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Data Engineering Cloud Technologies

Many companies face challenges in efficiently organizing business processes. Demand for cloud models grows as enterprise data grows. Large amounts of data require reliable storage, backup, and analysis tools. Modern cloud services help store and compute gigabytes of documents, files, and other data. They are available to businesses of all sizes. New ways to reduce costs and improve productivity are opening up for businesses. Cloud tools give the benefits of security and administrative control over data with ease of use and flexibility. Today more than 90 percent of companies use cloud technologies.

Cloud Technology concept

Cloud technologies are IT technologies for distributed processing of digital data. They help provide computer resources to the Internet user as an online service. The cloud is the entire set of hardware and software that handles and executes client requests. Cloud-based solutions provide an infrastructure for digital products that quickly grows or decreases depending on business needs.


The best Cloud Solutions of the World

Leaders of the global public cloud services market are:


  1. Amazon Web Service (AWS)

  2. Microsoft Azure

  3. Google Cloud Platform

  4. IBM Cloud

These companies have accumulated a lot of expertise in developing and inventing cloud services. Most enterprises choose these providers as businesses benefit from their global capabilities, rich experience, and a massive amount of cloud services.


AWS is an IT infrastructure platform of various services: computational power, databases, network solutions, storage options. The essential advantage of the AWS cloud is its high security. Data encryption, hardware modules, and security certification are used for protection.


Microsoft Azure is a vast cloud-based platform that combines IaaS computing infrastructure solutions (servers, data warehouses, networks, operating systems) and a set of tools and services that facilitate the development and deployment of cloud applications (PaaS). The variety of services, their constant development, the emergence of new ones, and maximum data protection allow Azure to take a leading position. There are an unlimited number of MS Azure platform use cases.


Google Cloud Platform provides a variety of features, including:

  • computing services

  • storage services

  • network services

  • big data services

  • artificial intelligence services

  • Google products, creating acceleration services, websites, and data storage.


IBM Cloud provides universal infrastructure and platform services: virtual capacities, storage, network infrastructure, operating systems, virtualization, databases. Also, users can find more complex services for development, blockchain, building chatbots, server-free computing, containers, etc.



Which Cloud Services are Popular in Data Engineering?

The advent of cloud solutions has greatly benefited the software industry. Most companies have changed their strategies by moving existing projects to the cloud and building new ones on this basis.


The largest provider of cloud storage, AWS provides many offerings for data. Here we will look at three of the most popular services.


AWS Glue is a simple and cost-effective ETL service for data analytics. It generates ETL code in Scala or Python to extract data from the source, convert it according to the target scheme, and then load it back into storage.

Glue is based on Apache Spark and is convenient for data engineers who have experience with Spark. For instance, migrating from Hadoop.


One of the main services provided by AWS is EMR. It's a platform that manages all the features necessary to handle big data in a cost-effective, fast, and secure way. On-demand services mean that numbers can be controlled based on available data, making them cost-effectively and scalable.


AWS Athena is a SQL engine based on Apache Presto. SQL-query allows making SQL queries directly to data stored in the AWS Simple Storage Service (S3). It is a serverless solution that requires no infrastructure. Users can create SQL queries in the ANSI standard with the new interactive query editor, using a standard syntax to access objects stored in S3. This tool complements Redshift or EMR.




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