demand for data analytics skills has pushed the wages for qualified professionals. A salary survey conducted in 2015 by the Institute of Analytics Professionals of Australia found that the median salary of a data analyst is $130,000. The growing demand for this professionals and scarce talent pool will only push the figures higher with experts anticipating a year-on-year median salary increase of +13.63%.
The emergence of Unstructured and Semi-structured Data Analytics
Many organisations process and analyse unstructured sources of data, including social media, weblogs, videos and photos. This may create errors when making decisions, which translate into losses.
Few Restrictions for Existing Professionals
Data science is a relatively new field thus, able to allow entry from different professionals. Many data scientists have pursued computer science, mathematics, statistics and engineering disciplines. The premise is to foster analytical and problem-solving skills.
The Trendiest Job of the 21st Century
The Havard Business Review branded this profession as the coolest in the 21st century. The responsibilities of these professionals are unique compared to regular jobs, and the nature of work enables them to utilise multiple analytics skills. Also, the vast range of opportunities provides data scientists with an irreplaceable repute.
Availability of a Range of Roles
From a career perspective, students pursuing data science and IT can pursue a range of options in terms of domain and the nature of the job. They include big data analytics, big data engineer, analytics associate, and business intelligence consultant. What’s more, a big data analytics professional can specialise in any of the three analytics profession, depending on his environment- predictive analytics, prescriptive analytics and descriptive analytics.