For this week’s exercise we will look at customer purchase behavior to decide if we should offer a “Meal Deal” that would add a side and drink to a purchase of pizza or a burger.
This week’s Objective:
In order to decide if we should start including a new “Meal Deal” on our menu we want to study the potential impact on recent transactions. Please identify the number and percentage of orders since July 1, 2013 which include the following categories of food: Pizza OR Burger along with a Side and Drink.
This is a part 1 of many blog posts coming up on Alteryx workflows, weekly challenges and walk-through – as I learn it. Beginning with a brief overview of Alteryx and it’s use cases, I will conclude with a workflow walk-through.
After spending enough time on data visualization tools and mediums like Tableau, RShiny, Dash and PowerBI I found an ardent need to explore ways through which I could connect only relevant data to my visualization media. Through my internship I came to terms with the fact that data can be voluminous and way more messier than you can imagine.
With data lakes storing large volume of data dumps the process of value creation from this resource begins with creation of defined pipelines to analyze that data – a process some call the Extract Transform Load (ETL) process.
I could go out on a limb and call myself an Alteryx fanboy – I have reasons though.