Designing a Big Data strategy is key to ensuring the success of the digital transformation that a company must undertake to adapt to the new demands and needs of customers.

For this, it is essential: Leadership, the design of a horizontal strategy in the organization, internal cultural change

Our team of expert consultants in Big Data helps you to define the Roadmap of your Big Data strategy from an initial diagnosis that will take into account the technological maturity of your company and the business aspects to improve.

To understand well the needs and objectives of the company, the collaborative work of both teams will be essential.


-Initial diagnosis Big Data.

1.- Knowledge of the company: Joint definition of what needs to be improved in the company.

2.- Initial Diagnosis: Evaluation of the current situation and technical requirements.

3.-Road Map: Roadmap and execution of the company’s big data strategy.


To transform your company’s data into business insights and intelligence, the first technical challenge is to have the architecture and technological tools necessary to support a whole Big Data ecosystem.

The most common problem of data science is: The quantity, volume and types of data

Being able to process all that information in reduced times requires distributed systems. The Big Data architecture design is key to implementing the systems and technologies necessary to be able to distribute all that information.

Big Data ad-hoc architecture

From BusinessGoOn we offer services of Big Data Ad-hoc architecture for companies, designing the structure and the choice of tools and technological components that support the Big Data projects proposed according to the need of the company.

Given the existence of different options when configuring a Big Data Architecture, we have experts with knowledge in different solutions for a custom design and development.

Cloud, on-premise and hybrid infrastructure

Depending on the characteristics of your company, the level of security required, the processing and storage capacity needed, at BusinessGoOn we offer you the development of your Big Data projects …

Whether through cloud solutions (IaaS, PaaS, SaaS), on-premise (in your own offices) or hybrid, with the support of our technology partners:

Cloud Supported Platform

We work with trusted partners: Amazon Web Services, Microsoft Azure or Google Cloud Platform.

Hadoop Solutions Specialists

Through partners such as Cloudera and HortonWorks among others.

Flexibility and scalability

Para permitir el crecimiento progresivo de su empresa y su adopción de proyectos Big Data, cualquier plataforma de datos tiene que cumplir con las premisas de flexibilidad y escalabilidad.

En entornos Big Data, las plataformas son altamente flexibles, adaptándose en función de las necesidades de almacenamiento de datos y procesamiento, así como incorporando nuevas capacidades (plataformas IoT, herramientas, APIS, nuevas fuentes de datos, etc).

En este sentido, resulta crucial que desde la propia fase de diseño de la arquitectura de datos, se prevea las posibilidades de escalabilidad de la misma, para la productivización de los modelos y procesos a desarrollar.
Esto se traduce además en reducción de costes de implementación, desarrollo y mantenimiento.


-Veracity of data, correct decisions

Once the architecture that will support the Big Data Ecosystem has been designed, the next step is to proceed with the data intake to the data lake, as the sole repository of all the data related to your company and its environment, regardless of its nature, type or volume.

❑ Big Data allows the agile incorporation and dynamic processing of new data sources without the need for architecture development.

❑ Data engineering sets the standards that any company needs to dispose of its data in a unified, clean and accessible way, responding to the company’s requirements.

❑ Its importance is crucial, since it is the phase in which the data is prepared so that in the later phase, the advanced analytics, the precise data models are executed, which can provide truthful business conclusions. If the data is not reliable, the business decisions will not be correct.

-Information processing

Data engineering services for information processing
At BusinessGoOn we offer all our own data engineering services, from data modeling, to the migration and automation of data intakes through scheduled workflows.

Data modeling and organization
Scheme of data distribution and replication for their security.

Organization of data for agile access.

Data quality

Profiling and enrichment of the variables.

Definition of data quality processes

Cleaning and standardization processes

Generation of variables, attributes and indicators directly from the DATA LAKE

Definition of data transformations, necessary after the extraction of their original internal and external sources

Data intake process (batch and streaming)

Integration and treatment of structured, semi-structured and unstructured data

Definition of strategy and roadmap of data intakes, with appropriate latency times. According to the type of data that each company has

Process automation

Cleaning process design and automatic data standardization

Framework for data integration automation.


Generation of new business sources

The data allows you to have a deeper knowledge of your client, and this makes it possible, together with the application of Machine Learning and Deep Learning techniques, to be able to customize your products or services so that your company adapts better to the needs of the consumer .

Therefore, through the knowledge of your client you can improve the effectiveness of campaigns, improve cross-selling ratios, boost up-selling etc.

Improvement of operational efficiency

Thanks to the correct storage and provisioning of data in real time, together with technologies such as IoT, we are able to have a unified knowledge of the processes, of a production chain or of a machine.

An integral vision of the productive environment will allow you to anticipate a possible breakdown or anomaly, as well as improve maintenance cycles, which translates into operational efficiency.

Prevention and prediction of fraud and risk

Thanks to the ability to analyze not only a sample, but the entire data set, we are more effective at detecting anomalies.

Likewise, the option of integrating new data sources, which complement the information of your company and generate relationships that you did not know, such as official statistics, social networks, makes it possible to detect behavioral patterns and determine possible fraudulent or irregular cases, which It will allow you to offset future costs.


Translation enters the technical and business layer

One of the biggest challenges that Big Data poses is knowing how to make decisions about the results of the models and algorithms.

The area of ​​data visualization, almost intrinsic in any Big Data project, has the mission of showing graphically and clearly the results obtained from a project, mainly through dashboards; which includes different types of graphs, such as heat maps, maps with geo-located data or with movement flows, where it is sought to answer all the questions posed at the beginning of the project and thus convert insights into actions.

The data visualization tools allow to represent any type of information in a visual and simple way.

In BusinessGoOn we work with tools such as Tableau, CARTO, D3, leaflet, R libraries, among many others to be able to graphically represent the projects carried out.


The growing need of companies to digitize to face an increasingly changing market and increasingly demanding customers has led companies to populate their multi-machine processes (sensors, meters, GPS devices, computers, etc. .) in order to have an end-to-end view of their business from the point of view of processes.

❑ The inclusion of all these devices in companies is posing new challenges in terms of storage, treatment and analysis of all this data, in multiple formats, now available to organizations.

❑ It is thanks to Big Data and the use of Advanced Analysis techniques, that for the first time companies can have a unified vision of their processes, understanding their operation, their status and the environment.


Transforming a company to a data-oriented one is not an easy task, it is very clear to have a managerial strategy that allows prioritizing Big Data use cases that respond to business needs.

Likewise, a strict definition of policies and norms regarding the use of data is required, which is called data governance.

The governance of the data establishes a framework of reference, necessary for the maximization of the value of the available information in a transversal way throughout the organization through the definition of policies, procedures and roles that facilitate the effective management of the data life cycle.

From BusinessGoOn, we offer our clients solutions to guarantee data integrity and efficient management.


In generation of business sources:

High value customer detection for the company.
Customer 360º Vision
Define the optimal product / service product portfolio for each segment.
Sales prediction.
Dynamic prices
Increase and improve cross-selling ratios and boost up-selling.
Create personalized recommendations.
Attract new customers with Lead Storing

In improvement of operational efficiency.

– Office data.

-Monitoring and maintenance of machines.

– Stock management in real time.

-Optimization of routes in logistics transport.

In prevention and prediction of fraud and risk.

Prediction of customer leakage.
Detection of fraud and other anomalies.
Prevention of late payments or non-payment of customers
Anti-corruption activity monitoring.