UBM data scientist: A background in data analytics, not data management, is key to being a data scientist

Jody Porrazzo warns that the data management route 'isn't the ideal way' to a career in data science

Having a background in data analytics rather than data management is preferable for anyone aspiring to a career in data science, according to Jody Porrazzo, a data scientist at multinational media company UBM.

Porrazzo, who was speaking to Computing at the SAS Global Forum in Las Vegas last week, said she "wasn't sure about the new programmes that have come into play", making reference to the large number of university courses that have sprung up in recent years as companies cry out for more data scientists.

She said that she came from an analytics background, and then learnt about data management and quality as she had to get the data in the right shape to analyse. "That meant understanding that your confidence limits are going to be impacted if there are high variants in the data," said Porrazzo.

She insisted that someone in IT wouldn't talk about data in the same way. "He or she is going to build the system and get the data through the pipes, but is not going to talk about the variants in the data. They will talk about error, but they're not going to understand why the error affects the analytics," she said.

Porrazzo said that people could take a data management route to becoming a data scientist. "You can come in from a data management perspective with a good idea of how data should flow through the enterprise and then study the analytics and statistics, but I don't think that's the ideal way," she said.

"The ideal way for a data scientist to prepare is to have a great background in statistics, predictive models and business analytics and then to understand how to build out a data programme and understand the importance of data management techniques [later]," she added.