Transcript for:
Sales Data Analytics Project Series: Project on Department Store

hello everyone welcome to projects neuron first of all let me introduce myself my name is madula and I am a data analyst with 1.5 years of experience I have been involved in doing multiple projects in this domain my expertise lies in Excel SQL powerbi and tblo I have also been involved in guiding students in this domain for more than an year now I will be the instructor of your project and in this project series we will be tackling a simple analytical problem with sales of a department store so let's quickly get started see you in the next video bye hello everyone welcome back to this video series on sales analytics so let's first discuss about the tools that we will be using and the requirements for this project before we do the project itself for this particular project which is a beginner level project we will be using TBL all you need is a reliable system which has Tableau and Excel already installed in it you will also need to have a fundamental grasp of the sales domain and some familiarity with the user interface of Tabo once these requirements are fulfilled we will be able to move on to the project see you in the next video bye hello everyone welcome back to this project series on sales data analytics in the last video we had seen the prerequisite for doing this particular project so in this video we will be seeing the project overview so in and I will be telling you at each phase what we are going to do so the overview is we will understand what sales data analytics is what actually sales is what analysis do we do with the sales data and we will also talk about benefits of Sal sales data analytics what it does to the business and then we will go to data sources from where we get the data okay so these three concepts cover the domain knowledge of sales data analytics it is important to know certain terms and certain uh ideas behind why we do sales data analytics so that is why this has been included okay so once we complete that uh theoretical part part of sales analytics we will move on towards our project right so once we move on to the project first what we will see is the problem statement then we will be getting familiar with the data we will understand the data what are the data types what are all the uh types of characteristics that are there in the data okay and after that we will be loading the data into our uh Target tool which is tblo right and then we will be doing the visualizations then we will be moving on to dashboarding then we will be discussing about the analysis and then we will be ending it with a conclusion conclusion mean meaning uh after the analysis we will give you the final word okay this is the overall project View and uh this will help you understand how the flow is with respect to the project I hope you have OD and that's the end of the video see you in the next video bye hello everyone welcome back so in this video we will be discussing about data analysis flowchart so what is data analysis flowchart we will be discussing how the data flows from starting till the analysis and dashboarding part okay so how to approach any business analytics problem problem or data analytics problems we can see in this particular flowchart so this can also be inferred or integrated into any part of data science projects but this particular flowchart ends at dashboarding okay uh so let's quickly get started right so the very first step that you have to uh do is you have to understand the business okay business understanding let me explain what is business understanding okay suppose a client come clients come to us with their issues and some analysis problem okay but you have to understand that every business has its own mission and vision statements its own way of looking or dealing with the businesses what this will help is knowing this will help how to analy what type of approach do we do while doing the analysis right business understanding and apart from business understanding you have also to understand what the business needs from us okay this will help us approach our problem statement in a perfect or uh in the right direction and the analysis also will we will be able to do in the right direction right so this is business understanding understanding what typee of another could be what type of markets it is into what type of business is it into what what is its approach towards its clients right all these will help you understand and drive your uh analysis problem right this is what is called business understanding right so after business understanding we go to the data ction but before data collection you also have to understand the problem statement from the business okay once you understand the problem statement thoroughly and understand the business also then you move on to data collection so data collection could be from primary sources or secondary sources right so data collection is collecting the relevant data for which we are providing the analysis for okay so the data sources could be primary or secondary sources so what are primary and secondary sources primary sources could be as collecting the data directly from the uh people we can do it through questionnaires or surveys right so these are primary sources we get those uh uh data from directly from the people right and then secondary sources what are secondary sources these sources are where they have all already collected the data and kept it in store for other people to use like repositories or something like that okay so these are second sources any Ty type of uh uh data sources can be used to do your analysis provided it is related to your business problem right so the data usually is provided by the business itself or by the client itself what you have do with the data later is analysis right so before we go to the analysis part and once we get our data we have understood the business also we do the data processing okay so now that we have collected data from primary or secondary sources for that matter we will do the data processing so let's understand what is data processing data processing is um when you get the data the data is very very very very shabby like like it's not relevant some some features are not relevant and there are no proper order or structure or to that particular data so after you collect the data the first thing you do is processing and cleaning right the first thing that you do is choose the relevant features so what are relevant features relevant features are those features where um you see we ignore the parts or ignore any kind of columns or variables which are not needed for the um for our analysis how do we do decide which features are not relevant to our particular analysis that is where your business understanding and problem statement understanding will come into picture based on that business and understanding and problem statement understanding only you will be able to select the relevant features into our analysis right other features you can ignore okay you don't delete them you always once you get the data you always make a copy before you do anything to that particular data so that the raw data is always there whenever your client is asking right so you make a copy and then you remove the uh irrelevant features and keep only the relevant features which the data which the data is asking right or the client is asking you right so once you're done with selecting the relevant features you come to cleaning the data so there are several steps when you come to uh understand the cleaning the data one could be removing duplicates what do removing duplicates means removing duplicate means um sometimes what happens is while entering the data a person might have entered it twice or a person might have um while entering itself uh he might have forgot to enter some data or he might have forgot to enter uh or he might have entered the wrong data and he has entered again and he has not deleted the um First Data so these are duplicates so you have to remove the duplicates why do you have to remove the duplicates is because suppose I'm doing any kind of analysis or supp I want to find the median somewhere okay I have more numbers right in I have duplicates of a particular numbers and because there are duplicates my median will go wrong or the mode that we are trying if it is a categorical V variable the mode we are trying to find out might be wrong because there are duplicates right so and it will not give us proper analysis or proper results if we have duplicates in our data so it is very important to remove the duplicates next we will fix structural errors what are structural errors so uh I'll give you two examples for this okay so first a simple one called let's say you have the data and you're trying to take gender okay there are five people who are entering the uh that particular survey sheet or something like that and you are you you you have just written a gender okay some will write m capital M some will write small M some will write male some will write man some will write female some will write wom some will write F you see the pattern I'm trying to see but when you when it is entered into that system it will come like that and the system will take each of it separately like M separately male separately man separately like this but all belong to only one gender right so these are structural errors okay one more example of structure errors could be where you will face a lot of problems in fixing it are um dates okay so everybody has a different system of writing dates okay maybe I will write in uh date month and year format otherwise write in month date and year format some will write only two letters when when respect to years some will write all the four letters and separating month date you have hyphens somewhere you have slashes somewhere somebody will write something else so fixing these errors has to happen because analysis when you do analysis the formats should be regular okay so you fix these types of Errors some could be um let's say you're dealing with states in India right recently Bangalore has changed to bangaluru guram has changed to gurugram right all these changes and uh often times people interchange these names because it has changed some will write alahabad in St of prayag Raj all these but these two are the same cities this the name has changed right some will put slashes and right but the system will take it separately right so fix these types of errors are structural errors right and then after we fix them we will go to missing data okay so missing data is where people do not choose to write or give us that information some won't like to give us their phone numbers some wouldn't like to reveal their gender or some wouldn't like to pass some other address or something like that because they feel that it is personal some don't like to give email IDs because they might get unnecessary emails I think so yeah these are missing data sometimes they miss because of our human errors also but sometimes you might not choose to give that particular data so how do you deal with this missing data categorical variables are different but if there are uh numerical variables right continuous variables what do we do with them we can either replacement them with mean median or more depending on the character right so but before imputing or replacing them you have to definitely ask the business on what to do with that particular missing data okay it is the same case with outliers let me explain what are outliers these are extreme kinds of data uh one example could be suppose you are writing age okay um you use your number pad right while typing let's say the person's age is 45 you have just written 456 why because 456 and are there uh together and you have just uh while typing it's just by mistake it has come as 456 but person age can't be 456 we know that right there are limitations so this could be outlier these happen due to human errors right so how do you deal with out layers same as missing values you impute them with mean median or mode or you have to ask the business or what to do with it sometimes businesses choose to keep the outliers as it is okay so you need to know how to deal with it right so this also comes under cleaning the data next is check for correct data types okay sometimes numbers could be saved as text uh text could be saved as something else right date could be saved as text all these things should be changed okay before we move on and load it to our particular Target tool okay so all these cleaning has to be done once this cleaning is done if you think that it is done then okay if it is not done you go and clean it but make sure that the data is properly structured while you're before you load the data into that particular tool and you use the proper tool and then next steps comes in as analysis or dashboarding once you do the dashboarding or visualizations what you'll do is you'll represent your reports you'll present your reports and the business will see your reports okay so is your dashboard whatever the dashboard that you have prepared is representing what the problem statement given by the business uh is um is it relevant right is it relevant and uh is it solving that particular uh problem statement if yes then you generate those reports if not you go back to business understanding right business understanding this is what a total flowchart of data analytics is like so basically you just understand business simple steps understand the business understand the problem uh problem and then you go to the sources take the sources clean the data right after cleaning the data you do the analysis and dashboarding if it's satisfied generate reports if it is not satisfied you go and understand the problem once again that's it this is what data analysis flowchart is okay um see you in the next video bye hello everyone welcome to this video series on sales data analytics in this video we will be learning what actually sales analysis is what is a net for business what are the benefits and how the data sources are coming let's quickly get started so overall sales data analytics consists of analyzing sales data gaining insights into it and making data driven decisions data driven decisions meaning we get the data from the business we analyze it and then we try to gain insights we give those insights to the business and the business will take decisions based on our insights we have got the insights from the data itself right so from the data we are gaining insights and taking decisions that is data driven decisions okay so now it includes collecting cleaning and transforming sales data from various sources such as CRM systems sales reports and customer feedback okay so where is the data coming from for the business crn systems what are crn systems customer relationship Management Systems every company has a customer relationship Management systems and they will be getting data from there and they will be giving it to us other source could be sales reports which the sales people prepare how many sales have done who have purchased Ed how much they have purchased which project they have purchased Etc and then we also get the data from customer feedback how our product is doing how it is not doing okay all this data we will collect it okay we collect it and then clean it why cleaning is required cleaning is required because all these systems contain humor errors all these errors need to be removed so that we can clearly see what is the relevant data so that we will transform it and gain accurate by accurate I mean without any errors okay how we can get accurate results from this and we can give it to the business that is what cleaning does okay so this is an overview of business analyst so what is in it for businesses so sales data analytics it will help businesses or the organizations to understand their customers how will they understand their customers they will understand their customers by identify pattern and Trends they will identify the patterns and Trends in customer Behavior what could be customer behavior for example uh be here could be purchasing patterns or preferences there might be some instances where you perform a certain product over some other product there could be your buying patterns for example you are buying some products on a specific time rather than some other time one example could be you might be buying your stuff more on the first week of the month rather than other weeks because you might be having liquid cash cash or more money with you right so this is your purchasing habit okay and you might be purchasing more during the time of festivals this is purchasing pattern what are your preferences you might be purchasing something ethnic at one point of time something modern at some point of time elegant modern trendy at some other point of time okay these are preferences at one point of time you might be preferring something or other point of time you will might be preferring something else okay these are your behavior these are your patterns at one point of time you will form a pattern and these are recorded by the businesses to take the data and they give it to the data analysts okay so that they will gain more insights into your buying patterns okay so it can provide insights into effectiveness of sales strategies so by these data the businesses what they do is they form their sales strategies marketing campaigns and pricing strategies okay so how will they differ for example businesses might try to reduce their prices during some festivals okay they might start marketing uh camp CS at one point of time because some Festival is coming up and they understand that customers will buy at this point of time okay so that's what is there for business let's talk about what its benefits are sales data analytics can be used to answer wide range of questions what are these questions okay for example I am a business okay I own one business which has a lot of products so I want to know which product is selling High which of my products are customers are buying more and which of my products are going less so what it'll by knowing that what I'll do okay I'll try to reduce the manufacturing of those products which my my sales are less and then try to to magnify the manufacturing of those products which are going well that could be my decision again this is a data driven decision and then what are the customer segments what are customer segments segments are those where uh they divide businesses divide the customers into segments suppose they are my I want to launch my business only for ladies I have uh some jewelry which are catered to only only for ladies ladies is a customer segment based on gender right and or I have some product okay which I only cater for babies for example first guy okay they're not they do not do anything for adults right so that is one customer segment right so that is customer segmentation based on gender based on uh class based on um the age there could be different other factors they just cater to one segment of customers okay uh suppose if my product is there for all segments okay I want to see which segment that particular product is profitable to and I will cater more to that segment maybe I will customize my product to that segment right this decisions a business can take okay so my what are my sales channels my sales channels could be online could be offline could be shops or something else and I want to know which channels I will be able to sell more okay and I will be able to take decisions based on customer churn customer churn meaning how my customers are coming back or not coming back to buy my product or if they are not coming back to buy my product if they're not coming back to buy my product again why are they doing so that that is customer CH okay so by using this data analysis they gain a Competitive Edge Advantage competitive advantage over their competitors and it will help them to optimize their sales process and it will also improve their revenue these are the benefits of doing sales data analytics for any business okay moving on let's talk about data sources what are data sources so data sources are where we get our data from uh these could be CRM uh sales reports website analytics social media or customer feedback okay let's discuss each of them CRM CRM is customer relationship Management Systems okay so these are systems or softwares that are put in place by businesses so that they can collect customer Behavior customer interactions sales interactions and customer feedback so that they can collect it and they can gain insights into proper customer behavior and they can identify sales Trends and they can maximize sales performances okay now moving on to sales reports what are sales reports so these are detailed over overview of the sales performance that are done by the company okay so these are connected to the point of sales Point of Sales could be a person who selling the selling your product the business's product or any website that you create which usually takes care of the sales transactions okay so these all these people or these softwares collect that data so that so that they can give a total overview of the companies or the businesses performance they could based on what based on their revenue their sales volume and their uh let's say sales performance right all these can be collected so these consist of sales reports these could be one of the sources of data for a data analyst to do sales analytics okay so now moving on to website analytics okay what is website analytics so let's take the example of Google analytics so what does Google analytics do okay so when you open Google and you try to shock Okay Google tracks your data or Google Tracks your actions right where you're visiting which websites you're visiting more okay and after visiting that website what for what you are searching for more right for example you're searching for shoes in the in one particular website okay all these of uh all these are called customer behavior these customer Behavior are tracked by those Google analytics website sheets and they are kept this data is kept so that we can gain insights into customer behavior and by this what can be achieved by this we can achieve that we can improve our website so and in turn which will improve our sales so next next what we come to is social media okay social media uh so we collect data from Facebook LinkedIn there are many people who sells product or on all these social media this one especially on Instagram you might have seen right so this social media um when you run campaigns in social media let's say I want to sell one product and and I have a handmade product or something like that and I want to sell my product on Instagram or on Facebook I run campaigns when I run those campaigns these social media collect data what type of data on is that what kind of customers are coming uh and actually visiting and seeing the brocher or what kind of campaign that we have conducted right who are converting into potential customers who could be potential customer and who are actually converting all these data can be seen okay so the next time we run a campaign into social media we will be aware of where to send and which customers to focus through right this will improve our sales also this will um make us enable us to see or to send campaigns to Quality customers which are likely to convert into customers right and then we let's move on to customer feedback so customer feedback could be anything related to the product or whatever uh your business is selling okay by customers feedbacks we uh tend to gain insights on what are the pain points what do you mean by pain points okay so what is stopping our customer to buy our product right what is stopping our customer to buy our product and what is actually enabling the customer to buy our product okay feedback would be uh helpful very very helpful to understand how our product is working how customers are um engaging with our product okay which will in turn improve or optimize our sales performance okay so these are all the data sources that can be used for sales data analytics there could be other sources also but these are very important okay so uh these data sources we collect the data from here we clean it we process it so that we can do further analysis once we clean and process it and we analyze and we show the sales analytics dashboard okay that's all for this video see you in the next video hello everyone welcome to this video series on sales data analytics in the previous videos we have seen a brief on what sales data analy itics is and what we are expected to do on sales analysis okay now let's get on forward with our project we will be doing a simple project on department store and before we start any project we have to look at its problem statement what the business for wants from us and what kind of analysis it is or output is the business expecting from us we have to have a business understanding okay so let's quickly move on to the problem statement let me first read the problem statement and then we will try to understand we have a data set of a simple department store which is spread across USA the owner of the department store wants a dashboard where he can track how well his department store is doing in terms of sales profit and quantity of items sold okay pretty simple he wants his sales he wants what um what kind of sales are happening he wants what is the profit okay and he wants the quantity of items solds across and it also says that the department store is spread across USA okay he also wants to know how well the categories of products are performing in different regions so now we also knows know that we have different cartic theories of products okay so the owner thinks that that a lot of his customers buy two or more products per order but he wants it to be confirmed by the data profit is 30% of selling price okay so we already know that the profit um the owner is already in profits okay and he thinks that customers usually buy more than two products okay so that is his assumptions okay so he wants it to be confirmed by the data Okay so so we have different regions we have different categories we want to see how what customers are buying uh I mean in what quantity the customers are buying okay we have to display the profit right we have to show the sales and profits right this is what the owner is expecting from us the owner of the department store okay simple retail store a simple problem statement let's quickly get started on the project that's all for this video see you in the next video bye hello everyone welcome back to this video series on sales data analytics we are currently doing a project on department store and we have already seen the problem statement so now in this video we will see the flowchart by flowchart I mean we will see the flow of our data from right from the problem statement till the ending analysis part okay so the very first part of any uh project is data inje we have already discussed about the data analysis flowchart right in couple of videos before so this is particularly for this project right so in the data inje part before before data inje uh we usually see the problems statement which we had already seen in the previous video right so the problem statement is basically the department store owner wants to track sales and profits across his department store across Europe right so this is the problem statement so let's understand what is meant by data inje data inje is basically loading the data that particular data where the source uh source is there we are taking that source and loading it into our Target tool right that is data ingestion okay ingesting or bringing it into the target tool right is data injection right so that our particular data is available in CSV format CSP is comma separated values okay each point is separated by a comma that that is what is CSV means right so it is available in a CSV format we will talk about the data also uh in the next video but now let's just understand the flowchart right so that's CV file we will use and try to load it into tblo Tableau has a lot of variety of uh options from lot of sources you can extract the data or you can load the data from okay so it is easily available in Tableau you can directly load the text uh uh CSV file using text option okay once you load the data you will see if each of the column or each of the variable has the correct data type or not right so if it doesn't have the correct data type we can change it in Tableau itself right each and every column you will see how many columns are there how many rows are there how much data is happening right and if there are any uh other missing values or something like that you will be able to clean it first before loading okay so even after loading there are some feature there is one feature in Tableau where you can use tblo interpreter to clean it but it is better that you clean the data and then load the data into Tableau right but the data that we have is pretty much clean and it has all the values right it doesn't have any out layers or duplicates so check the data types and you can use extract connection right what is extract Connection in uh Tableau is you have two types of connections live and extract live connection is where the data keeps loading okay extract is where it will take the part of the data and then you do analysis on it right so you use extract connection okay it'll be easier later okay so after you load it we move on to the visualizations so this there are basically only four charts that we'll be preparing in the visualizations part which is uh we will be preparing a line chart a bar graph a histogram and a map okay map usually takes geographical locations um geographical locations without geographical locations you can't do any maps and histogram uses only one variable okay so in that one variable you have have to create bins that will also be taught uh in a detailed manner when we do the visualizations bar and light line charts are pretty easy right so once we do that we have to uh create headline cards what are headline cards are these are values that will be appearing on the particular uh what do you say that will be appearing on the particular uh screen or on the dashboard so that uh it will be easier for the Observer to see right these are headline cards we will prepare three headline cards showing sales quantity and profit right and then we go to the dashboard part and make it presentable and interactive you we will set the size of the dashboard then we will be uh adjusting the dashboard make it uh uh make it presentable and then we use filters and make it interactive that is what is uh dashboarding is all about once we are done with that once our dashboard is done we will have to any analysis part is the main core of a data analyst right so we will give our observations and our suggestions based on the problem statement that is given by the uh client right so the client now is the owner of a department store so what we do is we take our conclusions give it on a report so that the owner can actually see and take decisions based on our observations okay we give our conclusions once we are done with the conclusions uh our project is done but I have already already created an assignment for you so that you can uh give your observations or uh you can practice on your own right so this will be the flow of our project going forward so let me just U show you how our final dashboard would be right once we uh finish it right just give me one second so this is what our final dashboard would look like I've created it in a dark thing okay so these are the charts this is the line chart bar uh this is the histogram this is a bar graph and this is the math right and these are all headline cards right all these will be integrated and shown to you while creating the project okay so let's this is the end of this uh video we will end it here and see you in the next video where we will be discussing about the data and its understanding right bye hello everyone welcome to this video series on sales data analytics in the previous video we have seen the problem statement of a Department Store where the owner wants to see a dashboard on sales profits and the quantity of items sold okay now in this video we will see what is the data that is given by the client and we will look at its data types and we will also see what all the variables mean right so as you can see on screen this is the data given by the client right and it has 19 number of columns and it has about 10,000 rows right 10,000 rows so next what we will be doing here is we will be seeing what each row is and what it means and what are all its data types so let's quickly get started this is row ID so this is just numbering of the uh of all the row that's it okay now this is order ID so what is order ID suppose you go on shopping on any kind of platform online platform e-commerce platform or something like that you will see that once you place an order you will get a unique ID called the order ID right that is specific to your order so the businesses can track the or track the shipment or the order based on that order ID okay so this is the order ID for which a customer has ordered it will be unique for each customer and each order okay see uh you can see that there are uh two order IDs here with the same order ID right there are two orders here with the same order ID so this could be the thing and this could be something that the two products that they have ordered could be ordered at once so for for both the products there is only one order ID okay so every Pro for every order it is a unique ID okay next we will look at the order date this is in date format okay so don't worry about this once this is there uh this is a proper date uh because the column is compressed it is showing like that so the order date is where the customer has put the order on okay that is when you got get the order ID also the date in which the customer has ordered the product ORS right Shi it okay so this is the date where the customer sorry the business has shipped the order okay it might be giving it to the Delivery Agent okay or it might actually be G uh giving it to to Del delivery itself okay that is the ship date okay so for different orders there might be different uh ship dates okay so one order might take more time some other order might take less time it also depends on what kind of uh shipment or how fast you need the customer need okay that is ship mode so that this is uh this is classified as standard class first class and second class so let's say first class customers whatever the ship mode is if it is first class the customer might get quite early because that is a uh speed order okay the standard is normal second class is might be something more than first class okay media model something like that so this is ship mode okay and then we have customer ID okay so this is the discreption of the business itself so the business will classify or this particular owner has classified each customer by giving them a customer ID what is customer ID uh like you have your employee ID or you have your student ID each customer will have customer ID okay so that so that the customer can be identified why we are giving a customer ID when there are already customer names in the next next row because we give customer ID because there might be name duplication right so customer ID will ensure that there is no such thing happening okay so next we have customer name these are the names of the customers okay so you can see there are multiple columns with the same name okay and this is they are also the same order ID right so all these order IDs are same because this particular customer has ordered multiple products on the same date okay so all the orders will have all the products will have same order ID okay and the sales agent the so next we have sales agent sales agent ID okay this is exactly like having employe ID and student ID okay so each sales agent that has sold to that particular customer it has a different ID so those IDs are given here okay the names of the sales agents are not given only the IDS are given okay so the next is the country we know that it is us we uh then we have City we have state we have postal C code and we have region okay these are all the City postal codes are uh and City and region and country are all the notes of uh the stores the department stores that are present in each region right each location okay and the next column is product ID so what is product ID each product will have its own unique ID right so so this product ID that you are seeing here is the uh product ID for Bush SAR set collection suit bookcase okay so this comes in the subcategory of bookcases and category of furniture what is category and subcategory so we have already learned that there are separate categories of products that the department store is selling okay so there is furniture There is office supplies and there is technology okay so each each will have these three are the categories and each will have many number of subcategories for example for office supplies as binders art okay uh binders artart envelopes uh all these things papers all these things office supplies we'll have labels also and then in the office we have uh Furniture also like tables chairs all these things so that comes under Furniture category something like that okay so each subcategory will have different different products product names like bookcases there there are there might be different models of bookcases that are there okay so different styles will have different product names so these are the product names that are given to each product okay and then we have sales sales is an uh sales is what uh it it is given in dollars because uh the sales are uh the sales are in the US right so this is a number this is the money from that particular order right so and the next how many quantity did the particular order or the customer take in that order okay each each order will have different different quantities okay so each row what does it represent okay it represent it represents what that a customer with customer ID so and so has ordered this particular uh product okay this particular product with product ID this belonging to these uh category and subcategory of product uh products okay they have ordered on this date with second class shipment ship mode okay and in this is in this particular region of United States this was dealt by this particular sales agent and the order ID is this it was shipped on this date this this is the sales that is got we have got from that particular product and this is a quantity that has been purchased by this particular customer this this information the whole row gives likewise we have 10,000 such rows okay this is the whole information or this is the whole data that is being Des described okay now that we know what is the data let's look at its data types order ID should be numbers pretty easy custo order ID okay what is order ID see we have characters also we have uh alphabets or characters and we have numbers also so what do we do with this kind of this one we will put it as text only because order ID we don't really do any quantitative calculations on this order date and ship date both are dates ship mode again clearly text right and then customer ID same as order ID we do don't do any quantitative operations on that so we will look at it and we will see that it is text okay customer name pretty easy text sales agent ID okay sales agent ID is a number technically but uh sales agent ID are these are IDs which belong to categorical valubles we count it okay these are not continuous right so this can be considered as text also okay if you put it as number also doesn't matter okay and all these belonging to that particular region or state it comes under geographical values right all this will help us when we are doing Maps next we have product ID each product will have a unique ID right okay so this is again the data type is again like order ID and customer ID okay text data type clearly category and subcategory are also text data type product name also is Text data type okay so sales and quantity both of them will have number data type or decimal data type because we have to do quantitative calculations this is this is a target variable that we usually say okay so these will be number numbers or decimals or whatever according to the data type okay now that we have clearly understood the data let's move on to the next video where we will be seeing how we upload the data for our analysis as we already discussed we will be using Tableau in this particular project project so let's move on to the next video bye hello everyone welcome back to this video series on sales data analytics we were doing a project on department store in the previous videos we had seen the type of data that the client has given us we had also seen about the data types of that particular data now in this video we will see how to load the data so let's quickly check what type of data we have what type of file format we have so that it'll be helpful for us to load the data in T So as you can see on my screen wherever you have saved your uh particular file that is given in the resources save it somewhere and open that file okay see uh open that folder so see the type of the file is comma separated values file okay or CSV file okay so now that we have understood that it is a CSV file we can quickly go to Tableau and try to open it and try to load the data okay so open your tableau as soon as you open your Tableau this particular screen will open okay so and on the left plane uh left pan you can see you connect okay okay so this connect data will connect you to various types of data sources that are available so RS is CSV data CSV data is also called text files okay so here in this section you can see text file right click on that text file and the and navigate in your system navigate to the file that you want to open click on that and click on open right once you click on open it the data will be loaded okay in the left you can see that we have loaded the department store okay the file is already present it is already loaded on here you can see what are all the uh fields that are available the column names row ID order ID order date ship date all these we had seen in the uh data section where we have explained about the data and let's just check if all the data types that we had discussed earlier have been correctly taken by tblo or not it usually takes um but let's just see okay so firstly there are 19 fees and 9,994 rows which we had already seen in the Excel file ear earlier okay so coming on to the data types number this is right row ID order ID text or ABC is file in any case any which ways if you want to change the data data type in tblue or it has not interpreted it correctly you can just see this uh down arrow Mark here click click on it and you can see all the all these things oh sorry you can click on ABC here and you can change the data types over here but now it has correctly interpreted it so I'm leaving it like that so order date ship date this is date this is the symbol for date which is right this is also right second class text is Right customer ID is Right customer name is Right sales agent ID number that is fine and uh all these uh geographical this is this is a symbol for geographical data so this is also fine okay and next uh region South ABC Fine this is also fine category ABC Fine product namec fine and sales and quantity are in numbers this is also fine so now that the data is loaded we are good to go to the visualizations okay so that's all for this video see you in the next video bye hello everyone welcome back to this video series on sales data and analytics we are currently doing a project on department store and in this project series we have already seen the problem statement and we have understood it we have also seen the data we have understood the data and now we are moving on to visualizations so let's get started in the last video we had left on the data source page we have to do the visualization we have to move on to the sheets to do that on the left hand bottom corner you will see sheet one beside data source click on sheet one once you click on it you will see the screen where we will be performing the visualizations right so on the left you'll see all the column names that we have on on our data okay and now for the first visualization we will be doing yearly sales and we will be dividing it into months so to do that click on order date drag it and place it on columns click on sales again drag it and put it on row now we are seeing sales for each year but we want it for months to do that on this blue pill you see year right we will change it to month once you hover over it you will see a down arrow here click on that down arrow you will be see seeing two sections based on the dates in the second section click on month once you do that it has changed to monthly as you can see January February March 2016 to December 2019 there are a lot of fluctuations okay now that we have this uh sheet I also want to see what is the average sales okay to do that click on as you can see click on we are on data you will click on analytics once you click on ADD analytics in that summarize options are there click on average line once you click on it drag it to the visualizations once you try to do that there will be an option coming add a reference line and with three options table pain and sell drop it on table because we want it on the whole visualiz ation see we have got the average line now we our visualization is ready but it's just lines that's it there are no values coming so what we will do is uh we will add labels to it so that I can see on the screen what are all the labels that are coming so to do that click on data click on sales drag it and on the mark shelf drop it on labels see we have got the labels for each month okay no now I don't want to see the value like this because it's very shabby I want to see the rounded off figure maybe up to thousands right to do that what you'll do is in the mark shell we had just dropped the sales right click on that down arrow once you hover over that green pill and click on follow format once you click on format you will see this options coming here right click on the numbers click on number custom so reduce this to zero decimal places and display units in thousands once you do that all your thing will change all your values will change right so now I have the average line but only when I over over it I will see the value what if I want to see this value written here to do that click on it and click on edit once you click on edit you will get the screen okay and in the line option in the label we have to change the label right in the label instead of computation click on custom once you click on custom you will see that there is a line appearing I will type average and uh what I will see I want to see the value also right to see the value click on this greater than symbol that is there right and click on value and click on okay right click anywhere else your normal is your normal visualization will be seen see the average value is also being displayed okay now um this this looks very plain to me I want to beautify it to do that what I will do is there's a format is already coming just close it right to do that um let's say right click on it and click on format okay and click on this font a font go to sheet if Rose is there don't put it go to sheet if sheet is there font is fine now I want to change the font also right I don't quite like this font I want to change the font click on this down arrow you will see the options for changes right uh click on this button and I want to change it to Century goic just on see find Century Gothic okay I will leave it at 9 UM okay so I want it on a darker background so I will change it to White the font to White Once I changed it to White since I have not changed the background to Black you won't see anything because the white of the uh font font over here and background will match but then once I change the background to Black you will be able to see the font don't worry okay so I'm changing this to white okay the font will come back as I said and yeah the whole thing has changed now I want to change the background to change the background see go to this Paint Bucket which is called shading once you hover over it click on that and the and on the default on the worksheet click on the down arrow and click on black right see this font has come back right and I don't want on these lines okay these are rows right so click on rows click on rows there's nothing highlighted but these are lines right so click on these three lines these three lines and rows and on the grid lines click on it and select none over here once you select none the lines will go right done now I want to change the color I I'm not quite liking the blue on the black background so to change the color on the mark shelf click on color and the blue is highlighted change it to maybe yellow green no orange okay let's change it to Orange now I think my visualization looks good but uh this line seems to be little thin let me uh change the size again click on the size to change the size and just drag it see it has changed now that this has changed I think one more change I have to do is the average line so this is dark I have to make it light so click on it and click on format again you will see it changed where there is line click on the down arrow and change it to probably this color and I don't want it to a straight continuous line I want it to be a dashed line right I changed it to dash line and clicked on it okay looks good for me my average line I can see my visualization is ready and the next thing I want to change is the headings I want to see early sales here double click on it on the heading you can change the font to the one that we are using let's keep a uniform font 15 is fine for me 15 size is fine for me make it bold okay and make it white color and Center it and change it to yearly sales okay let me give space right this is fine and click on okay my visualization is ready let me quickly change the name of the sheet yearly sales it is important to change the sheet of the name we will see why it is important in the dashboarding section right our sheet is ready and our visualization is also ready that's all for this video see you in the next video bye hello everyone welcome back to this project series on sales data analytics we're currently doing a project on department store and in the last video we had completed our first visualization now let's move on to the second visualization we will be creating a bar chart this time okay and we will be seeing the sales based on categories right so let's quickly get started okay so before we move on there's a lot of formatting that we had done on the last screen we will keep that formatting to keep that formatting what you can actually click on either sheet but what what I'll do is I'll right click and I will duplicate it once I duplicate it I will take out all the pills that are there in this particular uh visualization why I'm doing that because as you can see the formatting will be there we don't have to waste our time on it okay by doing it again and again so this time I will change the name to sales by category and see our uh formatting is the same and click on okay change the sheet and name also sales by category once that is done so what I'll do is I will put the sales on columns click and drag it and then I will put category on rows once that is done see it looks a little this one small not to worry we'll just change it on the top you can see standard right in this tool bar you can see standard click on that particular down arrow and click on entire view it will change now this doesn't look like a bar graph it is a bar graph so so because last time we had increased the size over there we will just change the size to one bit slow H now it's done we don't need average line we will just remove it Okay click on the average line and remove it now we will put we will see the sales also on this click labels click on sales drag it to labels just like last time we've got the labels now this time we have vertical lines right so we don't want this vertical lines also so right click click on format you're getting this click on this two lines and in the columns click on columns change the grid lines to none done okay so my visualization is done but what I want I want to sort it from small to pick I'll just go to this particular toolbar you see these bars here and there running like that okay so these will sort if you sort like this in descending order the highest will come first if you sort like this the lowest will come first okay so this is done my sorting is done now what I want is I want to change uh see this like uh let's say say I want to the lowest sales category to be in the lighter color and highest category to be in the darker color to do that what I'll do is I'll close this I will click and drag sales to color but it has changed to Blue right so you don't have to worry about that again click on color click on edit colors on the pallet there is automatic right on the pet click on the down arrow once you click on that you'll get lot of options I'm using this one let's say yeah orange gold okay now it's changing from gold to Brown actually okay and click on okay it has changed right now I'm quite comfortable with the sales by category okay we have we are done with the visualization okay see you in the next video bye hello everyone in the last video we have seen sales by category and in this video I will be teaching you how we can prepare a histogram and and we will be C covering sales by quantity so let's quickly duplicate our sheets duplicate change the names sales by quantity okay sales by quantity again clear the sheet so to do a histogram we need only one variable which since we are dealing with quantity click and drag and drop it on columns okay now it's a bar graph to make it a histogram click on here show me and then click on histogram once you click on histogram bar here in the show me you will see that bin has been created right see quantity it creates on its own I mean the Tableau by default creates bins on its own so it is on R part to change the size of the bins as you can see it is somewhere between 1.5 and 2 right somewhere between 1.5 and two but we want bins of size two right so how do we change that it is pretty simple it the new new item has been created quantity bin you see the down arrow click on the the down arrow click on edit once you click on edit you will see the size of the bins is 1.77 we want it to be two just change it to be two and click on okay see the size has changed now that we are ready with the visualization let's change the color color to Orange since we want it to be uniform and then one more thing we need the labels okay so labels how do we do we'll just again take quantity drop it on label so as you can see the it is little wrong uh it is danging between 4,500 to 5,000 and it is showing 12,000 which is wrong right so the only thing that is uh this one changing is you can see that there is sum of quantity it is taking the sum of quantity we need the count to do that just click on the down arrow okay and in the sum measure sum click on count okay it has changed now see okay as per me this is fine my visualization is complete and I'm satisfied okay so in the next video we will be doing geographical Maps Okay that's all for this video bye hello everyone welcome back to this project series on sales data analytics and we are currently doing a project on department store in the last video we had seen sales by quantity and how we created a histogram okay so now in this video we will be seeing how to show sales by region and how to use geographical maps in tblo okay so now let's quickly get started uh I will just duplicate the page I will change the name to sales by region click on okay again change the sheet name to sales by region okay so now I will clean the sheet just take out all the parameters okay now that we are ready so it is very important that uh while doing geographical Maps if you have any geographical data we arrange them in hierarchical order for example we have some country under that will come State under that will come City something like that so we will be doing that in hierarchical role now okay so as you can see there are 1 2 3 uh 4 geographical data and we have to arrange it right so there is country then there is uh State we will just click and drag it and when it when the country or region is highlighted drop it now it says create hierarchy name country or state region or state you can you can write your own name okay I will say [Music] geographical Geographics okay and click on okay now see country and region is there state is there after that we will be putting in city and then what else is there postal code right once that is done our hierarchy is created right now what do we do I I will just click on state I will go to show me show me and there are two maps that are highlighted I will select this map this particular map field map click on okay okay see the map is created right so now it's empty it is it is it has taken all the regions but it's empty so we need to so show sales right sales for each state so what I'll do I'll take sales Okay click and drag it and put it on label see easily sales has come for each state right now uh like we did on the bar graph I want to see darker color for the states where the sales is more and lighter colors for the states where uh the sales is less to do that what we will do is we'll select sales from here okay sales click drag it and drop it on color since we have already selected earlier the go gold to Orange it has by default taken that color okay and it has been created so I can't for the light colors I can't quite see the sales right so what I'll do I'll just click on the text one click on the down arrow click on format okay so font click on black that's it now I can clearly see what is there what is not there okay so what if in this particular uh visual I want to see sales in decimals and I want a dollar sign in front of it what will I do don't have to do anything since this is already already open go to numbers go to already is there one decimal you can click and where there is prefix just just uh type the dollar sign this is prefix this is suffix so we need it in prefix we have put it in prefix right that's it okay now this is fine but one more problem I have I have all my other sheets in Dark theme but this is in white I can't have that right so what I'll do I'll I'll go to the screen right click and click on background layers once you click on backround layers this will appear right so in the style instead of light I will choose dark it has changed automatically okay so in this we have completed the sales by region also we have created successfully created a map also I can happily see all my re I have got my dark theme also okay so yeah that's it for now so in the next video we will see how to create cards okay so that's all for this video see you in the next video bye hello everyone welcome back to this project series on sales data analytics we currently doing a project on department stores and we have come to the end of visualizations now now in this video we will be doing cards we will be doing sales profit and quantity cards which will will be using in our dashboard in the final dashboard so let's quickly get started the last we had left on the uh sales region okay so let's go close this background layers uh click on sales by quantity right click and duplicate we can't really do duplicate the sales region because it's a map so now let me change it to Sales card change the heading to sales card okay right click and change the name of the sheet also sales card okay remove everything right now click on sales drag it and put it on columns now you have already got the bar chart but we want text okay so click on show me and click on the first text tables right click on it you can see that the amount is appearing sum of sales is appearing here okay so now since this is a text right so we will change the text do some for formatting click on Text Okay click on text and you and you click on the three dots once you click on the three dots it will appear now let's select this and change the font to 15 make it bold okay and let's just enter and write sales right once you write sales uh take out the bold and change this to 12 okay now I want this one in Orange and this one is white in white so change it to Orange and click on okay now change the alignment to center right vertical also Center and but is still appearing on the top left corner to change that in the options in this title bar click on the down arrow in standard and click on entire view it has come in the middle okay now what we will do is um for sales it'll it'll be nice if you put decimals and dollar symbol also to do that as we have done earlier we can change it through format options click on the down arrow in the sum of sales click on format okay and in numbers in the custom change it to one decimal places and uh put a prefix as dollar sign that's it our sales card is done now let's move on to quantity card so to do quantity card just duplicate sales card okay rename to quantity card okay rename the sheet name also okay uh cross this and now uh just instead of sum of sales just drag quantity and say drop it right on top of sales like this right on top of sales it'll be replaced right and since it's not sales it is quantity it is in numbers and we can change the text here okay click on text and click on the three dots instead of sales you write quantity click on okay okay okay so we are done with the quantity card also let's move on to profit card okay for the profit card we need to do some calculation let's start with doing that calculation to do the calculation of profit we have to first create a calculated field so that we can calculate the profit so since the owner of the department store has already observed that the profit is uh 30% of the sales okay so we'll do that only we will multiply sales with 30% all right so to create a calculated field on the on the data pan just click on the down arrow over here as I'm showing you and click on create calculated field once you get that let's change CH the name to profit let's change the name to profit and start writing our formula let's say we are multiplying sales with 30% right so let's start writing s a e sales so once you write start uh start writing you will see you will see already the column names are mentioned Okay click on one column name okay and type into point 3 30% is.3 right 0.3 okay so you will see that the calculation is valid once the calculation is valid you can click on apply and okay now you see that the new item has been added to profit and you can now what you can do is you can start creating the card to do that duplicate the quantity card and change the name to profit card right profit click on okay change the name of the sheet also profit okay now like like you have done for the quantity card just click on profit and drag it and drop it on the quantity right this has changed now uh go to text go to this three buttons instead of quantity you write profit profit Okay click on okay now profit will be in dollars only right and in points we can quickly change it through format options go to the screen pill click on the down arrow click on format on the numbers custom change it to one decimal place and put the prefix as dollar and click on okay our profit card is ready all the three cards are ready okay so we have all our visualizations and we have all our cards ready right we have four visualizations and we have three cards so with this we will be proceeding towards doing the dashboard okay so that's all for this video see you in the next video hello everyone welcome back to this project series on sales data analytics we are currently doing a project on department store and in this video we will be proceeding with how to do the dashboard in the previous video we have already completed the visualizations and we have also done the cards so in this video I will be showing you how to set up your dashboard how do you set up the sizes of the dashboard so that we can see it clearly right so let's quickly move on towards our session so in the last video we had ended here on the profit card okay now to do the dashboard on the bottom middle of the screen you can see these options options right this is what you press or click to get a new sheet but to get a dashboard you click on this particular button where you see four boxes right click on this button so this is the screen that you will be seeing when you get a dashboard right on the left you can see all the sheets and the size also so here we will be setting up the size you can by default we will be getting the size you can use it for phone also that is a different layout but we will be using it for screen only okay so let's set up the sizes by default it'll be 1,00 by 800 okay but um you can uh give fixed size automatic and range also give fixed size and I will be using cust size also why by using custom by using custom you can change the width and the height of the dashboard so I want to use 1500 let's say 1500 by 850 this is the size that I want to use these are in pixels okay so now my dashboard is set up okay what we will be doing is these are are all the objects we will be using these objects to place our sheets and then uh create our dashboard so in for this video we are done setting setting up the dashboard in the next video we will see how to actually create the dashboard right bye hello everyone in the last video we had seen how we set up our dashboard how we set up the size of the dashboard in this video we will be seeing how we make our dashboard okay last time we had uh talked about the objects we will be knowing the dashboard objects in detail now okay so let's uh this this is a horizontal container vertical container okay we will be using these two mainly to put our sheets you can put the sheets directly also but they'll be uh all shabby to regularize and make our dashboard in order we will be using objects right so there are others as well we will be seeing them as we go forward okay let me put a horizontal container click and drag it onto the screen the screen that you're seeing you have set up here right that is the size of the screen so drop it here in this container we will be placing our sheets okay so what once we are placing our sheets what we'll do is first I want to put sales by region it has occupied the whole uh screen but don't worry we will be using other as well so as you can see apart from my screen there is one other thing coming here right I don't want this on my dashboard so what I'll do is I'll cross it off right I'll cross it off I'll go to each sheet okay so this doesn't have this sheet and I will remove this container right remove the legend okay or hide it go to each uh visualization and hide the card sales by quantity category yearly sales region region also I will hide card okay now on the dashboard I will put uh let me use a vertical container I'll use a vertical container here okay so on this I will put sales by region see that card is not available after this what I will do is on the bottom I will use this card okay sales by category I'll drag it okay once you once I'm I'm dragging it you are able to see the this particular and this particular container right grade out area I'm just putting it down okay once you get this half graded just release it see both the cards have come now I will use another vertical container where see once you put and drag this this gray out area is coming in each visualization but I don't want it like that I want it on the whole sheet so let's drag it further H so when this gr grade out area comes on the half of the sheet then release it we have created one other container and in this container what I will see is I will put sales by quantity on top right and what else is left yearly sales yearly sales I will drag it to this sheet and take it to bottom only on this container I will see half of the grade out area and release it okay now that everything is released we have the four sheets okay now what I will do is we also need to give the cards once we want to do the cards you will put a horizontal container but where I want to put it on the bottom okay bottom of this whole sheet so like we did the vertical container we will see the horizontal container also where we see see the grade out area put it here right once that is done place your sales cards place your cards sales card is done quantity card is done profit card same like like like how you have placed those you will place them all three of them have come right now I want also want to put the title okay so how do I write the title I will use a text box text box again objects text in this I want to write it here just drag it wherever we have the grade out area put it there and right this dialogue box will appear okay so till now we have used um Century Gothic right Century Gothic size has to be 20 let's say I want to use uh let's say department store whole thing in Orange okay uh I will make it bold and sales sales analytics I will make it white and I won't do it bold I will do somewhere around 15 and select everything and put it in the middle and click on okay okay don't worry now what you have to do is just adjust all these visualizations so that it looks beautiful I'll be doing that right now you see along with me okay you can continue right I'll just drag it okay firstly what I'll do is take out the title for each and every card I don't want to see the title okay um no for this I will need the title right so in this okay it's already there so I want to change the color of the dashboard to Black let's say dashboard format default color to Black see it has changed now good right so the dashboard title title and all we will change the this one to Century Gothic okay and leave it like that right H so as you can see we have the dashboard so what I will do is I will just drag it huh and so that adjust these so that we can right make them even I think this looks fine yeah I'm quite satisfied this is how we have designed our dashboard that's all for this video see you in the next video in the next video what we will be doing is applying filters and making this particular dashboard Dynamic that is our agenda for the next video see you in the next video bye hello everyone welcome to this project series on sales data analytics we are currently doing a project on department stores and we have actually finished creating the dashboard now it's time to make it Dynamic so how do we make it Dynamic so suppose what is dynamic and how do we make it suppose I'm clicking on this particular sales quantity or let's say category office sales I'm clicking on office sales and nothing is changing but how I want to see is if I click on off office supplies here I want to see yearly sales only for office supplies what is the sales of quantity only for office supplies same kind of thing from the region and all these also have to change which is not happening right now so the best way is to use filters right now how to do that right once you click on the sheet or any sheet you will get a gray thing over here right uh you will get a gray thing over here in that gray thing the third one you can see is this use as filter so what we need to do is for each and every uh every visualization you'll have to click on that filter it will change right before we clicked it was Hollow now it is filled that means that it is using as a filter so let's do that for every sheet right every sheet and you can do that also for the cards let me do that for the cards and let me show you how each and every uh d uh visualization is changing dynamically right okay so let's say I'm clicking on office supplies see it is dynamic it is changing so only for technology this is the sales okay average is 17K highest is in November and sales of quantity is again more than two uh two quantities people are taking and there are new sales in over here and then highest sales were in 159 California like that and for technology likewise you are seeing so most of our sales are in California only office supplies also the same thing right so and according to let's say I want to see according to the region click on this region so it will show you from this region these are the sales by quantity these are yearly sales these are sales by category okay likewise if you click on on uh let's say November 2019 it will show sales at that point of time right so this is how we make it Dynamic all these also will change now let's say I want to know specifically for some particular month or something like that I can obviously click here but there is another way to uh what we will do is uh put on a dynamic slicer kind of thing okay so what I'll do is I'll click on the down arrow here on early sales okay and I will see I will click on filters right on filters I will see month of order date I will click on month of order date see this is coming this particular card is coming slicer it's called a slicer so I don't want it here I want to place it because it is making all my my this thing is whole empty just making all my sheet uh little shabby I will drag it once I click on it you see this two lines click on this two lines drag it and place it somewhere here uh yeah here once you do that you see the slicer has come for each month you can take it separately suppose you only want to see for one year probably okay so January AR 2016 to drag this December 2016 it is showing only sales for that particular time period this is how a slicer works right this is how we set up the slicer now all our dashboard is dynamic everything is set up our dashboard is ready our project visualization project is done okay so with this we complete the visualization and dashboarding part in the next video we will look at conclusions okay see you in the next video bye hello everyone welcome back to this project series on sales data analytics and we are currently doing a project on department stores we have completed the visualization part and we have also done with the dashboard now comes the conclusion part the very important part of any data analysis is once you do the analysis you have to report reported to the client or your senior manager in any company right so based on this particular dashboard let's draw our own conclusions on this so by seeing this chart I can see that the sales had drastically dropped down from December 20 2018 to the start of 20 uh 2019 but they gradually picked up and by the end of the year they have recorded the highest number of sales when compared to the Past right so and then again in December they have gone down but not so much too uh and the next thing that we can see is uh as the owner said people usually take quantities that is more than two so the highest number of quantities that people buy are 2 to four units they are 4,811 so his analysis was right and we can say that by by seeing the region the highest that has been uh the states of highest sales are in California and United States and we can say the lowest were in some where this one probably s the quota this recorded the lowest sales right and the sales highest sales category is the most of the products that are being sold are in technology right it has the highest number of sales so by this we can say that if they increase the products in technology their revenue might be more so that kind of analysis you can do from this but this is overall so if you see year wise also so the first year okay um so the later end of all the years we are they are seeing a hike in in from this particular uh visualization we can say that the later half the second half of the uh of the year they are seeing a spike in their sales right in the later half in the first half it's always low but in the later half later half it is picking up okay so let's see um in 206 let's say till December 2016 there uh Revenue was quite little low they were not getting anything from Wyoming or not Dakota but the highest sales Remains the Same everything the analysis also remain the same so let's say in the next year December 2017 January to December 2017 again in the later half they are seeing a hike in the sales okay but since the last year it has seen almost same it has seen almost same number of sales in technology and Furniture in 2017 right and in 2018 again technology is more same the highest are in New York and California the trend is same in all over the uh all over the years right right technology is more than office supplies than Furniture okay right the trend is same so the highest number of sales or profit that they've got is in 2019 so all in all we can say that the business is improving and if they concentrate more on technology uh related products they might actually see more of sales and they can concentrate more on New York and this one and they might have to probably do a lot more uh uh marketing over these regions Wyoming Montana sou Dakota all these reasion they might be able to do a lot of marketing right this is our conclusions from our project okay so that's it for this video we are done with the conclusion also in the next video I will be giving you some assignments where you'll have to visualize or answer some of the questions that are there and you'll be done with this project okay that's all for this video thanks for watching hello everyone welcome back to the project series on sales data analytics we have completed the project on department store but yet there are more things to explore and which is why we are giving you assignments to solve I've given you five questions based on the data and you can probably do the visualizations and come up with your own analysis apart from this if you can come up with any more analysis that is also more than welcome so you can display a top five sales agents top five products in terms of sales uh you can do top five products in terms of sales per each category okay in terms of top five products in terms of quantity what are the top products based on region so you can use probably filters or something like that and what are the who are the top five customers in terms of sales quantity and goods purchase these are some of the questions I have come up with if you can come up with your own analysis that'll be a great practice for you so this is the assignment and you can go ahead and start with your assignment that's all for this video thanks for watching hello everyone welcome to this last video of our video project series I hope you have found it interesting and entertaining over the past few sessions we have covered a lot of topics and now I'm going to give you an overview before we conclude we in this project we have seen what sales data analytics is how it helps businesses run their businesses well optimize it and how you can earn Revenue so over after that we have seen a case study of a department store and we have done our analysis based on what the data is given by the client we have also presented it through a dashboard I hope you have found it entertaining and interesting as we wrap up this project I would like to thank you our viewers without your support this not would not have been possible thank you for your encouragement and thank you for joining us on this journey I hope you have enjoyed watching the series as much as we have enjoyed making it from all of us here at uron thank you so much for joining us goodbye and take care