Research Article on data visualization for business analytics and data science
What is data visualization and why is it important
Data visualization architecture for enterprise data analytics – explain architecture here
Data visualization cycle/process
Data Visualization types- explain- make a table and explain what are these and why they are useful: 1) Pie chart 2) T sne algorithm 3) bar chart 4) Waterfall plot 5) Clustering algorithm 6) another type 7) another type 8) another type
Sample Solution
Research Article on data visualization for business analytics and data science Data visualization is the representation of data or information in a graph, chart, or other visual format. It communicates relationships of the data with images. This is important because it allows trends and patterns to be more easily seen. Research shows that we create 2.5 quintillion bytes of data every single day. What types of data visualization do you use to properly digest all of that data? Some of the most common types of data visualization chart and graph formats include: column chart, bar graph, stacked bar graph, area chart, dual axis chart, line graph, mekko chart, and pie chart. While all of them serve to expedite and improve data interpretation, not all are appropriate for the same job. Choosing the right visual aid is the key to preventing user confusion and making sure your analysis is accurate.- The appropriate basis for decision making
- The types of data to use in decision-making and, by implication, the types of data not to use.
- Alternative courses of actions are identified.
- Estimating is made of the results of each alternative.
- Preferred courses of actions are chosen in terms of business objectives.
- Actual results are compared with corresponding estimates.
- New course of action are identified.