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Data Visualization: The Big Context of Big Data

Data visualization, or DataViz, is in full swing. It accompanies the development of the Big Data market. Data visualization provides an interactive visual representation of the data, and makes graphic and user-interactions emerge from facts, trends, undetectable otherwise.

Data visualization allows an understanding of a very large stream of data whose simple readings and analysis are made impossible by the amount of data involved. Data visualization is becoming a solution for many sectors such as banking, marketing, telecommunication, transportation, health and public services.

All sectors that have accumulated a large stock of data and are continuing to do so should be the users of data visualization. These data can be of any order: website logs, sales history, behavioural data, textual data, statistical, geographical, economic, social data, etc.

The reasons for a boom – the massive digitization of data

The Internet is emerging for a variety of reasons:

  • It is a producer of data: history of site visitors, behavioural tracking of Internet users, data produced by consumers on social networks, forums, opinions, votes, notes…
  • It is data storage: thanks to the clouds, this data can be collected, stored and analyzed.
  • It is a broadcaster of data: the public utilities launch themselves in the Open Data for reasons of transparency but also because the technology allows it.
  • It is the interface of data: from dedicated user interface, it is possible to create interactions that will allow the public to manipulate the visual representations to search for information.

In addition, computer design has evolved to a greater degree of technicality: the emergence of visual standards (open font, web, css, html, svg) and accessible programming languages ​​(javascript, python, php). Programmers have helped create a generation of “techno-designers” who have combined a very precise sense of design with a strong and precise knowledge of technical constraints.

The emergence of Big Data

Big Data is constantly developing and taking shape within companies. The idea is that all the data produced over several years, by thousands, even millions of consumers, if it can be analyzed, it will offer the opportunity to be even more effective in the sale of new products or in creation of new services.

The global economic crisis reinforces this idea: strategic decisions made by companies, such as investment decisions by financial groups, must be justified – it is not enough to give conclusions, they must now be demonstrated, and they must be sufficiently granular to give their approval to the strategic orientations.

In addition, financial and political scandals, international scams, terrorist groups and international money-laundering require a total expression of transparency. The Big Brother effect is reciprocal: if markets, businesses, politicians get a lot of information about consumers or voters, citizens can also equip themselves with open source tools and demand access to all kinds of data to verify the probity of governing elites.

A source of job creation

Data visualization will create a large number of high value-added jobs. These information engineering professions are a key asset for a country. Indeed, it is not only a question of creating a new service in the tertiary sector, but it gives a strategic advantage to a country or a company.

Some of these trades already exist but they must be adapted to the dual notion of “Big Data” and “Data visualization” which involve reconsidering practices.

  • Data collection

These are the trades for collecting information. This ranges from the network administrator who configures the Apache server to retrieve the browsing history of visitors to a site, to the technician who places a shape recognition camera to count the number of passers-by in front of a shop window and their behaviour.

  • Aggregations

They analyze the data and qualify it. They determine categories, validate the consistency of information, and format or standardize the information to be processed.

  • Statistical modelling

They propose representations and modalities of interrogations of the database created. They validate the choice of representations, and denounce the possible interpretation bias.

  • Data design

They program and design visual representations, define data mining interactions, create user interfaces to query and visualize data.

  • Consulting

They interpret visual information and recommend strategic directions.

New offers to create

  • Desktop Software – Provides software to develop its own data analysis applications.
  • The Saas – Provides online tools to simplify the production of graphics.
  • The data-design studio – Recovers data already processed and analyzed and offers a pleasant visual infographic. The problem is not to access knowledge but to communicate a message through computer graphics.
  • Consulting – Proposes a strategy for the implementation of a policy of processing, analysis and representation of large data. The principle is to put in place decision-making tools.
  • Data mining – Retrieves information from the organization, analyzes the data and represents it to help the organization make decisions.
  • Data Journalism – Recovers data, usually public, the structure, then presents (data-design) but also analyzes and explains them.

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One thought on “Data Visualization: The Big Context of Big Data

  • May 25, 2017 at 9:10 am

    Visualizations give people the same feelings that they get with these new fast and slick cars. There is a lot of power under the hood. But just like with cars, visualizations need to get us from A to B. Just because the tools today are more powerful, it doesn’t mean they’re more useful.


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