Visualiseringerne så super lækre ud, og BI-værktøjet virkede prisvenligt. Alligevel viste det sig ikke at være det rigtige match til din organisation og dine brugeres behov. Måske var en af grundene, at du startede med at vælge værktøj og hoppede over de grundlæggende trin, der ligger før udvælgelsen af et moderne BI-værktøj? Derfor - uanset om du er stormende forelsket i Power BI, Qlik eller Tableau, så læs lige med her, inden forelskelsen koster dig unødvendige kroner.
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Fristes du også nogle gange til at bruge lagkagediagrammer (pie charts) eller donut charts? Skal vi ikke aftale, at det slutter nu? Grunden er simpel: Øjet kan ikke aflæse vinkler og krumninger, så det er stort set umuligt at vurdere lagkagestykkernes størrelse i forhold til hinanden. Samtidig er det næsten umuligt at få overblik over de mange kategorier. Og løsningen - dén ligger lige for, nemlig et søjlediagram. Yes – det føltes godt at komme af med, men hvordan kommer du så videre?
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When hearing about governmental politics, we encounter a lot of information, some official - some from different observers and commentators. We frequently hear about internal turmoil or even crises in the government, and from time to time we see a minister leaving or switching office for one reason or another. Such changes are, of course, recorded in official annals and publications - but rarely do we take the time to actually put a visual face and pattern on this data. If we could do that, it might prompt us to ask other - perhaps more interesting - questions - and hopefully, get interesting answers. In today's post, we will use Tableau to make a little data journalistic attempt at visualizing political data.
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If you popped by this blog, chances are that you work with BI or data analysis or just find visualization of data interesting. You probably see many visualizations everyday - perhaps you even make some of them yourself. But dealing with a visualization, how do you know if it contains C.R.A.P. or the opposite? That's todays topic.
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The pie chart remains a surprisingly popular ingredient in the media and various sorts of business reports and dashboards. Do a quick Google search on 'Chart' and the menu will look something like this:
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Text is an indispensible helper when we make data visualizations, but we need to be careful not to let it steal the picture.
Quartz recently had a short article on the state of residential property prices around the world. The focus was on the wide disparities in price changes within each country between on the one hand, the national average, and on the other hand, the prices in the largest city. The article suggests that generally property prices tend to rise more in the largest city than in the given country as a whole. And that some anomalies can be spotted to that trend in recent figures - presumably the result of regional economic crises.
The article featured this visualization, making use of text, color and position.
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Remaking charts has become increasingly popular around the web lately. Good blogs such as JunkCharts, Story Telling With Data, ExcelCharts or The Functional Art all testify to this trend. It is fully understandable! Picking a visualization and working with it is a great way of learning, practising and discussing visualization techniques and generally putting your tools and skills to the test.
I teach people about data visualization - but I will always be a student myself! There is so much interesting stuff out there (yes, a lot of horrible stuff too) and the
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