According to the forecasts of the World Economic Forum, by 2020 data analysts will be in high demand in companies around the world. This is further confirmed by IBM, which claims that the annual demand for data scientists, data developers and data engineers will lead to 700,000 new recruitments by 2020.
According to an analysis conducted on a sample of 550 small and medium-sized businesses, 50% of SMEs state that they intend to hire a data analyst in the next three years. And the earnings are not to be sneezed at. The average yearly salary of a data analyst is among the very highest, with figures ranging from £35,000 to £55,000. Moreover, in a field that has reached almost complete equality with men, many data analysts are women (41% against 59%).
The reason for all this is quite simple. If you think of our use of smartphones, emails, loyalty cards, public transport subscriptions, social networking, and searches on Google, the amount of data we generate is increasing year after year. This enormous amount of information needs to be managed and analysed. That’s why data analysts, or data scientists, have become so sought after. Indeed, the economist Hal Varian Ronald has defined this role as “the sexiest job of the 21st century”.
But don’t think of it as the exclusive domain of IT giants or digital start-ups. According to a Modis survey involving 347 business profiles, 97.44% of respondents – from mechanical companies through to banks – perceive the analysis of big data as an opportunity, in particular – and this comes as no surprise – as regards sales, marketing and interpretation of data. Moreover, there is a greater interest in the interpretation of data than its analysis. However, 42% of respondents complain of a lack of qualified profiles in the labour market, while almost 55% are aware of their existence but consider these profiles hard to find.
But what do data analysts do?
First of all, they try to understand the origin of data and any possible distortions, through the use of technology. Then, they collect and analyse the data, identifying correlations and interpretative patterns in order to draw useful information relating to certain fields. Nowadays, Big Data applies to everything from transport management to mass market retailing, from workforce performance (workforce analytics) to healthcare, from banking to insurance.
What skills are required to gather and interpret such a wealth of information?
Data analysts have analytical skills and a natural propensity for mathematics, statistics and computer programming. However, they should also have good communication skills, as they must present their findings in a visually clear and universally understandable manner. This profession attracts people from a variety of educational backgrounds: not only economics, mathematics, statistics or information technology, therefore, but also the humanities. Most entry-level data analyst jobs require at least a bachelor’s degree. To become a data analyst, you’ll want to earn a degree in a subject such as Mathematics, Statistics, Economics, Marketing, Finance, Computer Science or Information Management.
Is coding / programming required for data analytics?
You need to have the knowledge of programming languages like Python, Perl, C/C++, SQL, and Java—with Python being the most common coding language required in data science roles.
How can you become a Certified Data Analyst?
A bachelor’s degree in a related field, such as Statistics, Information Technology or Computer Science, can gain data analyst experience and to advance your career you can consider a master’s degree or certificate program.
Would you like to know which certification is high in demand or which data analytics certifications will pay off ?
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