NAIROBI, KENYA: In the next five years, 59 percent of organisations will increase the number of positions requiring data analysis skills.
This is according to Data Analysis Skills report, sponsored by the American Statistical Association.
That is not all, according to IBM, annual demand for the fast-growing new roles of data scientist, data developers, and data engineers will reach nearly 700,000 openings by 2020.
What IBM predicts thus is that demand for data scientists will soar 28 per cent by 2020 according to The Quant Crunch: How The Demand For Data Science Skills Is Disrupting The Job Market.
With nearly half of the occupations becoming computerised within the next ten years, one in three jobs will evolve into software, robots, and smart machines.
This new era of data technology will bring with it the need for very specific types of workers, one of them being skilled data analysts.
Data analysis skills are defined as the ability to gather, analyse and draw practical conclusions from data, as well as communicate data findings to others.
The most lucrative analytics skills include MapReduce, Apache Pig, Machine Learning, Apache Hive and Apache Hadoop.
Some examples of jobs that require data analysis skills are statistician, market research analyst, supply chain & operations, financial analyst and research manager.
The other most common functional areas for data analysis positions are accounting (71 per cent), human resources (54) and business administration (50 per cent).
Usually, these are full-time positions at mid-level management (79 per cent) and individual contributor (73 per cent) levels.
However, 60 per cent of organisations require senior management or executives to have data analysis skills.
Seventy two per cent of marketers consider data analysis skills vital to surviving in today’s data-centric marketing landscape.
The marketing industry supports this sentiment, with a report from BlueVenn revealing the biggest “marketing skills gap” to be data analytics.
This report has now placed data analysis as the most important skill a person could learn within the next two years.
The advent of the big data era means data analytics has become integrated into almost every application, software and platform.
As businesses start to realise the power of information to inform their business decisions, customer behaviours and purchases, and the way they manage business productivity, they will make data a more integral part of their operations – whether that be marketing, systems and technology, sales, engineering, healthcare, or product development.
However, data is useless to a company without someone who has the skills to analyse it.
This gives human resources personnel the pressure to look for top talent who have strong data literacy skills, in other words – are competent in sourcing, manipulating, managing, and interpreting data – including numbers, text and images.
Even if you’re currently in a senior position, 60 per cent of organisations want senior leadership to have data analysis skills.
Characteristics of data analytics is not just being good with numbers, you have also got to be a problem solver, out-of-the-box thinker and a strong communicator.
In Kenya for instance, the career is gaining much momentum if the online search results of data analyst job opportunities available is anything to go by.
According to Nicholas Cheruyoit, a data analyst and research consultant and graduate of BSc Applied Statistics with Information Technology from Maseno University, technology has in the recent past rapidly evolved with several trends and emerging issues in the business world.
"To remain relevant, businesses are forced to carry out serious research to improve their operations. These requires on a large extend the input of a data analyst to inject in such skills as analytical skills to deal with data analysis, communication skills to help in presenting the findings in understandable form, critical thinking for data interpretation and drawing of relevant inference and strong mathematical skills to estimate numerical data," says Cheruyoit,
According to him, anyone who is planning to be a data analyst needs to pursue fields in mathematical science, statistics and computer science.
Together with these, Cheruiyot says one will need to move a further step of studying statistical packages such as SPSS, STATA, R, SAS among many others for the purposes of analysing the data as in most cases may not be as much explored.
"These degree courses are quite competitive in nature with mathematics and language as major requirements and are offered mainly in top universities in the world but as one in Kenya are University of Nairobi (UoN), Kenyatta University(KU), Maseno, Moi, Jomo Kenyatta University of Agriculture and Technology(JKUAT), Daystar Strathmore among others,” he says.
He says that the course still remain a very ripe field for grab as it is very marketable careerwise and technical in nature thus many people still don't want to “stress” themselves with mathematical stuff leaving the field unexploited as much.
"I'll personally encourage those with passion for Maths to join us in this field,” concludes Cheruiyot, who adds that the entry point salary ranges from Sh120,000 to Sh180,000 per month and increases with experience and output of the employee.