Currently, companies manage a large volume of data that, day by day, hinders its correct management and interpretation. We are talking about Big Data concept, a complete puzzle when, starting from them, strategic decisions must be made for the company. This difficulty, united with a constantly changing business landscape, make essential to have a system that is capable of interpreting data quickly, easily and intuitively.

Therefore, in this article we are going to explain how Ayscom can contribute to the improvement of your procedures, both data collection and interpretation, using Data Mining, Data Analytics and Data Science techniques.

Main concepts of Big Data

What is Big Data?

This concept refers to the data set whose size, complexity and growth speed make it difficult to capture, process and analyze it. However, they are extremely important, since they provide answers to many questions that companies do not even know they have, such as, among other things, which niche markets are not covered or in which geographical area their product is most sought after.

In short, Big Data makes possible for us to consider and identify both problems and new opportunities in a more understandable way. In other way, the perception of these would be unrealisable.

At present, Big Data systems from several tens of TeraBytes to PetaBytes are being managed.

What is Data Mining?

When we talk about Data Mining, we refer to the process based on analyze big amounts of raw data, with the objective of discover patterns and other relevant information.

Usually it is done in databases that have structured information in a certain way. Once this process has been carried out, it is usual to have this data in a Data Mart or a Data Warehouse, where this information will be more organized and accessible.

What do we understand by Data Analytics?

This concept refers to a list of manual proccesses and techniques, both qualitative and quantitative, that increase productivity and business profits.

Once the data is extracted and organised, its behaviour is analysed with the aim of detecting patterns and developing techniques and solutions in relation to the  company or user requirements and the previously specific situation.

What is Data Science?

It is a multidisciplinary field that unifies statistics, data analysis and Machine Learning techniques in order to understand, analyse and, if possible, purpose a solution for a specific problem. To clarify this concept in a simple way, it is considered as “the whole of the Machine Learning process”, that is, predicting since learning.

The Data Science life cycle emcompasses all the processes mentioned previously and also adds Machine Learning techniques for the decision-making.

Data visualisation process in Big Data environments

Next, the process is detailed from which in Ayscom we process, purify and analyze the data of our clients to favor a simple and efficient interpretation of them:

First step is monitoring and testing of infrastructures and systems: we obtain a large amount of data, which is collected in a database. This raw information is constanly increasing, and if we add the proper collection of information to this fact, we have a Big Data environment to work on.

Afterwards, Dashboards are developed, from where the data can be visualised in a graphier and even more comprenhensible way. These Dashboards will show us the data in relation to other factors that may have influenced them; we can access a more specific definitions of these data or stay in a more abstract layer, from where we can only see the situation and results without delving into certains searches.