Big Data Architecture

Technology & Innovation

To transform your company’s data into business insight and intelligence, the first technical challenge lies in building the architecture and technology tools necessary for supporting an entire Big Data ecosystem.

One of the most common problems encountered in Data Science is the sheer quantity, volume and different types of data that exist. Being able to process all that information quickly requires distributed systems. The design of a Big Data architecture is key to implementing the systems and technologies necessary for being able to distribute all that information.

Experts in Ad-hoc Big Data Architectures

Synergic Partners offers Ad-hoc Big Data Architecture services for companies, designing the structure and choosing the technology tools and components to support the Big Data projects proposed depending on the needs of the business.

Given the existence of various options when configuring Big Data Architecture, we have experts with knowledge of various solutions who can offer customised design and development.

Based on the characteristics of your data and the technological capabilities of your company (hardware and software), we propose the best solution and implement it.

On-premises or Hybrid Cloud Infrastructures

Based on the specific characteristics of your company, the level of security required, and the processing capacity or storage needed, Synergic Partners will offer to develop your Big Data projects either using cloud solutions (IaaS, PaaS, SaaS), on-premises solutions (at your own offices) or hybrid solutions, with the support from our technology partners.

  • · Cloud-based platform. We work with reliable partners: Amazon Web Services, Microsoft Azure or Google Cloud Platform.
  • · Specialists in Hadoop: via such partners as Cloudera and HortonWorks among others.

Flexibility and scalability

In order to enable steady growth of your company and the uptake of Big Data projects, any data platform needs to satisfy flexibility and scalability demands.

In Big Data environments, platforms are highly flexible and adapt to suit data storage and processing needs while incorporating new capabilities (IoT platforms, tools, APIs, new data sources, etc.).

It is therefore crucial, that from the design phase of the data architecture, the possibilities of scalability of the same are foreseen, to enable productivisation of the models and processes to be developed. This also leads to a cost reduction for implementation, development and maintenance.

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