Information analytics (Big Data/IA)

Probably in your company a large amount of data of various kinds is generated daily. Data that grows exponentially day after day, assuming a considerable expense in storage space, and what is more worrying, without any use. It is time to value this data and get the most out of it, to help improve processes, increase profits, productivity and predict behavior in the future.

What do we

offer ?

We design and execute tailor-made proposals for our clients, related to data analytics from different sources and structures, development of predictive models, and information visualization for optimal consumption, always adapted to the user and with the aim of helping decision-making. decisions.

We build these projects on BigData architectures that support exhaustive treatment, fast processing and massive storage of information. From them, and from external data sources that we select, we train prediction models (machine learning) applied to the client's own activity: preventive maintenance, cognitive services, activity forecasts, billing, volumes, etc.

how can we

help you?

To do this, we establish a project in service mode with the client, where we begin a first phase of analysis of existing information sources together with the client, after which several objectives are set based on defining different use cases.

After this, the development phase begins where we define the data-warehouse, architecture, systems, clouds, frameworks involved, etc. We also include new external sources and those that come from unstructured environments, IOT networks, etc. Finally we carry out the main data mining work that comprises the largest percentage of project time.

In the last stage, the machine learning models are trained that allow estimates of future results to be made, with which behaviors can be simulated and therefore anticipate forecasting. As a form of consumption, visualizations are created and published through BI tools or web platforms that help interpret the required results, in real time, and adapted to the profile of each final consumer within the customer profiles that participate in it.

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