Data visualization is all about how you present your data, to the right audience and organization, at the right time. Data visualization is important to make them understand the most of the informative insights effectively.
Specifically, “Beautiful Visualization” explores the process of storytelling with data, communicating with data through using visual indicators such as color, themes, graphs, charts, tables, and researches the methods to put it all together on a dashboard.
Data Visualization Definition
Data Visualization is the presentation of data into various pictorial formats in a very attractive and effective manner to reveal complex information from the raw data at a glance. Successful visualizations are beautiful not only for their attractive design but also for elegant layers of detail that efficiently generate insight and new understanding.
Data visualization is both an art as well as the science of data. With a different perspective, people view it as an informative, descriptive presentation of data or the development of the individual and organization.
The success of any visual, which is beautiful, depends on the logic behind it. That, as well as the visual’s ability to provide brief access to information through the insights to the users. All that with the goal for the user to gain the information, visuals that do not achieve the goal of providing an accessible way to see and understand trends, outliers, and patterns in data have failed. At the end of the day, it’s because accessibility is the most important factor in determining overall success. The ability to convey information must be the primary driver of the design of a visual.
A beautiful visualization has a clear objective, message, or detail. Or, it offers a particular perspective on the information, designed in order to convey a message to the audience. Reports should be as possible as easy to understand the data without any hassle and complexity.
The keys to achieving the beauty of visualization are to focus on keeping the visuals
- Data-oriented, and
That can reduce the complexity of raw data after visualization.
Human brains process the colors and the visuals in a pictorial format much better in the context of written text data, even before we are fully aware of it. Consequently, charts or graphs used to visualize large amounts of complex data are easier than reading simple data.
There are paid and free open source types of Business Intelligence tools present in the market. Paid tools like Microsoft Power BI, Tableau, QlikView, Qliksense, Klipfolio, and free and open-source tools like Google Data Studio, and Google Sheets.
Free tools have limited visualization features and connections. You can select any of your choices. Finally, before buying, you can try the trial periods, and then further, you can decide which satisfies your BI purposes best.
Business Intelligence Tools
BI tools provide you with a variety of features and functionality. However, distinguishing and filtering data can be done using the inbuilt visuals. Also, the custom visuals features, like charts, plots, graphs, matrix, and tables can be used to fetch the information statistically correct.
The much more improved data now can give you improved sight as well as makes it easy for faster decision making for various and important industries.
Microsoft Power BI
As we have different clients associated with our Loginworks data team, most of our clients like Microsoft Power BI more. The reason behind it is that it is affordable and relatively inexpensive compared to other tools. The Power BI Desktop version provided by Microsoft is free of any cost. You can download and start using it to make reports and dashboards on your computer. You have to buy the paid version of Power BI Pro to publish the report on the Power BI service workspace or to share the dashboard with others. The Power BI Pro version will cost $9.99/user/month.
Data Analysis Expression (DAX)
The drag and drop functionality makes it easy to learn and create the report. Data manipulation and Data modeling can be done with ease with the Data Analysis Expressions (DAX) functionality of Power BI. These expressions are the collection and combination of functions, operators, and constants, and they are used as one formula to give the final result. In a similar manner, the DAX function is similar to Excel functions. Having said that, DAX is much more advanced. If you are aware of Excel and its functions, you can handle DAX easily.
Moreover, the main goal of data visualization is meaningfully communicating information. Data Visualization has fascinating effects on decision making. Predictive analysis, as well as sentiment analysis, can be done using data analysis.
Accordingly, various organizations use it for analyzing their advertisement or campaign data for the benefit of the organization’s business.
Scope of Data Analysis
At the dawn of the digital age, there is a lot of data present. But all the data in the world is useless if you can’t understand it. Data in the form of visuals can help you identify trends and the direction of the graphs.
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