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Data Analytics: Data analysis is the collection, transformation, and organization of data in order to draw conclusion, make predictions, and drive informed decision-making. Data analytics in the simplest terms is the science of data. It's a very broad concept that encompasses everything from the job of managing and using data to the tools and methods that data workers use each and every day.
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Data-ink:
- In the context of Data Visualization, "data-ink" refers to the amount of ink or space in a chart or graph that actually contains useful data information. This concept was introduced by Edward Tufte, a renowned expert in data visualization.
- According to Tufte, "data-ink" is a term used to describe the portion of elements in a chart that represents actual data information. In simpler terms, it is the amount of "ink" (or visual elements) used to represent real data compared to the total ink used to draw the chart.
- The goal of optimizing "data-ink" is to make the chart simple, easy to read, and keep the viewer focused on the essential information rather than being distracted by unnecessary details. This way, you can convey the message clearly and effectively.
- Examples of optimizing "data-ink" include removing unnecessary gridlines, reducing the size of labels, and minimizing non-essential details, all aimed at enhancing understanding and interaction with the data.