Data Engineering Services
Solid experience and qualifications allow DevHight engineers to solve the most difficult tasks of working with a huge amount of data to make successful management decisions by business owners.
The volume of data is growing at a gigantic rate and obviously requires specialists capable of handling it competently.
The need to solve these problems requires the Data Engineer to be proficient with tools with different features:
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Maximum speed
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Maximum security
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Minimum cost
The most common database technologies are:
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Extract Transform Load (ETL) - migration of data between different systems. This technology allows the parameters of interest to be converted, processed and presented to the developer for final analysis
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Structured Query Language (SQL) - used by engineers to perform ETL tasks in relational databases. The tool is used when the source and recipient of the data are databases of the same type
Python is a popular programming language for ETL tasks. It has gained popularity because of its simplicity and extensive libraries. Many data engineers use mostly only this language
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Spark and Hadoop - these tools are distinguished by their ability to handle large data sets. This uses the power of many networked computers. Integration removes the limitations of processing and storing large amounts of information that a single individual computer has
HDFS and Amazon S3 are file systems designed to store almost unlimited amounts of data. What sets them apart is their low cost. They are also part of the environment in which data is processed.
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These and other tools are used by our company's specialists to solve clients' problems. Solid experience and high qualification enables DevHight engineers to develop complex systems and modules for collecting, structuring and analyzing huge volumes of data for making successful managerial decisions by the business owners.
