It is simply impossible not to notice how quickly the total volume of metrics collected grows. Not only the frequency with which automatic systems collect data and the throughput of data warehouses has increased, but also the set of metrics that we can use. This trend is most clearly expressed in IoT, but other industries can also boast of a huge set of data sources, public or available by a special subscription.

Increasing the amount of data creates new challenges for analysts and professionals working …

Most of the time when a warehouse transforms into a datalike, question arises on how to normalize/denormalize the data. As an intro you can read an article, and follow the guidelines for deploying an IBM Industry Model to Hadoop.

To get an insight into a new highload big data platform you can read a blogpost on the keen website that highlights the architecture of several giants from a 10000 ft view.

Again serverless architectures are coming, the number of …

Big Data / IoT

You might have had inspiration to create a new database, and here it comes — a tutorial for creating a new time series database.

Performance is always critical, most of the speeches and talks are dedicated to improving performance of the jvm/.net runtime or sophisticated MPI algorithms. Nowadays, it usually comes to the fact that we need to improve the performance of a big data infrastructure, and most of the components provide various metrics and properties for fine tuning, and …

Articles

• The Big Data industry develops quite fast. New approaches, frameworks, databases, etc. appear every month (and our newsletter proves it).
  And this is the article about the tools to be ditched (according to its author) in 2017. Keep your stack up to date! ©
• Read about systems’ evolution seeing from the infrastructure point of view and its shift to the serverless design, architecture and deployment.
• The serverless architecture topic and the hybrid approach are continued in …