{"id":6408,"date":"2018-08-09T15:07:35","date_gmt":"2018-08-09T19:07:35","guid":{"rendered":"https:\/\/blog.brainstation.io\/?p=6408"},"modified":"2020-05-12T12:29:59","modified_gmt":"2020-05-12T16:29:59","slug":"data-visualization-work-analytics-projects","status":"publish","type":"post","link":"https:\/\/brainstation.io\/blog\/data-visualization-work-analytics-projects","title":{"rendered":"Putting Data Visualization to Work for Your Analytics Projects"},"content":{"rendered":"

Every second, more than 65,000 search queries<\/a> are processed by Google, 8,000 tweets are posted on Twitter, and just under a thousand photos are shared on Instagram. These numbers shouldn’t be a surprise. We are being inundated by data. In fact,\u00a0<\/span>every day, 2.5 quintillion bytes of data are created<\/a>.<\/p>\n

This avalanche of numbers and information is making\u00a0the ability to analyze data increasingly important, and unsurprisingly,\u00a0Data Scientist roles have increased by 650 percent<\/a>. How will these data scientists share findings and trends? Data visualization.<\/p>\n

\"data<\/a>

Image source: tableau.com<\/p><\/div>\n

This chart shows rising global temperatures; it takes average temperatures between 1961 and 2010 as the baseline, and then compares temperatures between 1850 and 2016 to this baseline.\u00a0<\/span>Even if you didn\u2019t read the descriptions,\u00a0you probably noticed the upward trend, and\u00a0<\/span>can quickly make sense of this data. The thing is,\u00a0<\/span>there are over 100 points of information on this chart. <\/span><\/p>\n

That\u2019s the power of data visualization. It allows us to make sense of a large amount of information quickly.<\/span><\/p>\n

Data Visualization in the Visual Analytics Process<\/b><\/span><\/h3>\n

Contrary to popular belief, data visualization is not simply the last step of an analysis \u2013 there’s more to it than simply creating a quick chart for a presentation to management; it’s part of\u00a0<\/span>visual analytics.<\/span><\/p>\n

Imagine you were tasked with comparative analysis of dietary trends across 150 countries. Looking at all this data in the form of a table would take a long time. Now t<\/span>ake a look at the chart below.<\/span><\/p>\n

\"data<\/a>

Image source: tableaupublic.com<\/p><\/div>\n

This chart shows dietary trends for 150 countries over 50 years in four categories: calories, protein, fat, and food weight.\u00a0<\/span>The world average is taken as our baseline, and each country is then compared to this average.\u00a0<\/span>Analyzing this data using visual analytics techniques makes this process much more interesting and less time-consuming. <\/span><\/p>\n

Let\u2019s filter to category \u2018fat\u2019 for example.<\/span><\/p>\n

\"data<\/a>

Image source: tableaupublic.com<\/p><\/div>\n

It is easy to spot which countries have something interesting going on. Look at Canada: the consumption of fat is declining. Now look at Kuwait: here, the consumption of fat is increasing. It\u2019s probably worth diving in and looking at what\u2019s driving these trends.<\/span><\/p>\n

And that\u2019s the power of visual analytics. It allows us to use data visualization not as the final step of the analysis, when we want to share our findings with the team, but as the means to making sense of large amounts of information, quickly.<\/span><\/p>\n

Why is Data Visualization so Powerful?<\/b><\/span><\/h3>\n

A large portion of our brain is dedicated to visual processing.<\/span><\/p>\n

\"data<\/a>

Image source: olgatsubiks.com<\/p><\/div>\n

Our brains can actually process 10 billion bits of visual information per second<\/a><\/span>, which means that as soon as we see a chart, our brains start making sense of it.<\/span><\/p>\n

The large size of our visual cortex also allows us to take care of visual information in what psychologist Daniel Kahneman calls “System 1,” which is\u00a0\u201cis the brain\u2019s fast, automatic, intuitive approach.\u00a0<\/a><\/span><\/p>\n

System 2, meanwhile, is\u00a0\u00a0\u201cthe mind\u2019s slower, analytical mode, where reason dominates.\u201d<\/a><\/span><\/p>\n

\u201cSystem 1 is…more influential\u2026guiding\u2026[and]…steering System 2 to a very large extent,\u201d\u00a0Kahneman says.<\/a><\/span><\/p>\n

Being part of System 1, data visualization is more likely to result in actions and decisions than any other type of analysis.<\/span><\/p>\n

Data Visualization Is Part of Communication\u00a0<\/b><\/span><\/h3>\n

As a data scientist or a data analyst, you need to offer clear insights and trends, and then be able to communicate them effectively.<\/span><\/p>\n

In fact, the ability to communicate is what often determines the success of <\/span>analysts and data scientists. Knowledge of math and statistics, experience in coding, and even domain knowledge is not going to be sufficient to move the needle in any organization. Data scientists and analysts need to communicate their findings in a clear, concise, and easy-to-digest manner. And as you\u2019ve probably realized by now, data visualization does this best.<\/span><\/p>\n

What Skills Do You Need for Data Visualization?<\/b><\/span><\/h3>\n

A quick search on LinkedIn for \u201cdata visualization\u201d returned 9,000 jobs worldwide. I then used Python to collect job descriptions. Here’s what I found in terms of necessary skills:<\/span><\/p>\n

\"data

Image source: olgatsubiks.com<\/p><\/div>\n

Data visualization overlaps with other roles in data, including software development, data engineering, and data science. Knowledge of Tableau, a data visualization tool, is in high demand, but the use of other data visualization tools is often required as well, including Microsoft PowerBI, Qlik, MicroStrategy, and Adobe Cloud. The ability to wrangle data using SQL, and understanding of core databases such as SQL Server and Oracle can also be essential.<\/span><\/p>\n

The rapid growth of data volumes won\u2019t be slowing anytime soon. Data visualization removes barriers to data analysis. Those who can manipulate these tools will turn data visualization to their advantage and move ahead in their careers.<\/span><\/p>\n

Are you ready to harness the power of data visualization?<\/strong> Check out BrainStation\u2019s\u00a0Data Analytics course<\/span><\/a>\u00a0to get core skills and learn about data visualization.<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"

Data visualization isn’t just the last step in the data analysis process. A Data Scientist explains its increasing importance. <\/p>\n","protected":false},"author":7,"featured_media":6410,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[330],"tags":[332,331,405,542],"yoast_head":"\nPutting Data Visualization to Work for Your Analytics Projects<\/title>\n<meta name=\"description\" content=\"How do you put data visualization to work for your analytics projects? 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