We live in a world where is a lot of data and we may even think that there is too much data.
There are a few signs that there's too much data. There are more and more of them, it is difficult to analyze, process or draw conclusions from them, which is why it is so important to be able to present them in a proper way.
In 2000, when the telescope was launched in New Mexico, more data was collected than in the entire history of astronomy, and today more or less the same amount of data is collected every few weeks.
Walmart has 20,000 stores worldwide in 70 countries and processes 2.5 petabytes of customer data every hour. For comparison, 1.5 PT is 10 billion Facebook photos.
This is an unprecedented amount of data in the past.
It seems that we live in a world ruled by the need to collect data. This is what the economy of the modern world is based on. Each of us "produces" data, each of us has a phone in his pocket, where applications are installed, which send further information about the user. Actually, the data has become a new currency. How many times have you met with the situation that you got something "for free", only for providing your data? Promotions to set up a bank account, permission to receive marketing materials such as e-books, applications - Facebook, search engine and Google tools.
Data is a new business.
From such a huge amount of information, the art is to select the most important data, invest time and human resources and do it in such a way as to interest the audience.
If you want your Facebook post to have record-breaking results - what do you do? You add catchy, attractive graphics. This works the same way with reports. Good visualization attracts attention, is easier to understand, and helps you reach your audience quickly. With dashboards and graphics adjust to target-group, even huge data can be clear and understandable. Why?
Because most people are visual. So if you want your meetings with colleagues to be effective and your customers to understand your data better and faster, you should turn boring charts into eye-catching graphics. Here are some interesting numbers that confirm the importance of visualization:
Proper visualization of data also provides many benefits for your company:
With this influx of data, visual communication can be helpful and become a key aspect to attract and retain users for longer, or help stakeholders to understand and learn from the data presented - and this problem will be discussed in this article.
The biggest problem in visualization of data is not, surprisingly, the selection of the wrong tool, lack of skills, but more prosaic thing of a strategic nature - the lack of orientation on the end user, results in the fact that visualizations are often done automatically, without thinking whether the recipient, for whom the graphic representation is made - will understand the presented results and whether, above all, it will not take him more time than if the data were in the status quo.
This often results in a "mesh" of data when we want to present more data than the human brain can quickly and effectively analyze. Examples of how to NOT do visualization:
Completely incorrect proportions of data
Obvious manipulation of scale/proportion
3D charts work well very rarely...
In order not to make such mistakes, I suggest you stick to the following (often forgotten) basic questions to make a proper mindset for your next data visualization challenge.
Three simple criteria. Good visualization should have:
Story (functional and at the same time engaging [storytelling] content)
Adjusted form (Design adapted to the target person e.g. weekly report - simple charts/presentation aimed at evoking emotions - artistic charts)
Values (consistency of information showing solution)
Bad visualization means:
Lack of functionality (effect - uselessness)
Lack of appropriate form (effect - misunderstanding)
Inconsistency (possible consequence - potential manipulation)
A perfect example of a data visualization that combines all the necessary ingredients of an effective and engaging piece: it uses colour to easily distinguish trends; it allows the viewer to get a global sense of the data; it engages users by allowing them to interact with the piece, and it is surprisingly simple to understand in a single glance.
This example tells the story of every known drone attack (obviously not controlled by AI...) and the victims in Pakistan. By sorting the information, the dramatic facts were presented in an easy to understand visual format.
This visualization shows 100 years of the evolution of rock in a single page. Not only does it simplify information for you, but also provides actual audio samples for each genre, from electronic blues to dark metal.
The goal of this insightful interactive piece by Nikon is to give users a sense of the size of objects, both big and small, by using comparisons. Next to the Milky way, for example, a common object such as a ball or a car seem smaller than we ever imagined.
An ideal example for presentations e.g. of the board of directors. The aim is to create a chart that shows the average price per carat of a diamond over five years. What should be done to attract attention, increase the memorization of the information, and perhaps even affect further decisions such as entering a specific market? Add the context - "Diamonds WERE a girl's best friend".
It depends. Data visualization is a form of communication used in various fields, e.g. science, business, journalism etc.
Therefore, everything depends on the purpose of presenting data, the level of advancement of visualization and your experience with a particular program.
If you are just beginning with data visualization or simply lack an idea for a proper graph, then visit the website - https://datavizproject.com
To select the right tool, you need to specify an (often contradictory) objective:
- Analysis or presentation? - Do you want to research data (R, Python) or build visualizations for e.g. a client (D3.js, Illustrator) or maybe something in between (Tableau, Ggvis, Plotly)?
- Changes - Will you change your data while doing the visualization? In Illustrator you have to start building your chart from the beginning when you change/add value. In D3.js you can change the data in an external location and update the database by re-importing. In Plotly and Lyra - just import the database once and you can freely change it in the tool without losing a lot of valuable time.
- Basic or unusual chart types? You need standard "bar" or "line" charts (Excel, Highcharts); or maybe more original? (D3.js). If you don't know how to code, then the solution to the second situation may be the Lyra application, where you can change any element without entering even a single line of code.
- Interactivity vs. static: You need to create interactive graphics e.g. for a website (D3.js, Highcharts) or maybe you just need static graphics in PDF/SVG/PNG format (R, Illustrator).
"There are no perfect tools for everything, there are only good tools for people with specific goals."
The tools should be tailored to a specific need (blue - software libraries, red - programs).
Free - Google Fusion Tables (a great tool for presenting geographical data, unfortunately, Google is cancelling its support for this program on December 3, 2019), Tableau Public (easy to use - often used by us to present e.g. sales data)
Paid - Sisense (simple interface - huge possibilities --> definitely worth recommending)
...and many others depending on need.
Do you have a small/medium enterprise and are interested in how new technologies such as Big Data can increase your competitiveness on the market? Maybe the online shop is such a company - if so, we recently wrote about Big Data solutions in eCommerce.
Or would you like to know more about the 10 most popular Big Data applications?
Whatever your needs, we are always happy to talk to you about the opportunities and challenges for the implementation of Big Data in your company.
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