Data visualization: what it is, how it works and what it is used for

The exponential growth of data has made the process of their use for the extraction of strategic information increasingly complex. In a sea of ​​numbers and statistics, Data Visualization stands as a beacon of clarity, transforming raw data into captivating and intuitive visual representations.

This discipline combines the art of design with data science to create a bridge between information and understanding. Through graphs, charts and infographics, Data Visualization reveals hidden patterns, highlights crucial trends and communicates complex information clearly and effectively. In a world where data is the new gold, Data Visualization is the key to unlocking its true potential drive informed decisions.

Tool come Connecteed they can prove fundamental in the preliminary data preparation phase, crucial for any subsequent analysis step.

 

Data Visualization: what is it

Data Visualization is the art and science of representing data in a graphical format to facilitate understanding and interpretation. It involves the use of visual elements such as graphs, diagrams, maps and infographics to communicate complex information clearly and concisely.

Data Visualization aims to exploit the perceptual capabilities of the human visual system, allowing users to quickly grasp patterns, trends and anomalies in data. By transforming raw data into intuitive visual representations, this discipline makes a informed decision making, reveals hidden information and promotes effective and direct communication within organizations and with the general public.
 

Data Visualization: how it works

The Data Visualization process involves a series of steps to transform raw data into data representations strong communicative content.

Here is an overview of the key steps involved in Data Visualization:
 

1. data collection and preparation

The first step in Data Visualization is to collect data from various sources and prepare it for analysis. This involves cleaning, dealing with missing values, transforming and integrating multiple datasets. The goal is to ensure that the information is accurate, complete and in a format suitable for viewing. Tools like Connecteed can simplify this process by automating data aggregation, cleansing, and transformation.
 

2. Data exploration and analysis

Once the data has been prepared, the next step is to explore and analyze it to identify meaningful patterns, trends and relationships. This involves applying statistical and data mining techniques to uncover information and trends of interest. Interactive visualization tools allow users to drill down into data, filter and segment information, and identify areas of interest for further investigation.
 

3. Selection of display type

Choosing the appropriate type of visualization is crucial to effectively communicate information. Different data types and communication objectives require different visualization approaches. For example, line charts are good for showing trends over time, bar charts are good for comparing categories, while scatter plots are useful for identifying correlations between variables. Selecting the right display type ensures the message is clear and the impact is maximized.
 

4. Design and create the visualization

Once you've selected your visualization type, the next step is to design and create the visualization itself. This involves choosing colors, layouts, labels, and other design elements to create an eye-catching, easy-to-understand display. Visual design principles, such as the use of color, hierarchy, and composition, are applied to ensure that the visualization is aesthetically pleasing and effectively conveys information.
 

5. Communication and sharing

The ultimate goal of Data Visualization is to communicate information and facilitate its understanding. Once the visualization is created, it is important to share it with the target audience effectively. This could involve integrating the resulting graphs into dashboards, reports or presentations in slide format. Adding context, explanations and narratives based on the data-storytelling technique can help users interpret and draw meaningful conclusions from the data collected.
 

Data Visualization a cosa serve

Data Visualization plays a crucial role in transforming raw data into actionable and usable information. Here are some of the main advantages and purposes of Data Visualization:

1. effective communication of information
   Data Visualization allows you to communicate complex information in a clear and concise way. By harnessing the power of visuals, it makes data more accessible and understandable to a wider audience, even those without a technical background.
    

2. Identifying patterns and trends
   Data Visualization helps identify patterns, trends and relationships in data that may not be immediately apparent in tabular format. By visually highlighting these patterns, it allows users to draw meaningful insights and make data-driven decisions.
    

3. Data exploration and analysis
   Interactive Data Visualization tools allow users to explore and analyze data dynamically. Through filters, drill-downs, and zoom capabilities, users can delve into specific areas of interest, ask and answer questions, and uncover hidden insights in the data.
    

4. Support for decision making
   Data Visualization provides a basis for informed decision making. By presenting data in an easily understandable visual format, it allows decision makers to quickly grasp key information, evaluate options and make evidence-based decisions.
    

5. Collaboration and knowledge sharing
   Data Visualization facilitates collaboration and knowledge sharing within organizations. Data visualizations can be shared and discussed between teams, promoting a shared understanding of information and aligning efforts toward common goals.
    

Connecteed as a tool for Data Visualization

While Connecteed is not a data visualization tool per se, it plays a vital role in theirspreparation for viewing. Connecteed is a powerful feed management platform that simplifies the process of aggregating, cleaning and transforming data from different sources.

With Connecteed, users can easily connect various sources, such as databases, APIs, and files, and merge data into onesingle centralized repository. The platform offers data cleansing capabilities to address issues such as missing values, inconsistencies and duplicates, ensuring high-quality information for visualization.

The platform allows users to transform and manipulate data using predefined business rules and logic. Other possibilities include aggregating information, calculating metrics and KPIs, and converting file formats. These transformations convert the data into a foptimal format for viewing, simplifying the process of creating informative charts and dashboards.

Once data has been prepared and transformed, Connecteed allows for easy sharing and integration with more specialized data visualization tools. The platform cangenerate data feeds in various formats, such as CSV or XML, and publish them to public or password-protected URLs. These feeds can then be imported directly into multiple data visualization tools, enabling a seamless workflow from data preparation to visual analysis.
 

Connecteed per la data visualization: Put the professional feed manager to the test by activating the Free Demo

Data Visualization has become oneessential competence in the data-driven digital age.

By transforming raw data into compelling visual representations, it enables organizations to unlock the true potential of their data assets. Through a systematic process involving the collection, preparation, analysis and design of data, Data Visualization deliversimmediate, direct It iscomplete the acquisition of complex information even for audiences with any level of expertise.

Test Connecteed: activate your Free Demo now or contact Customer Service for more information.