With the world’s data increasing exponentially every year, the ability to extract actionable insights from data is becoming increasingly more important. As traditional data analytics grow outdated, the data science field has skyrocketed in popularity in recent years due to the more powerful insights data scientists can provide by cleaning and preparing data and identifying more granular patterns or trends through machine learning. However, data scientists remain in limited supply today, and many companies struggle to hire the high price point of a typical data scientist’s salary.
If not all companies have the luxury of affording a highly technical team of data scientists, how might we enable less technical data analysts to elicit valuable insights from their data with machine learning?