Background
1 June 2020

What is Big Data Engineering?

There are many definitions of Big Data Engineering, and they all relate to data and manipulation over them.

This concept explains how big data manipulation practices cover building data infrastructure, storing data, accessing and formatting it.

Separately, the tasks in which Big Data Engineering is used have been identified only recently and therefore it is not surprising that many specialists in the IT industry have not heard about Big Data Engineering.

 

What tasks solves Big Data Engineering?

 

Big Data Engineers can work in quite diverse areas: finance, tourism, advertising, security, e-commerce. Simply put, on a project or product that requires working with large data volumes, velocity, or variety in structure and format.

Big Data Engineering performs the following technical tasks:

  • Builds effective processes in pipeline processing (Data Pipelines). 

They use different tools for different types of data; in Big Data they often work with static or streaming data types. To do this, PHP frameworks like Apache Spark, Flink, Storm, Kafka, and cloud services AWS, Google Cloud, Azure are used.

  • Storage

Storage can serve as relational (PostgreSQL, MySQL, MsSQL, Oracle DB) and non-relational databases (Cassandra, MongoDB, Neo4j), and other storage like HDFS or cloud services.

  • Data processing. 

Data often come in a variety of formats, so its use in databases or other repositories, it is necessary to translate the data into a suitable structured format. This type of processing involves changing the data format (if necessary), data cleansing, anomaly detection. The most common types of data in the field of Big Data — Parquet, Avro, Protobuf, CSV. 

  • Infrastructure

Big Data Engineers must deploy the created solutions, participate in the CI/CD configuration, determine the necessary amount of resources for running programs, and build mechanisms for collecting metrics and logging.

As Big Data has a very large amount of data, high-speed streaming data, custom size, and other features, then working with such data requires special skills. 

 

So what is the result?

 

Today Big Data Engineering is a new technology that is gaining momentum in the IT sector. And as the field of Big Data is growing rapidly, this opens up new opportunities for developers to learn a new profession or develop a new IT solution. For example, the company Captify is already actively using Big Data Engineering in its work and we are confident that Ukrainian companies will join a number of such companies.