 students, we are talking about different type of graphs and in which situation you have to use which graph the next graph is this is called heretical graph and the purpose of this is that the one layer, the third layer, the multiple layers the information is stored in this way and then you can represent it in this way and in the variety of situations these graphs are used these are simple to understand as compared to many other forms or types of graphs in this you can see that the entries within the data set they do not need to have a dependent relationship but that is something different but the real thing to understand is that this is your top layer this is next, this is next and this is next this is first, this is second, this is third, this is fourth and below this there may be more we have multiple depending upon the situation but this is just to understand this is called multilevel hierarchy this is organization's hierarchy this is a family hierarchy or your geographical hierarchy basically you can see this in any way we have multiple examples available which we develop for understanding as per your time if you are talking about a time period you need to see it from another angle this is a simple representation when you store the data when you do indexing or partitioning you do partitioning of the data in the same way for example this can be your year this can be month this can be day and this can be your hour this can be minute and this can be second this is complete hierarchy and this is very unique knowledge to understand similarly you can see it from another angle at the first level it can be your country then it can be your state or province then your city and then your to the basic level this can be this can be your home address the purpose of sharing this is not just to use it for family tree this is an example basically it is a company the CEO of the company then you have different departments head and so on and so forth same concept is being used when you start developing your data structures when you practically work on it you will understand that this this is a hierarchy concept is so important how is your efficiency when you query the data in SQL or in any other so one thing is that first you do step by step first you come here after that you come here if your data is not properly structured but if you have partitioned the data then your query is so in that case if you have to go directly here then you don't have to follow this route you can access the data directly at this level and this is a very unique feature of different databases partitioning is available the purpose of sharing this is the concept of hierarchy in data science or databases this is okay this is just to explain you or to develop your understanding but if you look at the hind side or back side when you define the data structure one thing is called schema the data base the data engineers and data scientists and data analysts this is very important to understand the schema of the data schema is basically a combination of different tables and structures so in that partitioning is one of the very very critical features the efficiency of your data I have run a report because of that when your query is not structured properly then you come here then you come here but if you have properly denormalized the data then you can directly come here so you can imagine if you have millions of records of the data and if you have to direct it from each line where your target data then how much difference it will make similarly I have given you an example of root, edge, parent child, leaf node all these are different concepts and one more thing if I look at the last so this is their pre-application if you take an HR application in HR applications when you define things on the back end so this organizational hierarchy or organogram also says it automatically makes the application you have defined it in the department then you have defined their relationship with whom you report right if you are CEO normally in a big organization you can report a CEO 8, 10, 12 people in a small organization you define the HR application that the manager reports to the general manager and the general manager reports to the CEO so when you design something it is called one-to-many relation right so the one-to-many relationship basically is the same thing that you define below it is called scoreport it is called scoreport these people scoreport these 6 people scoreport so this is your HR in this system you have coded there is a different technique but after that these people below this you said these 3 people scoreport okay below this these people scoreport these people scoreport like this you link them with each other right when you link then features are available in the software when you want to print the entire organization chart or organogram so it takes information from the data that who is on the top who is on the bottom and mostly the charts in the organization from the manager level or the particular department each department also prepares an organogram so this is how it is seen but the data base structure point of view that is a different application this application this can be managed from the front end when you design an HR application as an analyst the developer but these are the things and you can use them as a data scientist when you design data structure you can use them