But those days are gone – we are now experiencing a democratisation in data analytics.
Research by Gartner has found that more than 40% of data science tasks will be automated by 2020, by what it terms “citizen data scientists” (those whose job function is outside the field of statistics and analysis).
Gartner predicts that citizen data scientists will surpass data scientists in the amount of advanced analysis produced by 2019, resulting in increased productivity and business performance due to the broader usage of data and analytics.
“By using technology to automate complex analytics, retailers are able to expand the number of data sources to generate actionable insight”
This growth in citizen data scientists is being driven by evolving technology that is automating the hard work of data analysis.
By using technology to automate complex analytics, retailers are able to expand the number of data sources they use to generate actionable insight, without increasing their headcount or technical knowledge and expertise.
This will help them stay ahead of the competition and, in turn, allows data scientists to shift their focus on to more complex analytics.
New data collaboration technology is intuitively designed to make comparing and analysing datasets quick and easy.
The AI-powered technology removes the need for datasets to be manually changed so they are in the same format.
“Different formats are automatically recognised and transformed so they match and can be analysed together”
For example, different companies may store customer age differently – one as date of birth and one as an age range.
Different formats are automatically recognised and transformed so they match and can be analysed together.
This enables a simple and fast process for the generation of insights.
It’s time for retailers to seize the initiative as the field of data analytics and integration becomes democratised by new technology, source the best datasets for their business and act quickly on the collaborative insight they deliver.