Research Article on data visualization for business analytics and data science

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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

 

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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.

  1. The appropriate basis for decision making
  2. The types of data to use in decision-making and, by implication, the types of data not to use.

Decision means choices, thus decision-making implies making choices between alternatives, competing course of action. If there is no available alternative, then decision-making is not necessary. Management has to assess whether choosing a particular product X has the overall benefits or choosing an alternative, Y i.e. compare the two products, and weight up any differences between choosing on and not the other.

Management accounting is a key part in an iterative decision making process:

  • 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.

This is a continuous process.

The fundamental question for consideration here is, “How is management to choose from among these so many possible alternatives so as to maximize the present value of the expected future cash flows?” The answer to this question is indirect. Each potential alternative will have different cash consequences and change continuously with time. Therefore, analyzing the differences between available alternatives is essential to good decision-making. This analysis is called ‘differential’ or ‘incremental’ cash analysis. This basically gives managers an overlook of the advantages and disadvantages of the choice of alternatives. The final decision is to accept the alternative with the greatest net present value or cash flow, i.e. NPV

Stage 5, 6 and 7 : The decision making and control processes

Stage 5 is the forecasting stage in which it predicts the most likely outcome of a decision, expressed in a budget form. The budget is prepared on estimates of differential costs and revenues in the chosen course of action with some valid assumptions.

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