Original subtitles

Presenter: All right, get excited

because it's time to finally introduce our course project.

So here's the situation.

You've just been hired

as a business intelligence analyst by AdventureWorks,

a fictional global manufacturing company

that produces cycling equipment and accessories.

And your role is to help the management team

track their KPIs, things like sales, revenue,

profit and returns, compare performance across regions,

analyze product-level trends,

and identify high-value customers.

But all you've been given

is a folder of raw CSV files,

which contain information about transaction

and return records, products,

customers, and sales territories.

So your objective here

is to use Power BI desktop

to connect and transform that raw data,

build a relational data model,

create calculated columns and measures with DAX,

and finally, design an interactive dashboard

to help visualize and analyze that data.

So let's take a peek

at what we're gonna be building

and what the final product will look like.

All right, so here's a quick preview

of the AdventureWorks report

that we're gonna build together.

Right now we're looking at

the executive summary view.

You can see we've got those high level KPIs

that the leadership team cares about,

revenue, profit, orders, and return rate.

We've got a nice

weekly revenue trending chart here as well.

And you'll see some really cool interactive elements

that Power BI offers

like sliders to zoom in on specific time periods,

custom tool tips that we'll build together,

and even a completely custom filter pane as well.

Now, one thing you'll see here

is that we can drill into any specific product

to take us to our product detail view.

That's gonna show us things like

how a product is performing against

its monthly order, revenue, or profit target.

We're gonna practice using things

like parameters for what if analysis.

In this case, how does it change to the price,

impact a metric like total profit.

We'll explore field parameters

to make these charts more interactive

and dynamic for our end users.

We'll drill into Power BI's mapping

and geospatial tools like so,

and we'll build a customer-level view

to drill into performance

at the individual customer level

and break down different customer profiles and segments.

So again, we're gonna build

this entire report completely from scratch

with nothing but a folder of raw CSV files.

It's gonna be a lot of fun

so I hope you're excited to dig in.