Why is Color so important in data visualization?

Color Data Visualization Image

The point of Data Visualization

Many business intelligence tools available today are failing to deliver actual intelligence. IT has made a great technical progress in data integration, cleansing of transformation as well as in construction of big and efficient data warehouses. Nonetheless, we think that business intelligence industry has largely ignored the fact that actual intelligence is within human beings. Therefore, raw information can only be valuable when it is understood and not just when it is available. If data is poorly represented, whole great data warehouse project was in vain.

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Source: Dashboard Insight

CRM Software: Does Visualization Matter

It may be difficult to register, but traditional CRM solutions have been around for 15-20 years (Siebel Systems was founded in 1993 and Salesforce.com in 1998). Since then, they have evolved from simple contact management solutions to sophisticated commercial databases, branching out to marketing, customer support, accounting and more.

In their development, these solutions have also migrated to the cloud which has facilitated their connection to popular web services (e.g. LinkedIn and Twitter) and complementary B2B applications. They have become enterprise platforms at the heart of a company’s internal and external processes.

What is bizarre is that the user interfaces of these solutions have remained stuck in the 1990s: tables, pie charts, report builders are commonplace, as are simple views on the central database whose only value is the raw information they contain.

The History of Data Visualization

History of Data Visualization ImageData visualization has come a long way. From simple cave drawings depicting the success of a hunt to the intricate dashboards we have today connecting to millions of rows of data. It’s always good to know where you came from in order to better understand where you are now and where you are going. Michael Friendly from York University published a paper on the milestones in the history of Data Visualization, Milestones in the History of Data Visualization: A Case Study in Statistical Historiography. The paper provides an excellent breakdown of major points that have lead us to modern day data visualization.

Prior to the 17th century, data visualization existed mainly in the realm of maps, displaying land markers, cities, roads, and resources. As the demand grew for more accurate mapping and physical measurement, better visualizations were needed.

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Source: Dashboard Insight

What is a Dashboard?

What is a dashboard Image

Defining dashboards, visual analysis tools and other data presentation media.

There are many different ideas of what a dashboard is. This article will clearly define it along with other presentation tools. In my article, What is BI – A Business Intelligence Primer, I discussed the presentation layer of the business intelligence technology stack. To reiterate, there are typically four types of presentation media: dashboards, visual analysis tools, scorecards, and reports. These are all visual representations of data that help people identify correlations, trends, outliers (anomalies), patterns, and business conditions. However, they all have their own unique attributes.

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Source: Dashboard Insight

Visualizing For The Color Blind

Data Visualization Color Blind ImageIn the world of data visualization and dashboards colors  form an integral part of telling the data story effectively. However,  not everyone has the ability to to see every color equally.  The article from Dashboard Insights talks about creating dashboards and data visualizations for the color blind.

Color blindness is a color vision deficiency which affects roughly 8% of the North American male population and 0.5% of the female population. So when designing data visualizations and dashboards, it’s important to keep this group of people in mind to make sure they are seeing the same results as everyone else.

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Source: Dashboard Insights

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50 new Tools Democratixing Data & Visualization

50 New Data Visualization Tools

Just as we’ve seen the shift to “DIY” data collection platforms, we’re also seeing the development of a whole new class of self-service data exploration and visualization tools. These are not necessarily replacements for SPSS, SAS, R, and other traditional analytical suites: those enterprise level systems are often still needed to do more complex and advanced statistical analysis. However, in many ways these newer entrants have a leg up over legacy providers: they are less expensive (in many cases free), more flexible, easier to use, and are built with the needs of a variety of users in mind. Today it’s possible to find many tools that can help the most inexperienced user quickly begin doing sophisticated analysis and produce great visualizations from many different types of data.

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Source: Dashboard Insight

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