Expertise | DATA2B

Our Fields Of Expertise

Here’s an explanation of the scientific disciplines that we use to help you

Data Science

Our data scientists combine computer skills and mathematics to ensure data analysis achieves the expected results.

The role of data science is to extract useful information from the vast pool of available data and make it ‘speak’. By cross-referencing various data sources – both company specific and open data – our data scientists identify links between them that explain and understand phenomena, and enable accurate forecasts.

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This is possible thanks to machine-learning algorithms, which requires a large database, called a learning base, which groups data that characterizes a phenomenon, as well as the phenomenon itself. Business expertise is also needed, in order to select the data influencing the observed phenomenon, which is what constitutes the learning base.

Network Science

Network science has been defined as ‘organized knowledge of networks based on their study using the scientific method.’

So, it’s the job of our network scientists to delve into the vastness of Big Data and establish connections, links and interactions that help solve a particular problem. This is an interdisciplinary field of emerging research, covering aspects of physics, biology, epidemiology, information science and cognitive science.

Geomatics

This is the science of geographic information (the term comes from the combination of geography and informatics) and involves the acquisition, analysis and representation of geolocated data.

This ability to understand geospatial phenomena is crucial when analyzing large data sets, as the majority of objects studied are influenced by their close environment. Understanding this environment makes it possible to assess the dynamics that govern it. In turn, this provides answers to many issues and problems.

Big Data Architecture And Software

The boom in the amount and variety of data available, as well as the need to process it instantly, is challenging traditional storage and processing technologies.

To overcome this, we use the Hadoop open source software platform, which houses and ecosystem that perfectly meets the challenge of Big Data in terms of storage scalability and computing power.

However, there is no generic architecture, and our case by case examination and understanding of business needs and analysis of the data lifecycle is crucial.