With the title of “Sexiest job of 21st century”, it is expected that the job of a Data Scientist is making amazing work on making predictions and telling great stories. Unfortunately, ask any Data Scientist and they will tell you that they spend large part of their job cleaning data and doing many repetitive tasks. Therefore, the majority of data and analytics software vendors have pooled their research into one big question: How can the process of refining and analysing data be simplified? The answer is through the automation of a number of tasks, such as data integration and model building. With these tasks no longer needing to be manually carried out, the productivity of Data Scientists will be increased, with a greater use of data and analytics, and making Data Science products simpler to use. As Alexander Linden, research vice president at Gartner said, "The key to simplicity is the automation of tasks that are repetitive, manual intensive and don't require deep data science expertise".
This approach is automating repetitive task is important as we see continuous rise of citizen Data scientists. As mentioned in this article, a citizen Data Scientist is “a person who creates or generates models that use advanced diagnostic analytics or predictive and prescriptive capabilities, but whose primary job function is outside the field of statistics and analytics.” These citizen Data Scientists will also benefit greatly from the automation of certain Data Science tasks, and it is predicted that citizen Data Scientists are the key to bridging the gap between mainstream self-service analytics used by business users and the Data Scientist’s advanced analytical techniques.
If you’d like to learn more about ways to become a citizen Data Scientist, check out datascientists.net (Todo: change call to action).