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Successful Big Data mining relies on the correct analytical model, choosing the relevant data sources, receiving worthy results and using them to ensure the positive end-users’ experience.

Needless to say, paying for the traffic used by the services connected to your AWS VPC (Virtual Private Cloud) has never been welcomed. AWS PrivateLink solves this issue!

Reading the streams of numbers is possible only in the movies. In the real world, the businesses have to use data visualization tools to get the trends and patterns out of the raw data.

Cloud computing has become the synonym of air — it is everywhere around us and every business needs to have free access to it to survive. Or is it so?

We recently explored the Big Data visualization principles. Now it’s time to delve deep into Big Data visualization techniques and find out which one is appropriate for various use cases.

While AWS is undoubtedly the benchmark of cloud service quality, it has some drawbacks we described when comparing AWS vs MS Azure. Today we compare Amazon Web Services (AWS) with Google Cloud Platform (GCP).

Big Data visualization is undoubtedly the most essential part of Big Data analytics. Instead of drowning the user in unstructured data, visualization helps provide the actionable insights.

A startup needs a good idea, a great team, a decent funding and an eager audience to succeed and scale. A data-driven startup has all these things covered. Wanna know how?

On the 23rd of October 2017, Microsoft has announced the release of a new scripting tool for Kubernetes — Brigade, an event-driven framework for handling various types of jobs.

As the time goes on, DevOps as a service evolves and gains new trends. While some of them are not too widespread yet, they might have a significant impact on the industry in the future.