Why Use Data Visualization in Communication


Today all companies have data. The term Big data is already mastered in most companies and they know the importance of collecting information.

However, the main flaw that makes it impossible to extract the full potential of the data comes right after it is collected: analysis. And is that the real challenge of Big data is in the interpretation of data.
To facilitate this process and to be able to display the information in a simple and understandable way, data visualization tools have been created.

These tools collect all the company's databases and display them on a single platform, allowing the team to carry out a cross-sectional analysis.

To extract knowledge and transmit messages with the data, we need to have a good data visualization tool that supports and facilitates our analysis.

What Does A Data Visualization Tool Do?

To understand in a simpler way how a data visualization tool works, we will explain it:
We have a platform where all kinds of databases can be connected. On this platform, we can load data manually and automatically.

Manually, we will make the loads through Excel, CSV, JSON or HTML documents for example. Loading this data over time can be facilitated by sending the databases to the platform by email.
The connections that are made automatically can be several. For example, if the visualization tool has developed the connectors, we can connect via API with Facebook, Instagram, Twitter, Google or Adobe Analytics ...

Connections can also be made through SAS, Google Big Query or Hadoop. Unlike a DMP, a data visualization tool cannot activate other tools, that is, it does not have the capacity to make a call to the server of our Email Marketing platform to execute any action. It just collects the information and displays it. Although, in recent months, some of these platforms are starting to move towards the activation field.

What Is It Used for in Communication?

The Data Visualization gurus says that the data visualization platform collects the databases, previously labelled with business areas, reputation dimensions or company objectives.

For what? So that the impact of internal efforts can be measured, to have traceability of press releases in all media, to measure the effectiveness of each of the actions of the different campaigns.

It is the best way to control the objectives of the department and the company, to observe the real situation of the actions, the status of the reputation and the effectiveness of our communications.

 1) It allows to have a vision of what happens in all the communications of the company. Furthermore, the platform is interactive and usable. It is easy to extract knowledge from graphs.

 2) It is an ideal tool for communication since in this business area there has never been a spirit of measurement. However, metrics are already required from all departments and this is an easy way to carry them out.

     3)  It has the advantage that all the information comes from the same data source that can be consulted by other departments involved. This guarantees that the data is consistent and there are no inconsistencies in the results of one or another department.

     4) It allows metrics and cross-sectional dimensions to be used in all databases, matching them to be able to analyse them together.

Key to Keep in Mind

First of all, for a d3 expert tool to be useful to you, your data needs to be consistent. In other words, you have to have data volume and reliability. The data collection methodology must be consistent across all databases.

Comments

  1. Lafay Tech Plaza23 August 2021 at 06:38

    Azure Data Lake Gen2is a fully managed Hadoop-as-a-service offering on Azure. It provides cloud-based secure storage and interactive querying of large-scale data sets, and is optimized for storing massive datasets in one or more file shares. Data Lake Gen2 adds significant new features over the previous version, including an update to the Hadoop 2.8.2 stack, HDFS support, support for Kerberos delegation, high availability, and more.

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