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.

