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Beinex supports the launch of AWS Middle East Region in the UAE region

Beinex is proud to support Amazon Web Services (AWS) for the launch of AWS Middle East Region in the UAE. AWS is a global pioneer in cloud-based offerings, with more than 200 services provided from data centers run globally. An AWS Advanced Consulting Partner Beinex can transform how you run your business digitally by providing you with the true edge in AWS cloud-related implementations and solutions.

And yes, feel free to avail of the incredible Region Launch special offers we have for you!

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Special Offers in Connection with the Launch

10% Discount

10%
off

Real-Time Analytics Using AWS Kinesis

AWS Kinesis provides a fast and efficient way to transform and analyse streaming data in real-time using Apache Flink. It also allows customers to query and analyse data in real-time and continuously produce insights and stateful computations to trigger real-time actions like anomaly detection based on historical data trends. Such live data can then be visualised in the form of BI dashboards using Tableau or PowerBI.

Experience spot-on visualisation for dynamic data input flow.

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10%
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Cloud Readiness Assessment

A cloud readiness assessment is a process where an organisation looks at its resources and IT environment and determines if it is capable of migrating to the cloud. It is a best practice for any organisation migrating all of its IT infrastructure, or even a single app, to the cloud to perform a cloud readiness assessment in order to smoothen the migration process and set up a cloud environment that fits the organisation’s requirements.

Embrace the next big tech revolution and validate if your organisation is cloud-ready.

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Predictive Analytics Models on BI platforms Using AWS ML Stack

The SageMaker ML platform is designed to support the end-to-end ML model lifecycle, from model data preparation to model deployment. Its modular architecture makes it flexible as well. This means customers can choose to utilise SageMaker independently for model building, training, or deployment, enabling the creation of predictive analytics models directly on Tableau or Power BI dashboards.

Get a seasoned consultant to ingest data and create ML models based on KPIs provided.

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AWS SageMaker Case Study:

Savings of 800,000 Euros per Year

For this energy utility major based out of France, close to 10,000 pieces of equipment will be linked and every single one of them with dozens of models, providing an estimated savings of 800,000 Euros per year for the company.

The Challenge

The company encountered the issue of Predictive Maintenance with several thousand pieces of equipment functioning and those too of multiple models.

Solution

It decided to tap into the AWS suite to develop, train and deploy predictive maintenance models to foresee breakdowns of equipment parts.

Results

  • Within a short period, 1000 plus prediction models were developed and trained when it came to a collective of equipment like valves, pumps, ventilation, air conditioning, and heating systems.
  • 10,000 pieces of equipment connected and shall benefit from predictive maintenance for the next 5 years.
  • Savings of 800,000 Euros per year for the company

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