By: Siddharth Mehta
Overview
Reporting data in the most visually intuitive way is one of the most interesting branches of analytics. Displaying data on the report is equal to dumping data on the report. Organizing data on the report using the most appropriate visualizations to bring out the intended analysis in the most appealing manner to the human eye is the actual essence of visual intelligence. In this chapter, we are going to briefly discuss visualizations.
Explanation
Bar charts, column charts, pie charts, etc. are examples of some of the most commonly used visualizations in day-to-day reports. With the advancement of more complex systems, varied nature of data, increasing volume of data, and number of innovative visualizations available today, the reporting process has become highly sophisticated. Visualizations can be of different types like charts, graphs, maps, gauges, indicators, trend-lines, infographics, etc. Each type of visualization is aimed at a particular nature of data for a particular kind of analysis. For example, a scatter-plot graph can be used to plot large number of data points on a graph for correlation analysis. But if the same data is placed on a pie chart, neither the data can be accommodated such that it remains visible, nor the intended analysis would be evident to the user.
Below mentioned are some of goals of using a visualization:
- To represent a large volume of data that cannot be displayed in a tabular format using rows and columns
- To visually bring out trends and patterns that can't be analyzed without a graphical representation
- To statistically analyze data in a visual manner
- To enable a user to visually understand the value and position of the data points in the entire data ecosystem
Summary
Developing a Business Intelligence (BI) solution is a set of parallel and co-related tasks. Each layer of the solution is required to work accurately and integrate with the corresponding layers. Without a harmonious functioning of each layer, a BI solution can derive incorrect analytics which can be extremely harmful to the users using this data to make business decisions.
We started with a small business scenario and used the example to navigate through different layers of the BI solution process. Being new to BI projects, you have a wide range of areas to choose from where you can develop deep skills and build your expertise. You can start your learning path from any of the BI practice areas. Eventually as you gain experience, you may have to work with different areas of the BI solution architecture. I hope this tutorial provided the launching pad for enthusiasts who wish to understand the overall landscape of Business Intelligence using Microsoft tools and start their journey in the BI world.
