Big Data and Analytics Consultancy


Big Data comes out of IoT devices, medical records, web sites’ visits and marketing campaigns. To extract good ROI and predictive information from such huge amount of data, there exists several techniques that do need big computing power. The more computing power the more real time can analysis and predictions be. But computing power for Big Data processing and Predictive Analytics is not cheap.

Big Data Azure

Big Data AWS

Public clouds are becoming more and more successful because they allow companies to lower the required computing costs of Big Data processing by sharing hardware resources among several cloud customers. Big computing power is only needed when doing Big Data preparation and processing inside Machine Learning models. Before and after the processing, hardware resources become idle. Not paying for these big resources while idle, because of sharing them with other cloud users, is an intelligent way to lower costs.


On the other hand, the downside of public clouds include:

  • GDPR compliance in the cloud is not easy after US and European legislation conflict
  • Sensitive and confidential information must remain under control
  • Public cloud security is complex to implement
  • Public cloud resources are technologically demanding
  • Which resource to use to do each data processing step is not an easy decission


In this scenario, how can we help?

Our consultancy will help your company, both in your Big Data processing and your Move To Cloud projects, in all or any of the following ways:


  1. Strategy – Does your company need the public cloud resources? If so, which public cloud and which resources?
  2. Architecture – We can help you create the roadmap to public cloud
  3. Project Management – We can:
    1. Manage your project since the beginning
    2. Select the right team for your project
    3. Set up the public cloud platform for you (security, resources, connectivity, etcetera)
    4. Help you integrate the project with DevOps and CI/CD
    5. Coach and guide the team to implement the project in due time
    6. Take care of the cloud project maintenance (L1, L2, L3)
  4. Big Data – We can solve your doubts around Big Data processing
  5. Predictive Analytics:
    1. Do you have data to obtain good predictions?
    2. Do you want to create the data to do good predictions?
    3. Do you need daily Predictive Analytics?
    4. Do you need periodical one shot predictions?
    5. Do you have the money to create your own Predictive Analytics processing environment?


Big Data and Analytics