Click through for a closer look at the day-to-day activities of a data scientist, as identified by Trifacta.
In early 2012, a group of Stanford University researchers interviewed 35 data analysts from 25 organizations across a variety of sectors, including health care, retail, marketing and finance, and identified the various challenges data scientists face in the data analysis process.
Despite being in high demand and hailed as one of the hottest professions of the 21st century, much of the work of a data scientist is actually dominated by the incredibly time-consuming process of changing data into a usable form. The data analysis process involves four tasks - discovery, transformation, modeling and reporting – with data scientists spending as much as 60 to 80 percent of their time in the data transformation stage.
In this slideshow, Trifacta, a provider of productivity platforms for data analysis, takes you through each of these tasks in greater detail, highlighting the pain points data scientists face at each stage. It’s clear tools are needed that can simplify the data analysis process while at the same time increasing productivity and collaboration among data scientists.
An eWEEK Property
Copyright 2020 TechnologyAdvice All Rights Reserved.
Advertiser Disclosure: Some of the products that appear on this site are from companies from which TechnologyAdvice receives compensation. This compensation may impact how and where products appear on this site including, for example, the order in which they appear. TechnologyAdvice does not include all companies or all types of products available in the marketplace.