How to use data visualization in BI?
In simple words, data could be extracted from different sources like excel, CSV, WEB, etc and then the data is transformed. after the transformation, the data is loaded and finally it can be visualized. Transforming basically includes removal of unnecessary data and shaping of the data.
For instance, the company has data sets, which are imported in the power BI tool, the data is then transformed and finally loaded for visualization.
- Scheduling : It basically means to arrange a particular event in the given period of time. Data visualization helps easy scheduling which can save time and help to organize an efficient event.
- Easier analysis :Due to simplification of the data using data visualizing techniques, the analysis becomes easier.
- Better understanding of trends :To run a business, it is important to know the latest trends and the demands. hence, data visualization is very helpful to understand the trends.
- Network examination :Systematic determination of analyzed data to know the merits, worth and significance of any subject.
- Changes easily detectable :As we can study the trends easily, we can also detect the changes in them easily.
- Frequency is determined easily :The frequency of a particular subject can be determined using visuals.
- The value and risk is calculated precisely :The visuals can also calculate and determine the risk which is very essential to know, for any business.
Data Visualization for Business
It is the portrayal of any data in the form of chart, graphs, images, examples etc. It is used not only in one sector but in many sectors. Due to an increase in statistical data, visual representation of that data is appreciated rather than going through spreadsheets. It is easy to understand as well as it saves time which is of utmost importance. The trends can be easily identified and studied in a graphical representation. Data visualization is mostly used for business analytics. For almost every business, data visualization is used, because they have large data. For the analysis of the data, visuals are the most efficient.
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