Today, we’ve assembled an incredible team of experts, technology partners and leading data scientists.  Not only do we identify the best Big Data architecture and technologies for your company, more importantly we provide the know-how to analyze and monetize your data.  We develop Software As A Services (SaaS) tools to improve your data science team’s work and productivity.

We are focused on providing a winning combination of expertise and knowledge supported by the latest technologies available in the market, including those developed by our own team of experts and technological partners.

Data Strategy

At ACCÉDER you will find experts to assist you with designing the best strategy to collect, organize and use the data your company generates. We can help you find the right solutions to maximize your results and budget when building your data infrastructure.

ACCÉDER does not represent any specific vendor - our priority is you and your company. We build a tailored strategy that will allow you to maximize data, and give you an edge in the market.


Data Predictive Models

We’re pioneers on discovering the value of Big Data developing data analytics systems. In 2010 we began building systems to collect, organize and provide insights from your data. Today we’re focused on developing models that will allow your company to gather all the value of the data it produces.

Our team of data scientists have built and deployed countless predictive models across several industries including Communication Service Providers, Banks, Insurances, Digital Media, and Web-based companies. We work with the latest technologies, languages and algorithms to produce, update or transform your predictive models.

From segmenting your customers, discovering the DNA of your best prospects, predicting who is likely to churn or what best action should be performed next, our team has the ability to take your raw data and transform it into valuable insights and/or predictive machines.

Additionally, we have an extensive experience on transferring R models into Python or Java models, coding from SQL to Redshift databases, as well as developing APIs to integrated models on new virtual environment and systems.


ACCÉDERr’s Data Monetization Model (DMM) is a result of our many years of experience in the data universe.

The DMM is a powerful framework for data owners (businesses that generate large scale sets of specific data) that can be used to develop innovative ways to produce new revenue sources (NRS).  The creation of a Customer Data Marketplace (CDM), gives you, along with the data infrastructure,  a very detailed picture of your digital ecosystem.  

This framework is divided into three different approaches of data monetization:



The first step to monetize data is to create revenue streams from the CDM, created with data from the single entity. Monetization comes from improving existing products and services with the new information obtained from the data infrastructure. It also enables identification of new opportunities based on the needs of clients or of the market, that become evident within the existing digital ecosystem.



The second step to monetize data is to develop partnerships with other data owners that will enrich the CDM and create an enriched data segmentation. This creates a very attractive Data Ecosystem that can be exploited by members for its own monetization actions, or can be sold to third parties who can benefit from the new CDM.



The third step when monetizing data is the integration of the data ecosystem into technologies to create products or services with large scale reach and market potential. At this point the data owners belonging to the ecosystem can create spin-offs or startups, in order to exploit this model on separate products and services under a new brand.


ACCÉDER's Data Monetization Model (DMM)




  • Exploit the data generated by a single data ecosystem.

  • Revenue comes from new advertising solutions and subscription fees from new products and services that can be generated from its CDM

Step: Data Ecosystems

  • Exploit the data generated by two or more data ecosystems creating a robust and rich CDM.

  • Revenue comes from more profitable advertising solutions and subscription fees from new products and services that can be generated with the additional data. These can now be offered to third parties.

Step: Technology Integration

  • Integrate data from the data ecosystems into trending new technologies to provide massive solutions for B2C to B2C.

  • Revenue comes from the products or services that are developed under a new business model.