What’s data visualization? – definition, best practices, and examples | ELITPEDIA

14 August 2020

Data visualization is a graphical representation of numeric values by creating images that illustrate the relationship between the presented data. Data presented graphically are usually easier to digest by a potential recipient than a text description.

Thanks to data visualization, we can quickly reach the information we are interested in about the world, economy, specific company, or its weekly sales results. With easy access to information, we can make faster and more accurate decisions, which may become the source of our competitive advantage.

In today’s world, where we have a multitude of data, the challenge is not to obtain it, but to draw the right conclusions or communicate it properly to the final audience.

Basic data visualization toolbox

To visualize data, we need certain tools that will enable us to do so. There are plenty of them to choose from, but the most popular are:

  • Line charts
  • Column charts
  • XY charts
  • Numbers
  • Tables.

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Purpose of data visualization

What is data visualization for at all? Certainly, we could stay in Excel spreadsheets, tables, data warehouses, extract this data in SQL, and read it.

Data visualization improves the entire process of information processing, finding relationships, drawing conclusions, and presenting them to end recipients.

In the media space, “data-driven organizations” are increasingly being talked about. For an organization to be data-driven, it must have a process of efficient information transmission at every level, and for this purpose, data visualization is essential.

Data visualization means that, in principle, every employee involved in the information exchange process within the organization can understand the presented data, which cannot be said about raw data – graphically unprocessed.

What does the data visualization process begin with?

Many people believe that the data visualization process starts with data, i.e., we should have it extracted, systematized, analyzed, and interpreted. However, Paulina Sanak-Listwan from Elitmind, an expert in data visualization, is convinced that this process should be reversed and started with the user’s final analysis to whom our data is to be delivered.

The final recipient knows best what he or she is looking for and what information he/she needs. Maybe it is not always easy to verbalize expectations precisely. Hence, it is worth focusing on it first and arranges a meeting in which the final recipient will accurately outline his/her needs for the provided data.

Person and report types

We often report not to one person, but a group of people. These can include analysts, suppliers, managers, service professionals, traders, partners, financial controllers, departmental directors, or board members. Each of these people has its requirements and different goals.

With a single dataset, we are able to create separate reports and visualizations, dedicated to the group of recipients or even to individual recipients.

The most common types of reports delivered to end-users are:

  • Management report – mainly for the board, strategic, and planning objectives.
  • Analytical report – primarily for middle-level employees, analysts, and managers. These reports generally contain more detailed information than management reports.
  • Operational report – provides information on the quality of the current ongoing processes in the organization.

What are the most common data presentation topics?

End-users of our reports and visualizations most often look for specific and measurable information. They can be defined as follows:

  • Changes over time – trends, time series, cycles.
  • Elements of the whole – how the categories contribute to the revenue.
  • Correlations – the effect of one variable on another.
  • Relationships – the most profitable and least profitable products/services.
  • Cross-category comparison – a breakdown of sales regions.

Data Visualization Software

We present the ten most popular data visualization software, in our opinion. The list is open, so feel free to comment and share your experiences.

  1. Domo
  2. Klipfolio
  3. Looker
  4. Microsoft Power BI
  5. Periscope Data
  6. Qlikview
  7. Reveal
  8. Sisense
  9. Tableau
  10. Zoho Analytics.

Summary and takeaways

Every organization needs effective communication, and raw numbers cannot always be interpreted quickly and unequivocally. Data visualization makes the company’s employees share information much more efficiently, so they can perform their duties even more effectively.

After presenting the data in a visual form, you can see patterns, regularities, and correlations that might otherwise be overlooked.

Interactive reports, charts, active dashboards, graphs, and other visual objects help you quickly and efficiently discover the truth hidden in raw numbers, which can then be turned into key business information to improve decision-making processes.

The leader of the data visualization platform for analytics and Business Intelligence applications, according to the Gartner Magic Quadrant in 2020, is Microsoft Power BI. It is also one of the most used data visualization software as a service in the world.

Efficient and precise data exchange can become a competitive advantage of any business, and that is why the role of data visualization is becoming more and more important nowadays.

Check our Microsoft Power BI course with data visualization module!