BIG DATA, THINK BIG
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
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
Agility
React before and with more information: make better choices.
Integration
With the main analysis and Business Intelligence tools in the market.
Efficiency
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
Features of our Big Data Solutions
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.
Collect
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.
Store
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.
