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visualisation

Visualization of data in Redash

It is easy and handy to visualize the information in Redash, and in this post I will review the examples of data display on various charts. All the examples can be found in time series, constructed based on the data for each month.
Since I am all for analytics, along with graphs we will be exploring useful business indicators. Let’s start with quite a traditional metric for retail/e-commerce AOV (Average Order Value) – the average order value (in this case, for one month). The indicator allows to track changes, connected to consumer behaviour (whether they started buying less or more on average).

Example of a bar chart in Redash on the basis of AOV (Average Order Value) indicator

In terms of bar chart display, everything is pretty common, but handy – there is an opportunity to manage the colours of the chart, data labelling, format of data labelling (remove or display the data after comma).
Oftentimes, dynamics is much more evident, if looking either at traditional chart or at so-called area-chart. In this case, we are exploring new users’ dynamics, as well as which part of MAU (Monthly Active Users) belongs to new users.

This is a stacked chart – meaning that data of 2 rows are summarized, and one is shown above another.

In this example our chart is as informative as possible – we make one understand, which share belongs to new users, and, by stacking, we showcase the number of active users per month (in essence, killing two birds with one stone).
Actually, we could present the data in a slightly different way. For example, mix of various chart types is quite popular. Let’s imagine that MAU is represented by a bar chart (green on the chart), and the share of new users from MAU by red line, that is on an auxiliary (right) axis.

Two types of charts on one graph.

With Redash you can make pivot tables, display funnels and cohorts, and also use maps to display geo-data.
In the next posts I will tell you about a chart for funnel construction (however, prior to that we will learn how to involve google analytics).

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