I routinely see comparisons between #datascience vs #data analysis roles and I'd like to share some possibly unpopular opinions.

1: Data scientists and data analysts are equally valuable to an organization.

Sometimes data analysts are even more valuable if the company is not at the data science phase yet (and they're often not).

2: Data scientists can be more impactful if they are open to doing both data science and analysis.

Ie building a churn model? Why not make a dashboard to display basic churn statistics, then build your model, and display its impact on another dashboard?

3. I wish data science education programs would also explain that corporations desperately need "jack of all trade" data folks.

More focus on solving business problems with data using whichever technique is most appropriate. Less focus on trying new algorithms.

I finish this all saying I love the #data community. Y'all are so great and teach me new things every day.

I just want to find a bit more balance in the expectations given to new data professionals in the industry.