Visualization 

 Visualizing always challenges our community of designers , coders , and developers to take on the   pressing issues of our day . Each data visualization challenge involves creators working from the same   data set to compete for unique prizes . Data visualization has changed our society considerably . These   are some of the challenges faced in today ’s world 

 VR 

 Virtual reality is going to have a huge impact on the potential for data visualizations , allowing people   to interact with data in the third dimension for the first time . 

 AR 

 Augmented reality may well be the single biggest change that we are going to see regarding the use of   data visualizations . 

 The challenge that data visualization is going to have is that those creating them need to make sure   they are doing so in an understandable and non - obtrusive way . It creates a new dynamic , where the   data overlaid needs to be clear , concise and not distracting . It ’s a fine line to balance on and a real   challenge for those who are used to creating traditional visualizations . 

 Development 

 VR and AR are likely to be interesting technologies in the future , but for the time being , we are still   going to be consuming the majority of our data through traditional 2D screens . As the number of data   visualizations increases in almost every area , the chances of yours standing out decreases too as you ’re   trying to get to the top of a larger and larger pile . 

 Differing Levels Of Understanding 

 As data has spread throughout society one of the elements that has become evident is that there is a   huge variation in the levels of understanding . This could even be in a high powered business setting ,   where people who are used to seeing basic excel graphs do not understand anything more complex .   The idea of interactivity within visualized data is not something they would ever feel necessary .   However , there are others who would benefit from more complex visualizations , where they can see   as much as possible in as smaller space as they can , through interactive design or just more complex   features . 

 Technical Skills 

 Technical skills to first understand and translate the data then create visualizations around the   results . We already have a shortage of data scientists and people who can feed the right data to the right   people , so this is going to be a key challenge for the creation of decent data visualizations that can   pinpoint important data . 

 What is Data Visualization 

 A data visualization ( often referred to as a chart or graph ) is a graphical representation of data . Its goal   is to convey information in a clear and succinct format . 

 Data visualization is as much an art as it is a science . Selecting the right type of chart and adding   features that will enhance the visualization while keeping it readable can be quite challenging . 

 Selection of Data Visualization 

 There are many of types of charts that are easily available in most data visualization products . The   common chart that are used 

 • Line chart   • Column chart   • Bar chart   • Pie chart    • Stacked Bar chart   • Scatter plot   • Box Plot 

 Application of Data Visualization 

 Data Visualization Application enables users to visualize data , draw insights and understand it   better . It allows people to organize and present information intuitively . People can understand   pictures better than tables that contain rows and columns . By visualizing data , you are able to   ask more questions and quickly find answers . You can combine visualizations into a dashboard .   Dashboards are useful because they allows you to relate different views of information visually .      1.Tableau   Tableau is a business intelligence app that is among the leading software when it comes to data   visualization . It is quite straightforward in using , thanks to its intuitive drag and drop   functionality .     2.Roambi   It is a mobile - based website application for analyzing and visualizing data that revolutionizes   the way users leverage business intelligence . 

 3 Qlik   Data analysis is essential when it comes to improving your enterprise . With Qlik , you can   visualize any information you have , and thus , analyze it faster . It enables you to create   interactive reports and dashboards with stunning graphical and chart displays .     4.Salesforce Einstein Analytics   Initially developed for mobile , Salesforce Einstein Analytics can now work on smartwatches .   It enables you to leverage data and develop readable charts , images and graphical depictions of   any information you have . This application shines when it comes to assisting users in   comprehending their enterprises without the need for a background in analysis .     5.HighCharts   Highcharts is an excellent tool , particularly if you know JavaScript . The reason for this is that   its library is written entirely in JavaScript and leverages various formats to display charts on   different browsers and smart gadgets . It can process JSON data on the go and represent it in   diagrams as per the preference of the user .       Insights through data visualization     Data visualization is capable of producing significant levels of insight , provided that said data   is extracted in a clear and non - convoluted manner . Such insights can be used to delve deeper   into data sets , and have the ability to extract actionable information for businesses and clients   alike . For example , if an organization has been found to be operating at a loss , it would be wise   to draw on data to identify where changes can be made .     Approach to data visualization     Approach to data visualization mainly depends on your goals and audience . To present the   information engagingly and make viewers stick around , you should go with an infographic .      Meanwhile , if your audience is a board of busy people , you should use a pie or a bar chart –   this way , they 'll be able to understand the information quickly . With that said , you should get   to know your audience first , then decide on the data visualization technique . 


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 

 Visualizing always challenges our community of designers , coders , and developers to take on the   pressing issues of our day . Each data visualization challenge involves creators working from the same   data set to compete for unique prizes . Data visualization has changed our society considerably . These   are some of the challenges faced in today ’s world 

 VR 

 Virtual reality is going to have a huge impact on the potential for data visualizations , allowing people   to interact with data in the third dimension for the first time . 

 AR 

 Augmented reality may well be the single biggest change that we are going to see regarding the use of   data visualizations . 

 The challenge that data visualization is going to have is that those creating them need to make sure   they are doing so in an understandable and non - obtrusive way . It creates a new dynamic , where the   data overlaid needs to be clear , concise and not distracting . It ’s a fine line to balance on and a real   challenge for those who are used to creating traditional visualizations . 

 Development 

 VR and AR are likely to be interesting technologies in the future , but for the time being , we are still   going to be consuming the majority of our data through traditional 2D screens . As the number of data   visualizations increases in almost every area , the chances of yours standing out decreases too as you ’re   trying to get to the top of a larger and larger pile . 

 Differing Levels Of Understanding 

 As data has spread throughout society one of the elements that has become evident is that there is a   huge variation in the levels of understanding . This could even be in a high powered business setting ,   where people who are used to seeing basic excel graphs do not understand anything more complex .   The idea of interactivity within visualized data is not something they would ever feel necessary .   However , there are others who would benefit from more complex visualizations , where they can see   as much as possible in as smaller space as they can , through interactive design or just more complex   features . 

 Technical Skills 

 Technical skills to first understand and translate the data then create visualizations around the   results . We already have a shortage of data scientists and people who can feed the right data to the right   people , so this is going to be a key challenge for the creation of decent data visualizations that can   pinpoint important data . 

 What is Data Visualization 

 A data visualization ( often referred to as a chart or graph ) is a graphical representation of data . Its goal   is to convey information in a clear and succinct format . 

 Data visualization is as much an art as it is a science . Selecting the right type of chart and adding   features that will enhance the visualization while keeping it readable can be quite challenging . 

 Selection of Data Visualization 

 There are many of types of charts that are easily available in most data visualization products . The   common chart that are used 

 • Line chart   • Column chart   • Bar chart   • Pie chart    • Stacked Bar chart   • Scatter plot   • Box Plot 

 Application of Data Visualization 

 Data Visualization Application enables users to visualize data , draw insights and understand it   better . It allows people to organize and present information intuitively . People can understand   pictures better than tables that contain rows and columns . By visualizing data , you are able to   ask more questions and quickly find answers . You can combine visualizations into a dashboard .   Dashboards are useful because they allows you to relate different views of information visually .      1.Tableau   Tableau is a business intelligence app that is among the leading software when it comes to data   visualization . It is quite straightforward in using , thanks to its intuitive drag and drop   functionality .     2.Roambi   It is a mobile - based website application for analyzing and visualizing data that revolutionizes   the way users leverage business intelligence . 

 3 Qlik   Data analysis is essential when it comes to improving your enterprise . With Qlik , you can   visualize any information you have , and thus , analyze it faster . It enables you to create   interactive reports and dashboards with stunning graphical and chart displays .     4.Salesforce Einstein Analytics   Initially developed for mobile , Salesforce Einstein Analytics can now work on smartwatches .   It enables you to leverage data and develop readable charts , images and graphical depictions of   any information you have . This application shines when it comes to assisting users in   comprehending their enterprises without the need for a background in analysis .     5.HighCharts   Highcharts is an excellent tool , particularly if you know JavaScript . The reason for this is that   its library is written entirely in JavaScript and leverages various formats to display charts on   different browsers and smart gadgets . It can process JSON data on the go and represent it in   diagrams as per the preference of the user .       Insights through data visualization     Data visualization is capable of producing significant levels of insight , provided that said data   is extracted in a clear and non - convoluted manner . Such insights can be used to delve deeper   into data sets , and have the ability to extract actionable information for businesses and clients   alike . For example , if an organization has been found to be operating at a loss , it would be wise   to draw on data to identify where changes can be made .     Approach to data visualization     Approach to data visualization mainly depends on your goals and audience . To present the   information engagingly and make viewers stick around , you should go with an infographic .      Meanwhile , if your audience is a board of busy people , you should use a pie or a bar chart –   this way , they 'll be able to understand the information quickly . With that said , you should get   to know your audience first , then decide on the data visualization technique .
### Output: 