Instructor: Now throughout this entire
dynamic array section, we're going to be working
on a project.
Here's the situation.
You've just been hired
as a business intelligence analyst for Maven Recruiters.
It's a job placement agency based in the United States.
Here's the brief.
Your first task as a BI analyst
is to analyze a public dataset
from Glassdoor, which tracks things
like average salary and growth rate
across a range of cities, industries, and job titles.
And your goal is to use these new dynamic array formulas
in Excel to explore the job landscape
to compare salaries and salary expectations
and identify high-growth opportunities for the agency.
So here are the objectives.
You're going to identify top industries
by salary and growth rate.
You'll review popular jobs by industry.
You'll create tools to explore random samples of job titles.
You'll visualize the overall salary distribution.
And finally, compare average salaries across top US cities.
So a little sneak peek into the Glassdoor dataset itself.
What we have here is one file,
one table that can contains five different fields,
the "industry", which is the name.
of the industry or job category
For each job title, there are 17 industries represented.
We'll have a "job title" field,
which is obviously the name of the job itself.
There are 84 titles represented in the dataset.
We've got a "city" column, the name
of the US cities where the job titles can be found.
This table contains data for 10 different cities.
And then in terms of numerical metrics,
we've got the average salary in 2020
for each of these job titles in each city.
And finally, a year over year percentage growth field
which is the percent change
in average salary from 2019 to 2020,
again, at the job title and city level.
So it's a pretty simple dataset,
but we're going to be able to do some pretty powerful things
with it using this new dynamic array capability.
All right, that wraps up our project intro.
Now let's dive in.