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Actual Data Infrastructure Tasks


New solutions and applications on the one hand provide data stack accessibility and simplicity on at enterprises, on the other hand promote appearing of bigger amount difficulties. Current situation looks like this: data amount that pass through the organization is growing rapidly. Also, a number of their sources is becoming more also that is connected with the appearing of SaaS tools numerously.

The modern data stack is oriented on the field of transactional data and analytics. But enterprises don’t manage just pipeline and have several of them that are working synchronously. Additionally, enterprises need streaming technologies that now are in the early stage of development.

As a result, such tools like Spark, Kafka, Pulsar will be relevant any further. Consequently, the requirement of data processing engineers that can use these technologies will also grow.

Orchestration systems have a dynamic development. It is proved by the appearing of such frameworks like Airflow, Luigi, Perfect, Dagster etc. These tools have the form of the libraries set with open source code. They are destined for work process developing, planning and monitoring. The tool is writing in the Phyton programming language and it is the differentiating feature. Such singularity gives a possibility to create and write task chains in visual mood and write Phyton code. DAG (Directed Acyclic Graph) is used for data visualization.

It follows that data management continuous to be the main requirement in a business environment (through the modern data stack or machine learning pipelines).

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