add reference

book/04_data_and_types.md

@@ -62,7 +62,7 @@ A deeper exploration into data reveals various scales on which it can be measure
 
 #### Big Data
 
-Working in data science there is really no way to avoid dealing with the challenges, the promises, or even the (many) definitions of **Big Data**. Since this is not our core concern in this book, I will simply stick to the very simple definition of saying 
+Working in data science there is really no way to avoid dealing with the challenges, the promises, or even the (many) definitions of **Big Data**. Since this is not our core concern in this book, I will simply stick to the very simple definition, roughly following {cite}`russom2011big`, and say:
 
 > **Big Data** ≈ Data that is too large, too complex, or too volatile to be evaluated using manual and traditional data processing methods.
 

book/references.bib

@@ -352,6 +352,16 @@ @book{popper_2013
 	keywords = {Kritik, Wissen, Wissenschaftstheorie},
 }
 
+@article{russom2011big,
+  title={Big data analytics},
+  author={Russom, Philip and others},
+  journal={TDWI best practices report, fourth quarter},
+  volume={19},
+  number={4},
+  pages={1--34},
+  year={2011}
+}
+
 @article{weihs_2018,
 	title = {Data {Science}: the impact of statistics},
 	volume = {6},