Question

Given the volume of data surrounding us, data visualization techniques are become important for businesses. What visualization techniques do you find useful and why (e.g. histogram, line graphs, scatterplot, bar chart. etc.)? What challenges do businesses have with big data?

Answer 1

Part-1

What is data visualization?
This means when we represent the data in a graphical manner so that the data is easy to understand and the results can be visually seen in a more graphical manner. It also means that the data and results can be represented in a diagrammatic way. There are various type of Visualization Techniques:-

1. Line Graphs
2. Bar Graphs
3. Histogram
4. Line Pivot
5. Frequency Table
6. Pie Chart
7. Stem and Leaf Plot

So all the above techniques have there own areas of expertise as they picture a certain type of data well. But out of these the most used and useful technique which can be used in maximum conditions of data are:-

1. Line Graphs
2. Bar Graphs
3. Pie Chart

1. Line Graph-this is used to display continuous data and it is good in predicting future events.

2. Bar Graph-this is used to display a set of quantities and is more useful is comparing the sales of a certain period of time

3. Pie Chart- this is used to show the relationships from the whole, which means it displays the plot in a total of 100% and we can figure out the comparison of each category out of the given 100%

So each serves its own purpose we can say that the most useful visualization techniques are these 3 which may serve in all the circumstances.

Part-2

What is big data?

Any data which is very large in number and require some type of Artificial intelligence to extract meaningful data and to analyze that data in a more informative form so that the understanding of the data can be maximized is called big data.

What challenges do companies face in Big Data?

1- The biggest challenge in big data is to figure the most useful data out of a very large and complex data
2-Storing the data is also one of the major problems as the data consumes a lot of space so this is also becoming a problem for many companies
3-The data is coming on the continuous bases so a company need to figure this also what to keep and what to let go
4-Last but the most important part, the company has to validate the data which it is getting as there is no proof of the data being 100% correct.