#assignment 3 Data Visualization

Data Visualization

Data visualization is a general term that describes any effort to help people understand the significance of data by placing it in a visual context. Patterns, trends and correlations that might go undetected in text-based data can be exposed and recognized easier with data visualization software.

Today's data visualization tools go beyond the standard charts and graphs used in Microsoft Excel spreadsheets, displaying data in more sophisticated ways such as infographics, dials and gauges, geographic maps, sparklines, heat maps, and detailed bar, pie and fever charts. The images may include interactive capabilities, enabling users to manipulate them or drill into the data for querying and analysis. Indicators designed to alert users when data has been updated or predefined conditions occur can also be included.

Importance of data visualization

Data visualization has become the de facto standard for modern business intelligence (BI). The success of the two leading vendors in the BI space, Tableau and Qlik -- both of which heavily emphasize visualization -- has moved other vendors toward a more visual approach in their software. Virtually all BI software has strong data visualization functionality.

Data visualization tools have been important in democratizing data and analytics and making data-driven insights available to workers throughout an organization. They are typically easier to operate than traditional statistical analysis software or earlier versions of BI software. This has led to a rise in lines of business implementing data visualization tools on their own, without support from IT.

Data visualization software also plays an important role in big data and advanced analytics projects. As businesses accumulated massive troves of data during the early years of the big data trend, they needed a way to quickly and easily get an overview of their data. Visualization tools were a natural fit.

Visualization is central to advanced analytics for similar reasons. When a data scientist is writing advanced predictive analytics or machine learning algorithms, it becomes important to visualize the outputs to monitor results and ensure that models are performing as intended. This is because visualizations of complex algorithms are generally easier to interpret than numerical outputs

his is the video about data visualization :

Based on the video above, there are many type of application for data visualization.

I tried one of the data visualization that was gapminder from gapminder.org.

Here when i try the tools from gapminder.org

First, open gapminder.org. Look for the tools same like picture below

Second, after you click the tools the page should be like this 

Third, you can start to look for some information that you want, like: Income, Economy, CO2, and etc, by clicking the size 

I try to look for the income per person and also you can change the region or click search to look for the region you want

I look for data income per person for Indonesia

And the data show about income per person in Indonesia per year is 10.5 GDP/capita in $/ year in 2015.

The conclusion is with this tools we can see many things that we can look about data visualization in this world. Even this site rarely update the information like now, we can only see data for 2015 and the past.