data visualization

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As we detailed in our previous blog, Data Visualization History, people have been visualizing data for centuries. The ability to visualize large complex data sets quickly and easily is relatively new. With the introduction of Microsoft Excel in 1990 rows and columns of data could be changed into a visual representation with the click of a button. Business professionals joined scientists and statisticians in producing data visualization today.

Visual data allows communication of the information to be more universal, fast and effective. Non-statisticians and non-scientists can comprehend the implications of the data through the recognition of correlations in relationships, trends over time, frequency of preferred or non-preferred results, digging into the details of the market and ability to react to changes in the market as well as measures of risk and reward. Infographics, heat maps that highlight in light or warm colors based on high value or low value, fever charts that track changing data over time, area charts that show time-series relationships and histograms are all used to produce sought-after visual information.

Application Areas for Data Visualization Today

With half of all global advertising dollars being spent online in 2020, marketers need to find out the sources of web traffic and how they are generating revenue. Politicians and their staff look at geographic maps that display the party each state or district voted for. In the 2016 Presidential election, identifying a very small subset of specific voters made the difference in a number of states. Scientists are gaining greater insight into their experimental data and healthcare has a myriad of applications like look at how mortality rates of heart disease might change over specific geographic areas. In finance they analyze price movements over time and logistics uses visual data to determine the best global shipping routes – a hot topic as we come out of the pandemic and demand has exponentially increased for products not yet off the container ships.

Uses of Data Visualization Today

BI Reporting – As companies move from spreadsheets to dashboards for executive decision making, this interactivity makes people more conversational with the data but not necessary fluent in the implications of what the representation or data are saying.

Custom Data Visualization – A statistical expert who can leverage Python or R to explain more sophisticated models to decision makers has been critical for the past few years and will only become more critical in the future.

Information Visualization – The broad reach of data visualization is in your mailbox or inbox every day. Journalists are providing news and insights publicly through data tables, graphs, maps and infographics.

Exploratory Data Analysis – This is a method for analyzing data sets to summarize their main characteristics. The business practitioner is able to do this using tools that can write SQL queries for you. More people in the organization can explore the data and ask questions which improves their data literacy and brings their expertise to the data analysis.

Interested in being part of the booming area of data visualization? Contact the Data Science and Analytics Executive Recruiters at Smith Hanley Associates: Nancy Darian, ndarian@smithhanley.com and Paul Chatlos, pchatlos@smithhanley.com.

 


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