Use of Colour in #dataviz and other useful tips via CXL Institute
In this lesson, we are going to learn about how we can intelligently use colours in our reports and visualisations so everyone can understand the data easier.
Color is an area which is important. As a ‘Data Editor’ of many organisations, I’ve also used colour well to make sure it stands out and this technique tends to work well with Social Media platforms like twitter, etc.
We are told about some data viz principles and we need to know them to create goof vizes.
Some people are color blind and we need to make charts keeping them in mind.
We need to do an Sanitary check. We also need to be aware of the interpretation of colours when using them in certain countries. This is mostly based on cultural differences.
Eg: red is seen as morning in South Africa while it is seen as Celebration in China. The below image gives us an idea of different interpretations.
Even the color green has different meanings. It is good luck in Ireland while it represents death in South America.
All of this is imp to keep in mind when we are creating our data viz so we know our audience.
In data Studios, we have options. There is a color palate to choose from.
We can also use color to point out a data point for extra attention. This has often been used by me as well in many of the charts and infographics I’ve made in the past for many Newsrooms.
It does help in drawing attention to the audience. We are also told about how important it is to keep the colours consistent for visualisation.
We are shown how we can use the options in data studio to color by series order to dimensions.
Our instructor says to use Dimensions Value as that is a better option to use. We see an example of a chart (bar) and we see a trend line chart next to it. We have some features under style > color by > dimension values.
We are told to avoid using Series Order.
Conditional Formatting: fairly recently launched feature then. So we leant how to use colours intelligently in our reports.
Post Colours, we move to DATES.
We are going to learn about how they are formatted and how we can customise date ranges, etc. We learn a good tip right at the start which is to see that the field is set up as a date within your data source. Unlike say it was set up as a String, then it won’t work very well.
Different day functions we can use. When we make a Viz, we can choose how we want to show our date.
Daily data on a dataset is often an issue. When we have hundreds of data if becomes difficult to have them plotted on a chart, and Data Studio is very picky about data formats.
If you have dashes between the year and the month and the day, or you have slashes or something like that, you may end up banging your head against the table a little bit.
But there are some weird little tweaks we can use. There is a ‘date range control’ which we can apply.
There are many more things we can do like
Fixed
Previous Year
Previous Period
Advanced
We can use hacks to move around our data and they can be useful to us to know how to sort out our data.
Filter, controls and segments
How we can filter data studies charts and tables. There are a number of different ways of doing this:
1.Report level
2. Filter Control
3. Widget/Chart level filters
4. Segments (GA)
We learn about each of these ways with some examples.
From here, we move to Calculated Fields which also is a bit long — 22 mins. Here we are learning about how to make customised metrics but it’s also a lot to take in after going through the earlier lessons which was also very long.
Blends — or joints and we are going to learn how to combine multiple data sets. We can blend upto five data joints. They are often a LEFT joint.
We are told about how we can create a Blend.
We are also told that we should name our BLENDS. Don’t call them blend 1, 2, 3 etc…that will not help.
Give it a name so we know what it is for.
We use data from the Merchandise store. We can create two charts or go directly to Blend data.
There is a lot to take in here and I am going to come back to all of this as and when I need to use this.
Changing Data Sources — this is a short lesson and we are going to learn about the source of your data and where it is coming from.
Instead of creating a new data spruce, we copy it to edit it and then that allows us to keep all the fields (duplicates it).
We learnt how to change a data source without necessarily having to go and recreated all of our dimensions and metrics that we have built on top of it.
We learn a lot more useful points. We can share our work in data studios with others by using similar google drive settings.
Owners Vs Viewers Credentials
An owner is the creator and if I give access to anyone to see the report they will be able to see the GA data even if their account doesn’t actually have access.
Viewers credentials: This will only show them data if their own Google account has access.
I like the advice given on creating reports for clients. Instructor says that if we want to end up giving access to our clients and transfer ownership to them we will not be able to do that.
This is useful to those who work with an Agency where they are handling multiple clients.
Other tips include scheduling reports, export to PDF, version history. However, there is no commenting for now but maybe they might add it later or NOT.
It ends with some cool uses of data studio like adding annotations, etc.
(This is a part of my series as a fellow with CXL institute where I am pursuing a mini degree in Analytics)
