Visualization 

 Q : Challenge : Describe your challenge , including all relevant information . 

 Ans : Visualization of the data , that is in diversity , heterogeneity ( structured , semi- 

 structured , and unstructured ) and big in a volume or quantity , is a big problem . Speed is 

 also another factor in big data visualization but cloud computing and advanced 

 graphical user interface can manage the scalability of the big data . 

 There are some challenges in big data visualization which is represented as “ 4V ’s ” , 

 which is given below : 

 1 . Volume : High volume of datasets are enable to derive meaning 

 2 . Variety : Methods should be developed to combine different data sources as 

 needed . 

 3 . Velocity : Businesses should replace the batch processing with real - time stream 

 processing . 

 4 . Value : The Methods should be create business value by gaining insights from 

 big data 

 Q : Selection : In your own words , briefly describe the tool you selected ( e.g. , what it 

 is and why you selected it for your challenge -- including any appropriate video 

 lecture references ) . 

 Ans : Data visualization means to represent the data in some systematic forms or it is 

 about the explanation / description of the data by using images . It includes some kind of 

 attributes and variables that can be used for the unit of information . Visualization based 

 data discovery methods allow businessmen ’s to desperate data sources for an analytical 

 views . Some advance analytics can be integrated in the creation of interactive and 

 animated graphics on electronic devices such as computers , laptops . Mobiles , tablets , 

 etc 

 Reference Video Link : https://www.youtube.com/watch?v=FZSpUfsoezY 

 Q : Application : Describe how you applied the tool you selected to your challenge 

 ( e.g. , what you did and how the tool was applied effectively or ineffectively ) . 

 Ans : In big data applications , it is difficult to conduct data visualization because of the 

 high volume and dimension of the data . Mostly big data visualization has poor 

 performance in scalability , functionalities and response time . There are some solutions 

 to overcome the challenges and problems about data visualization are given below : 

 1 . One possible solution is the hardware on which you can save your big data to 

 put into the memory e.g. you can write your data on a notebook and then read 

 that material slowly and visualize it 

 2 . Having good expertise in order to understand the data e.g. if data is transfer in 

 your mother language then it is easy and quick to understand for you 

 3 . Data should be clean and understandable for visualization 

 4 . Data should be display in meaningful result for visualization effectively 

 5 . Another thing to visualize the data is to remove outliers from the data and create 

 separate charts for outliers 

 Q : Insight : Describe the insight you gained from applying the tool you selected to 

 your challenge ( e.g. , how an insight affected your thinking about the challenge and 

 about design thinking more broadly ) . 

 Ans : Visualizations can be static or dynamic . Interactive visualizations often lead to 

 discovery and do a better job than static data tools . Interactive visualizations can help 

 gain great insight from big data . Interactive brushing and linking between visualization 

 approaches and networks or Web - based tools can facilitate the scientific process . Web- 

 based visualization helps get dynamic data timely and keep visualizations up to date . 

 Q : Approach : Describe what you might do differently next time -- applying the 

 same tool you selected or a different one -- and the reason(s ) why 

 Ans : The tool which I will be used next time is the mind mapping because it represents 

 the ideas that are linked to a central idea and to each other . Mind mapping are used to 

 generate visualization , structure and categorize the ideas to look for patterns and 

 insights that provide designing criteria . We do this by presenting our idea and by survey 

 in order to ask from the people about the themes and patterns to emerge . Mind mapping 

 needs team spot for success . 


EMAIL: 
ID_NUM: 
NAME_STUDENT: 
PHONE_NUM: 
STREET_ADDRESS: 
URL_PERSONAL: 
USERNAME: 

### Task: You are a PII (Personal Identity Information) Detection. Given a essays written by students, you have to identify ONLY the following:
NAME_STUDENT - The full or partial name of a student that is not necessarily the author of the essay. This excludes instructors, authors, and other person names.
EMAIL - A student’s email address.
USERNAME - A student's username on any platform.
ID_NUM - A number or sequence of characters that could be used to identify a student, such as a student ID or a social security number.
PHONE_NUM - A phone number associated with a student.
URL_PERSONAL - A URL that might be used to identify a student.
STREET_ADDRESS - A full or partial street address that is associated with the student, such as their home address.
### Input: Visualization 

 Q : Challenge : Describe your challenge , including all relevant information . 

 Ans : Visualization of the data , that is in diversity , heterogeneity ( structured , semi- 

 structured , and unstructured ) and big in a volume or quantity , is a big problem . Speed is 

 also another factor in big data visualization but cloud computing and advanced 

 graphical user interface can manage the scalability of the big data . 

 There are some challenges in big data visualization which is represented as “ 4V ’s ” , 

 which is given below : 

 1 . Volume : High volume of datasets are enable to derive meaning 

 2 . Variety : Methods should be developed to combine different data sources as 

 needed . 

 3 . Velocity : Businesses should replace the batch processing with real - time stream 

 processing . 

 4 . Value : The Methods should be create business value by gaining insights from 

 big data 

 Q : Selection : In your own words , briefly describe the tool you selected ( e.g. , what it 

 is and why you selected it for your challenge -- including any appropriate video 

 lecture references ) . 

 Ans : Data visualization means to represent the data in some systematic forms or it is 

 about the explanation / description of the data by using images . It includes some kind of 

 attributes and variables that can be used for the unit of information . Visualization based 

 data discovery methods allow businessmen ’s to desperate data sources for an analytical 

 views . Some advance analytics can be integrated in the creation of interactive and 

 animated graphics on electronic devices such as computers , laptops . Mobiles , tablets , 

 etc 

 Reference Video Link : https://www.youtube.com/watch?v=FZSpUfsoezY 

 Q : Application : Describe how you applied the tool you selected to your challenge 

 ( e.g. , what you did and how the tool was applied effectively or ineffectively ) . 

 Ans : In big data applications , it is difficult to conduct data visualization because of the 

 high volume and dimension of the data . Mostly big data visualization has poor 

 performance in scalability , functionalities and response time . There are some solutions 

 to overcome the challenges and problems about data visualization are given below : 

 1 . One possible solution is the hardware on which you can save your big data to 

 put into the memory e.g. you can write your data on a notebook and then read 

 that material slowly and visualize it 

 2 . Having good expertise in order to understand the data e.g. if data is transfer in 

 your mother language then it is easy and quick to understand for you 

 3 . Data should be clean and understandable for visualization 

 4 . Data should be display in meaningful result for visualization effectively 

 5 . Another thing to visualize the data is to remove outliers from the data and create 

 separate charts for outliers 

 Q : Insight : Describe the insight you gained from applying the tool you selected to 

 your challenge ( e.g. , how an insight affected your thinking about the challenge and 

 about design thinking more broadly ) . 

 Ans : Visualizations can be static or dynamic . Interactive visualizations often lead to 

 discovery and do a better job than static data tools . Interactive visualizations can help 

 gain great insight from big data . Interactive brushing and linking between visualization 

 approaches and networks or Web - based tools can facilitate the scientific process . Web- 

 based visualization helps get dynamic data timely and keep visualizations up to date . 

 Q : Approach : Describe what you might do differently next time -- applying the 

 same tool you selected or a different one -- and the reason(s ) why 

 Ans : The tool which I will be used next time is the mind mapping because it represents 

 the ideas that are linked to a central idea and to each other . Mind mapping are used to 

 generate visualization , structure and categorize the ideas to look for patterns and 

 insights that provide designing criteria . We do this by presenting our idea and by survey 

 in order to ask from the people about the themes and patterns to emerge . Mind mapping 

 needs team spot for success .
### Output: 