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Data Engineering: How You Make Data Work For You

3 Min Read
July 04, 2023
EduALL

In a world where we'll be producing 463 exabytes per day by 2025, data engineering is essential to turn raw data into useful information and insight. Moreover, data enables decision-makers to make well-informed actions that will benefit businesses, improve customer experience, and achieve organizational objectives. So, are you interested in the world of data engineering? 

Data Engineering at a Glance

Data engineering is the complex process of designing and building systems to enable the collection and analysis of raw data from multiple sources. Moreover, these systems allow people to find practical applications of the data which organizations can use to thrive. Furthermore, working with each system requires understanding of the technology and the data itself. 

With the advancement of the digital world, more and more data is produced. As a result, companies need to go through vast quantities of disparate data to answer critical business questions. Moreover, data engineering is designed to support the process, enabling data consumers like analysts, data scientists, and executives to inspect all of the data available.

Data Engineering Responsibilities

Data is organized through data engineering to make it simple for users and other systems to use. As a data engineer, you will perform several tasks, including:  

  • Acquisition: Sourcing the data from different systems
  • Cleansing: Finding and cleaning any errors in the data
  • Conversion: Giving all the data a common format
  • Disambiguation: Interpreting data that has multiple meanings
  • Deduplication: Removing duplicate copies of data

Here are the day-to-day tasks of a data engineer:

  • Acquire datasets that align with the needs of a company 
  • Ensure compliance with data governance and security policies
  • Develop algorithms to transform data into useful, actionable information
  • Build, test, and maintain database pipeline architectures
  • Work with the management of the organization to understand company objectives
  • Develop new data validation methods and data analysis tools

As part of their responsibilities, data engineers support Artificial Intelligence analytics and the Machine Learning process. Here are career path of a data engineer: 

  • Data Architects: design, implement, and manage the sources of data; integrate and organize certain parts of the data management system.
  • Data Engineers: design, integrate, and prepare the data infrastructure; work with various cloud technologies 
  • Database Administrators: maintain database systems to ensure that users can access all functions seamlessly; optimize the speed of databases 
  • Data Analysts: extricates data and uses various methods like data cleaning, conversion and modeling to comprehend the data
  • Systems Architects: pulling data into the applications they build

Data engineering qualifications and skills 

Many employers seek applicants with a computer science, software engineering, or mathematics degree. 

Here are the skills you need to have to start a career in data engineering:

  • Programming languages: Proficiency in coding languages such as SQL, NoSQL, Python, Java, R, and Scala.
  • SQL (Structured Query Language): SQL is the standard language for querying relational databases. SQL is used by data engineers to perform ETL tasks within a relational database. 
  • ETL (extract, transform, and load) systems: ETL is the process of moving data from databases and other sources into a single repository, like a data warehouse.
  • Cloud Data Storage: When processing data, data engineering uses Google Cloud Storage, Amazon S3, and Azure Data Lake Storage (ADLS). These data storage systems integrates into environments where the engineer will process the data. 

Without a doubt, data engineering is becoming more and more essential as the world becomes data-centric. If you are someone who finds it exciting to build and design large-scale data systems, then data engineering might be a field you need to get into!

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