In your own words, how does analytics in a business context differ from pure data science?

In any organization there are two very important workflows (or pipelines), the Data Science pipeline and Business Decision making pipeline.

1) Data Science Pipeline - This is about converting data into insights (predictions, patterns, etc.) on specific business parameters / drivers. This pipeline includes data management, data engineering, modeling etc.

2) Business Decision making Pipeline - This is about utilizing different business parameters / drivers to create models (like Financial Models, Media Mix models in case of marketing optimization, Supply chain process models etc.) that help us to take a business decision (Ex:Setting a product price, Run a particular campaign, Invest in a particular distribution channel etc.)

Data Analyst is more proficient in data science pipeline while business analyst is more focused on the second workflow mentioned above. So the business analyst tends to have a good understanding of business context, domain knowledge, functional orientation etc. Having said that, the real opportunity is to combine the two pipelines seamlessly so that the insights on business parameters are automatically fed into model equations that helps to take a business decision.