58% of IT and Tech businesses have two or more data scientists, but many don’t get the actions they need
Many businesses in the IT and Tech industry are unable to develop the insights they need from big data despite the majority employing at least two data scientists, revealed a new study of multiple industries.
Research shows that although 58% of businesses in the IT and Tech sector have two or more data analysts, 16% feel they’re unable to develop insights from this big data collection.
The study, completed by business app discovery marketplace, GetApp, in April 2019, surveyed 488 business leaders from a range of industries working in businesses with 500 or fewer employees.
Proving that quantity doesn’t correlate with quality when it comes to data, respondents from the IT/Tech sector were most likely to say they have the right data but were also the most likely to admit that they aren’t drawing the right insights from this data.
These results prompted GetApp to put together a guide to help businesses get more effective results from their big data. Despite the survey finding a positive link between business intelligence (BI) software and confident decision-making, this is only to be considered the first step in a process that also examines qualitative factors, such as what motivates people to make certain choices.
Lauren Maffeo, Associate Principal Analyst at GetApp, commented on the research, “There’s no doubting the importance of data scientists in modern business. Having the ability to sort through and analyze large mines of data can be of benefit to any company, however, it’s important that businesses don’t try to substitute qualitative research for big data.
“The IT and Tech sector is a great example of where data analysis can be improved to get better results. The study shows that, despite IT and Tech businesses being most likely to have data scientists, they are finding great difficulty drawing the right insights.
“Along with our research, we’ve put together some points to help businesses get the most from their data analysis. This includes working outside the normal boundaries of your team and eradicating the silos that prevent cross-functional working, as well as conducting effective qualitative research to support big data.”