Keywords: Getting started, data visualization, data overview

It's usually a good idea to get familiar with a dataset before starting to work with it.

In Dcipher Analytics, we do this by dragging-and-dropping fields of interest – or the entire dataset – to different workbenches to get an overview of what they contain. Doing so aggregates and visualizes the data in ways defined by each workbench.

Example: Quick overview of 10,000 tweets

In this example, the dataset contains 10,000 tweets about sustainability. We open three different workbenches – a Table View, a Bar Chart View, and a Bubble View.

By dragging the dataset to the Table View, we get an Excel-like overview of the different columns in the dataset. But while traditional spreadsheets require tabular data, in Dcipher we can easily navigate between the different levels of this nested dataset.

We use the Bar Chart View to aggregate and view the hashtags in the dataset, which gives a quick overview of the dominant topics in the posts.

By dragging our "cities" field to the Bubble View, we are provided an overview of the cities that the tweets originate from. Coloring the bubbles by the "country" field helps to visually group cities by country.

Through a few simple drag-and-drops, we now already have an initial understanding of the content of the dataset through fast aggregations of the data.

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