this case is that of hospital pharmacy with stock of few thousand medicines the government came out with new norm to all pharmaciesall medicines should be checked for their sensitivity to light and be stored in newspecial containers one thing the government didn' supply to the pharmacies was an actual list of light-sensitive medicines this is no problem for you as data scientist because every medicine has patient information leaflet that contains this information you distill the information with the clever use of text mining and assign "light sensitiveor "not light sensitivetag to each medicine this information is then uploaded to the central database in additionthe pharmacy needs to know how many containers would be necessary for this they give you access to the pharmacy stock data when you draw sample with only the variables you requirethe data set looks like figure when opened in excel figure pharmacy medicines data set opened in excelthe first lines of stock data are enhanced with lightsensitivity variable as you can seethe information is time-series data for an entire year of stock movementso every medicine thus has entries in the data set although the case study is an existing one and the medicines in the data set are realthe values of the other variables presented here were randomly generatedas the original data is classified alsothe data set is limited to medicinesa little more than , lines of data even though people do create reports using crossfilter js ( javascript mapreduce libraryand dc js ( javascript dashboarding librarywith more than million lines of datafor the example' sake you'll use fraction of this amount alsoit' not recommended to load your entire database into the user' browserthe browser will freeze while loadingand if it' too much datathe browser will even crash normally data is precalculated on the server and parts of it are requested usingfor examplea rest service to turn this data into an actual dashboard you have many options and you can find short overview of the tools later in this among all the optionsfor this book we decided to go with dc jswhich is crossbreed between the javascript mapreduce library crossfilter and the data visualization library js crossfilter was developed by square registera company that handles payment transactionsit' comparable to paypal but its focus is on mobile square