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Dev Ops

Amazon says "DevOps is the combination of cultural philosophies, practices, and tools that increases an organization’s ability to deliver applications and services at high velocity: evolving and improving products at a faster pace than organizations using traditional software development and infrastructure management processes. This speed enables organizations to better serve their customers and compete more effectively in the market."

We agree.

Big Data

Big data is being generated by everything around us at all times. Every digital process and social media exchange produces it. Systems, sensors and mobile devices transmit it. Big data is arriving from multiple sources at an alarming velocity, volume and variety. To extract meaningful value from big data, you need optimal processing power, analytics capabilities and skills.

Data Science

Ask the right questions, manipulate data sets, and create visualizations to communicate results.

This specialization covers the concepts and tools you'll need throughout the entire data science pipeline, from asking the right kinds of questions to making inferences and publishing results. In the final Capstone Project, you’ll apply the skills learned by building a data product using real-world data. At completion, students will have a portfolio demonstrating their mastery of the material.

Cloud

We know that the list of advantages to cloud computing includes lowered operational costs, greater technological flexibility, and the ability to rapidly implement new systems or services. But are there measurable gains in business continuity? Read on.

Big Data and Dev ops

Today’s software developers like to fail fast. They don’t have the luxury of spending months developing and testing a new application only to find out it does not or no longer will meet the needs of the business. That’s something they need to find out ASAP, and it requires agility. The data scientists, data analysts, and developers working with Big Data analytics have similar requirements.

 To be successful, enterprise IT organizations need to extend the concepts of agile and DevOps software development models to Hadoop and Big Data; they need to allow data scientists and the developers they work with to get to the data and analytics they need as quickly as possible. That's where we come in. We cater to Amazon Web Services, Docker, Google Cloud Services and Big Data whenever and wherever it's needed.
And we love what we're doing.

Next Steps...

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