Data Visualization: Everything You Need to Know When Assessing Data Visualization Skills

Data Visualization

Data visualization is the process of transforming data into visual representations, such as charts, graphs, and maps. The goal of data visualization is to make data easier to understand and interpret. Data visualization can be used to communicate complex data findings to a wide range of audiences, both technical and non-technical.

There are many different types of data visualizations, each with its own strengths and weaknesses. Some common types of data visualizations include:

Charts: Charts are a popular type of data visualization that can be used to compare different data points or to show trends over time. Common types of charts include bar charts, line charts, and pie charts.
Graphs: Graphs are another type of data visualization that can be used to show relationships between different data points. Common types of graphs include scatter plots, histograms, and box plots.
Maps: Maps can be used to visualize data that is geographically distributed. Common types of data maps include choropleth maps, heatmaps, and point maps.

Data visualization can be used for a variety of purposes, including:

Exploratory data analysis: Data visualization can be used to explore data and identify patterns and trends.
Communication: Data visualization can be used to communicate data findings to a wide range of audiences, both technical and non-technical.
Decision making: Data visualization can be used to help make informed decisions by providing insights into data patterns and trends.

Data visualization is an important skill for data professionals and other roles that require strong analytical and technical skills. By learning how to create and interpret data visualizations, data professionals can better understand data, communicate findings to others, and make informed decisions.

Here are some examples of how data visualization can be used in different industries:

Business: Data visualization can be used to track sales performance, identify customer trends, and optimize marketing campaigns.
Finance: Data visualization can be used to track stock prices, analyze market trends, and manage risk.
Healthcare: Data visualization can be used to track patient outcomes, identify disease outbreaks, and develop new treatments.
Education: Data visualization can be used to track student progress, identify areas for improvement, and develop personalized learning plans.

Data visualization is a powerful tool that can be used to communicate data findings in a clear and concise way. By learning how to create and interpret data visualizations, data professionals can better understand data and make informed decisions.

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Scott Crowe, Canva (Lead Recruiter - Data)

How can you accurately assess somebody's technical skills, like the same way across the board, right? We had devised a Tableau-based assessment. So it wasn't like a past/fail. It was kind of like, hey, what do they send us? Did they understand the data or the values that they're showing accurate? Where we'd say, hey, here's the credentials to access the data set. And it just wasn't really a scalable way to assess technical - just administering it, all of it was manual, but the whole process sucked!

Cole Brickley, Avicado (Director Data Science & Business Intelligence)

I wouldn't dream of hiring somebody in a technical role without doing that technical assessment because the number of times where I've had candidates either on paper on the CV, say, I'm a SQL expert or in an interview, saying, I'm brilliant at Excel, I'm brilliant at this. And you actually put them in front of a computer, say, do this task. And some people really struggle. So you have to have that technical assessment.

Mike Yates, The British Psychological Society (Head of Data & Analytics)

I was at WooliesX (Woolworths) and we used Alooba and it was a highly positive experience. We had a large number of candidates. At WooliesX, previously we were quite dependent on the designed test from the team leads. That was quite a manual process. We realised it would take too much time from us. The time saving is great. Even spending 15 minutes per candidate with a manual test would be huge - hours per week, but with Alooba we just see the numbers immediately.

Shen Liu, Logickube (Principal at Logickube)

We get a high flow of applicants, which leads to potentially longer lead times, causing delays in the pipelines which can lead to missing out on good candidates. Alooba supports both speed and quality. The speed to return to candidates gives us a competitive advantage. Alooba provides a higher level of confidence in the people coming through the pipeline with less time spent interviewing unqualified candidates.

Scott Crowe, Canva (Lead Recruiter - Data)

How can you accurately assess somebody's technical skills, like the same way across the board, right? We had devised a Tableau-based assessment. So it wasn't like a past/fail. It was kind of like, hey, what do they send us? Did they understand the data or the values that they're showing accurate? Where we'd say, hey, here's the credentials to access the data set. And it just wasn't really a scalable way to assess technical - just administering it, all of it was manual, but the whole process sucked!

Cole Brickley, Avicado (Director Data Science & Business Intelligence)

I wouldn't dream of hiring somebody in a technical role without doing that technical assessment because the number of times where I've had candidates either on paper on the CV, say, I'm a SQL expert or in an interview, saying, I'm brilliant at Excel, I'm brilliant at this. And you actually put them in front of a computer, say, do this task. And some people really struggle. So you have to have that technical assessment.

Mike Yates, The British Psychological Society (Head of Data & Analytics)

I was at WooliesX (Woolworths) and we used Alooba and it was a highly positive experience. We had a large number of candidates. At WooliesX, previously we were quite dependent on the designed test from the team leads. That was quite a manual process. We realised it would take too much time from us. The time saving is great. Even spending 15 minutes per candidate with a manual test would be huge - hours per week, but with Alooba we just see the numbers immediately.

Shen Liu, Logickube (Principal at Logickube)