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Within the demo, I will take the role of a business analyst
who works for a Casino monitoring its slot machine performance.
The casino is a perfect place to utilize Big Data.
With a thousand different things happening on the casino floor simultaneously,
I need to store and analyze my data on Hadoop.
First, let’s connect to my Hadoop data through Hortonworks.
To do so, I will click on the “create a dashboard” button
then proceed to import data from database to build visualizations and get a closer analysis
of the data.
Now I am in the visual canvas where I can build queries
that allows me to drag the data tables that I would like to create
a cube out of with no manual SQL coding needed – a plus for business analysts
who often don’t have backgrounds in computer science or coding.
Although MicroStrategy automatically links attribute elements,
I can also manually join them through easy drag and drop.
Here I’ll be adding some necessary data columns for my report.
I can also do things to enrich my data.
MicroStrategy allows several ways to transform data without coding through out of the box
expressions and metrics.
I can also build a filter of the data to only bring back certain types of slot machines
or only the poorly performing ones.
Here I’ll be making a filter of only the active slot machines.
I can also supplement the casino data to create new attributes without pulling in additional
columns of data.
After building my queries on the visual canvas,
I can even take a look at the actual SQL code that is created
if I want to manually write my own queries.
Now I’m going to save this data into a cube and continue through my dashboard creation
process.
I’ll be creating a series of visualizations in order to take a detailed view of the slot
machine data.
I’ll be creating a series of 3 different graphs in this Casino Dashboard.
My hope is that I would be able to analyze the pattern of the data and gain business
insights.
This first graph is a daily analysis for selected slot machines.
One great feature of MicroStrategy is creating metrics on the fly.
This metric I’m creating with a custom formula will tell me the average amounts of coins
in the slot machines per day.
By putting it into the graph, I can get a better look at the trajectory
while I compare to the jackpot amounts to make sure our returns are consistent.
The slot hold by slot machine type visualization shows what the highest revenue generating
type of slot machines are
by the number of coins that each machine type is bringing in.
The Key Performance Indicator Review looks at the jackpot amount and slot hold amount
of individual slot machines.
They are colored by the coin hold % which means the darker circles are the higher revenue
generating machines.
I would want the darker circles to have higher slot holds
because I want the higher revenue generating machines to be bringing in the most profit
while giving out the least amount of jackpots.
Now that I’ve created our visualizations, I can set filtering to slice and discover
and analyze.
Look at the different data sets I can explore as I drag my mouse
over the areas of the graph I want to take a closer look at.
Look at the two visualizations right below being filtered by my selection.
Now let’s take a look at another dashboard
to visualize the data in the form of a Heat map and grid display that I have already created.
I will break down the analysis by individual slot machine makes
and furthest down by model and even further down by machine type.
I will color by the hold % to figure out the types of slot machines that are the most popular.
Look at the grid visualization on the side to get a detailed breakdown and numbers of
the slot machines.
It can be a great reference point to dig deeper into the data.
If I want to filter and figure out which slot machines aren’t doing well,
I can take look as I click on individual heatmap boxes or radio buttons that I want to take
a closer look at.
I can also drag the bottom filter along to bring back different slot machines.
MicroStrategy offers the flexibility, self-sufficiency, and visual sophistication
needed to gain powerful business insights from Big Data analytics.