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Turn data into your best asset

As an AWS Partner with the Big Data Competency, we have achieved a high level of requirements such as evidencing our deep technical knowledge and/or consulting experience helping companies to evaluate and use tools, techniques, and Big Data technologies in a productive way with AWS.

This means that we have the knowledge, capability and tools necessary to help your organization to get the most out of its Big Data workloads in AWS.

Data Lake Solutions

Data Warehouse solutions

Data Analytics solutions

Official profile on Amazon Web Services (AWS) website

We are the first AWS partner to achieve Data & Analytics Competency in Latin America

Solutions on Amazon Web Services,
get the most out of it

As an official partner of Amazon Web Services, we offer you specialized services in consulting, deployment, management and optimization of solutions on AWS.

Quickly create highly scalable and secure Big Data applications. You don’t need to provision hardware, there’s no infrastructure for you to maintain.

Everyday companies generate a huge amount of data that originates in different places and at different moments, no matter the sector. However, all this data is still not fully used. AWS and Morris & Opazo have the experience and technologies required to build a Big Data system useful for your company, that may help you to give a better service to your customers, as well as to discover new opportunities and strengths of your processes.

With AWS now is much easier to face and solve commercial and management challenges, by using Big Data techniques to collect, store, process, analyze and share your data in a more effective and secure way.

Benefits of our big data solutions


React before and with more information: make better choices.


With the main analysis and Business Intelligence tools in the market.


Large-scale storage at low cost and based on a pay-per-use model.

Do you know the key features of Big Data?

Know the 3 “V” s



Big companies generate big amounts of data, waiting to become valuable information.



Your company requires speed in making decisions. Let Big Data provide you with high availability of information.



By using Big Data it doesn’t matter where your data comes from.

Features of our Big Data Solutions

Solutions designed and implemented by our Certified Architects.
Large-scale storage at low cost.
Extraction and management of your data according to your analytic model.
Amazon Elastic MapReduce (EMR) based on Hadoop to process large amounts of data.
Integration with the main Business Intelligence tools.
Use of Amazon Redshift to speed up the large-scale management and analysis of data.
Integration with the main data analysis frameworks such as Spark.
Market Intelligence.

A Big Data Workflow consists of….

By using AWS it has never been easier or cost-efficient to solve commercial problems and discover new opportunities employing data. Now companies of all sizes and in all industries may take advantage of Big Data technologies and easily collect, store, process, analyze and share their data.


Collecting data with no processing, like transactions, records, mobile devices among others, is the first Big Data challenge the companies face. An adequate Big Data platform ease this step and allows developers to receive a huge variety of data, both structured and non-structured, at any speed, whether in real-time or batch.


Any Big Data platform needs a safe, scalable and lasting repository where data will be stored before or even after processing it. Depending on your specific requirements, you could also need temporary stores for data in transfer.

Process and Analyze

In this step, un-processed data is transformed into ‘consumable’ data, usually by classifying, accumulating, joining or even performing more advanced algorithms. Resulting data sets are stored to be processed even more, or to be available for their consumption through data visualization or Business Intelligence tools.

Consume and Visualize

Big Data goal is to get processable and valuable information from data resources. The best scenario is that related parts may access data through agile tools of data visualization and business intelligence that allows them to explore the data sets in a fast and simple way. Depending on the type of analysis, end users may also consume the resulting data as ‘statistical predictions’ (in the case of predictive analysis) or recommended actions (in the case of predictive analysis).

The Big Data Processing Evolution

Big Data ecosystem keeps on evolving at an impressive pace. Nowadays a diverse set of analytics styles support several company functions.

Descriptive Analysis helps users to answer the question: "What has happened and why?". Among the examples there are traditional report and queries environments with score cards and control panels.

Predictive helps users estimate the probability of a particular event occurring in the characteristic. Examples include warning systems, fraud detection, preventative maintenance applications and predictions.

Prescriptive Analysis provides recommendations (prescriptive) specific to the user. They answer the question: What should I do if "x" happens?

Cloud-Based Big Data Ecosystem

Create virtually any Big Data analysis application; support any workload regardless of volume, speed and variety of data. With more than 50 services and hundreds of features added every year, AWS provides everything you need to collect, store, process, analyze and view Big Data in the cloud.

Competences of our Team

Skills and Experience in the Design and Implementation of Big Data Solutions.

Cloud Practitioner

Overall understanding of the AWS Cloud.

Solutions Architect Associate

Experience and knowledge of how to architect and deploy secure and robust applications on AWS technologies

Developer Associate

Development and maintenance of applications in AWS platform.

SysOps Administrator Associate

Deployment, management and operation of scalable, high-availability, and fault-tolerant systems in AWS.

Solutions Architect Professional

Design of applications and distributed systems in the AWS platform.

DevOps Engineer Professional

Provisioning, operation and management of distributed applications systems in AWS platform.

Big Data Specialty

Design and implementation of AWS services to derive value from data.

Success Stories

Morris & Opazo

Promoting Best Practices on AWS

AWS Well-Architected Framework

Build your AWS foundation with Cloud Best Practices

Morris & Opazo Well-Architected Review offer is intended to educate customers on architectural best practices for designing and operating reliable, secure, efficient, and cost-effective systems in the cloud. This offer was developed around the Amazon Web Services (AWS) Well-Architected Framework, which helps customers understand the pros and cons of decisions made while building systems on AWS.

General Design Principles

Stop guessing your capacity needs

Test systems at production scale

Automate to make architectural experimentation easier

Allow for evolutionary architectures

Drive architectures using data

Improve through game days

The Five Pillars of the Framework

Operational Excellence

The operational excellence pillar focuses on running and monitoring systems to deliver business value, and continually improving processes and procedures. Key topics include managing and automating changes, responding to events, and defining standards to successfully manage daily operations.

The Operational Excellence pillar includes the ability to run and monitor systems to deliver business value and to continually improve supporting processes and procedures.


The security pillar focuses on protecting information & systems. Key topics include confidentiality and integrity of data, identifying and managing who can do what with privilege management, protecting systems, and establishing controls to detect security events.

The Security pillar includes the ability to protect information, systems, and assets while delivering business value through risk assessments and mitigation strategies.


The security pillar focuses on protecting information & systems. Key topics include confidentiality and integrity of data, identifying and managing who can do what with privilege management, protecting systems, and establishing controls to detect security events.

The Security pillar includes the ability to protect information, systems, and assets while delivering business value through risk assessments and mitigation strategies.

Performance Efficiency

The performance efficiency pillar focuses on using IT and computing resources efficiently. Key topics include selecting the right resource types and sizes based on workload requirements, monitoring performance, and making informed decisions to maintain efficiency as business needs evolve.

The Performance Efficiency pillar includes the ability to use computing resources efficiently to meet system requirements, and to maintain that efficiency as demand changes and technologies evolve.

Cost Optimization

Cost Optimization focuses on avoiding un-needed costs. Key topics include understanding and controlling where money is being spent, selecting the most appropriate and right number of resource types, analyzing spend over time, and scaling to meet business needs without overspending.

The Cost Optimization pillar includes the ability to run systems to deliver business value at the lowest price point.

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