Modern Data Science and Evolution of BI
Modern big data discovery tools enable all employees to access the data, streamlining the data prep process, and allowing data scientists to spend more time on advanced analytics. The infographics in this post show the evolution of the data scientist from data drudgery to modern data science for all.
However, there are still many companies stuck in the dark ages of data drudgery. Within these companies, data scientists are removed from main workflow of the organization, typically siloed to the back of the office where they spend more than half of their time preparing and cleaning data with traditional BI tools. It takes months versus minutes to turn gigabytes of structured data, which is buried within relational databases, into visualizations their companies can pull value from. Traditional BI technologies slow the process of data analysis down, creating the need to hire more analysts and increasing the risk of relying on stale data.
The dawn of modern data science tools paired with cultural shifts happening within organizations has accelerated the role of a data scientist to become today’s “hottest” job. They are bringing richer findings and data insights at a faster pace; a major competitive advantage in a world of quickly evolving data trends.
- Private: Forrester Research: Benchmark Your BI Environment for Continuous Improvement
- Should Data Science Really Do That?
- The Internet of People: 4 key principles for analyzing personal data