Data specialists add value to virtually every department within an organization. In sales, they can analyse past and current sales to predict future demand, determine pockets of heavy demand and areas with high potential to target customers well. In the marketing department, they can analyse social media trends, effectiveness of campaigns and optimize return on investment for different marketing media used. In the operations department, they can help make supply chain decisions, help in procurement and determine best routes for raw material and finished goods. In the finance department, they can do time series analyses to forecast revenue, expenditure and budget required.
There is a massive amount of information being generated every day. According to one research, 4 exabytes of new information was generated in 2008 – more than the previous 5000 years combined! This exponential growth of data has led to a massive surge in data specialist jobs. People are needed to clean this raw data, analyse it and make it usable. Even the most sophisticated data analyses tools present today, which use artificial intelligence and neural networks can’t make sense of this vast raw data, hence the high demand for data specialists is very likely to prevail for decades to come.
As years pass and more and more data is generated, jobs in all fields of analytics will be abundant. To handle the complexity, numerous firms will open and specialize in different stages of the process – some to fetch the data, some to clean it, some to use the sophisticated tools to get trends, and some top level consultancies to make sense of these trends and provide actionable insights while others to develop the necessary tools; thus creating lots of jobs. Like the 60s with the marketing departments; the 2010s will be when the data departments become the focal point of companies, making data specialist the most coveted job.
Analytics is a mathematics intensive field – it’s all about the numbers. People with a background in mathematics, statistics, engineering or finance will find it easier to perform well in analytics jobs than those without a degree in them. Computer and programming skills are essential in data specialist jobs to fetch and compile data from various sources.
Importantly, a logical approach to solving problems and a knack for seeing trends in large amounts of information with a lot of noise is needed to excel in this field.