I feel like articles written by the referenced author are extremely bias and have no real value to add to the discussion. The guy is basically arguing over semantics like it really matters to anyone. I say tomato, you say tomato...
There are a number of different approaches to building a report that aims to answer one or more questions of the data as well hopefully either gives someone an idea of what's going on or something to actually act on. Data is ingested, data is stored, data retrieved, data is computated, data is visualized, and data is analyzed.
Regardless of you accomplished any of those steps is irrelevant to what BI is or isn't. You can do this with SQL Server, T-SQL, and Excel or you can do this with HDFS, Hive, R, and Tableau. Who the hell cares what you call it as long as someone is using the data.
Stop freaking saying Data Science is not reporting or does not have reports. Almost every data science output I've ever worked with that is actionable goes into a freaking report with or without the help of traditional "BI" techniques (e.g.: entirely in R using a flat file that's still automated and repeatable).