Hello there.
And welcome back.
So we have co-created our very first project here in Palm Beach and congratulations you have a heart
so much because now you have learned a lot about the data analysis and visualization of the power.
So this particular we do I we just we we we we just going to what.
What are the different things which we have really done here in this particular project.
So I will be summarizing them all in a very brief manner.
So in this particular first page we have created some different kind of charts like this 100 percent
bar chart where we have seen the sales by different deal sizes for large and small.
Then we have created our line and bar chart for four different era analysis so we can see the ear by
ear.
You are what are the number of sales have been increasing in the past two years so far that this line
and column chart is pretty much useful.
Then again using the scatter chart and applying the plexis up here we can see or hear how this particular
things are going on for the status of our differences which we are doing how much I don't share.
How much are canceled and everything we can see year over year and also month over month by applying
the different kinds of filters.
I've been in the detail section.
So in the places we have taken the ears.
So we have we were able to get a little ear over here hear how all these states have been working on
for every year.
Then we have used our drill down doing a jar to calculate our deal size which is large and small.
When we applied on it we can pull that out each and every job we can filter out each and every chart
of our particular tab.
Then we have used this particular visual using chiclet slicer where we apply the images.
We have done the data maudling up here where we have joined our the images of all our products with
our main data and we're for the sentiment analysis.
Also we have joined the images so we were able to create this chiclet slicers with different images.
So for every image we can particularly easily filter out what each of our product for the second page
we have done our sentiment analysis of our customers who we are we have done this year versus last year's
series and we have calculated variance based on that.
So what were the sales of this year and what was it last year in any of the sales of this year has been
increased.
We have put it in a blue collar and if that is the sales.
Is it negative or does it feel having lost in our sales competitively from last year.
We have put it in the red.
So this has been done year over year analysis for each month.
We have done for the last year since we have applied us free three or four door sales for sale is there
aren't are there for all of Europe applied relative slicer we can use it from your different kind of
slice that option.
We have used related so we can check out what kind of slicing or felting we have to apply.
Also we have used our are up here and the sentiment analysis filters so if you want to see only the
positive feedback customers have given the positive feedback we can filter them out here or those customers
who have some negative or negative experience from the sales that we can check them as well.
So these are our customers list.
We can get to them.
This is all the sentiment analysis was done then we have checked the clustering and regression thing.
This is the regression analysis.
We created the regression defined the relationship between the two variables in the x and y axis which
it says and the quantity ordered and we have created a regression line up here.
See that trend between these two as quantity ordered is increasing the sales is increasing that this
trend line shows that.
And finally we have done our flustering clustering using two different methods.
First by the clustering method provided by power by clicking on these three ellipses and using the clustering
option find or the middle class starts and creating these three clusters clusters up here than we have
used the custom visual to do the clustering thing to separate our group our customers on our door or
the products based on their sales through different clusters.
This was hopeless sitting is done to blustering and regression is really a very important part of the
analysis.
So I hope you have understood all of these kind of different analysis which we have done like clustering
regression sentiment analysis these are very important.
And if you are left with any kind of doubt you can always ask me any time in the US S. I'll be happy
to help.
Then we have applied us sing slicers feature of power being the first AB so that we have synchronized
all of the slicers in each of our band just here in the first particular tabloid.
I want to see all the value all the details of my product which is motorcycle's I just click on the
motorcycle and then I to check that only for a year 2017 and only for the United States I can select
all of those up here and in all the different pages I will see only those only filtered they die as
we but in the same slicers that you go to.
This is how we have created our very first project an interesting project with a lot of things to learn
up here.
So I hope you have understood each and everything.
If not you can.
I'm always here to help you.
So that's all about this particular project.
And we're in the next lecture.
Thank you.