Data Visualization with Tableau

If you are a person who is familiar with tech world, one word that would never have missed your attention is data visualization. It is one of the buzzwords in the technology space today. Just what is data visualization?

Simple: data visualization, as indicated in its name, is visualization of data. Cool enough, except that this is the literal part of the subject. There is a world to be discovered beyond the semantics of the topic. Data visualization goes far beyond text. It is the domain in which the data visualizer arranges and organizes data with the help of graphics, tables, graphs, diagrams, maps, pictures and a whole lot more visual aids.

The purpose: to change the characteristic of raw data to make it both more attractive and meaningful. Present lots of raw, cluttered data to a businessman, and you will be lucky not to have it thrown on your face. Whereas, dress the data up to make it more visually appealing, and, add meaningful insights into the data. This form is sure to be lapped up. This is what data visualization essentially is about.

Data visualization uses visual elements such as those mentioned above. The aim of data visualization is not only to beatify data, but to make sure it makes sense from a business perspective. Data visualization helps identify factors such as trends, indications, outliers, perspectives and so on, which is where the real purpose that data can serve to businesses lies.

The need for data visualization in today’s world

We are looking at data visualization as a major discipline that businesses will find indispensable in the years to come. Here is why: this is the age of Big Data, which, as we are well aware, is the oxygen for businesses. It is the fuel that runs businesses, simply because it helps businesses like perhaps nothing else.

Categories of data visualization

Data visualization is the means by which Big Data can help businesses. Towards ensuring this, data visualization uses these five categories:

Temporal: Mainly used for linear and unidimensional data. It is useful for standalone feature lines;

Hierarchical: Useful for data that is from a solo point of origin, but diverge into clusters;

Multidimensional: As the name suggests, this is the kind of data visualization that is done when there are multiple dimensions of data, usually with more than two variables;

Network: This is the way in which the connection between data in different networks is understood and displayed;

Geospatial: This form of data visualization deals with data from real-life geographical locations.

Tableau in data visualization

We have understood a few basic elements of data visualization. Like all other technologies, data visualization runs on a process. For this, it needs programming languages and tools. Tableau is one of the most important tools used in data visualization, the other being R and Python.

Now, Tableau: this is used in data visualization to help visualize data by providing the entire gamut of inputs needed for data visualization, such as graphs, charts and tables. R and Python, on the other hand, are scripting languages that take part of the technical aspects of data. This means that without Tableau, R and Python, data visualization cannot come about.

There is a great opportunity to grow in the field of Tableau!

If a reading of these facts about data visualization has fascinated you, there is more! You can now become a full-fledged professional in Tableau! Simpliv, a learning platform that offers the most comprehensive learning on all topics of interest to the human mind, has a collection of courses on Tableau!

These course are designed by leading names in the industry. They are created to suit the needs of the industry, and are certified. Most of these courses are so affordable, they are available in single digit fees! This is the best time to make the most of this learning opportunity.

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