The growing rate of big data has led to an increase in demand of real time data processing and analytics. Data engineers play a huge role in designing and implementing data pipelines where data travels through from input to storage.A data engineer is a professional responsible for building storage solutions for huge amounts of data.
Data engineering on the other hand is the process of designing and implementing systems that collect and analyze data so as to get insights and understands trends and patterns in the data.
Roles of a data engineer
Extracting data from data sources - Data comes from different data sources eg. databases, external APIs among others. A data engineer therfore integrates data from these sources into a centralzed data storage.
Prepare data for analysis - data engineers are responsible of processing the data by applying some transformation, cleaning and validating making it ready for analysis.
Designing data pipelines - a data pipeline is where the data travels through from input to the storage.Data engineers are responsible for designing and implementing data pipelines to extract, transform, and load (ETL) data from various sources into a centralized data repository.
Step-by-step guide
step1: Master the basics
Mastering the fundamentals of data engineering would be the first step. As a data engineer it is advisable to have strong foundations in programming languages such as python and also databases such as MySQL/PostgreSQL, still get to understand data modelling which help in structuring data in a logical manner.
step2: Data manipulation and transformation
Data originates from different sources, therefore data engineer is responsible for extracting ,transforming, loading (ETL) and also cleaning and transforming data to make it ready for analysis.
step3: Getting insights and pattern from data
Data engineers should be familiar with various tools for visualizing the data such as tableau and power BI, so as draw patters and get insights from the given data.
step4: Building data pipelines
Having gotten the insights from data, you design and implement data pipeline where the data will travel through from input to the storage. data pipeline act as a highway for the data. This can be done by help of Apache Airflow to ensure smooth flow of the data.
step5: Data warehousing and data modeling
Data warehousing is the storage system for huge amount of data while data modeling involves organizing data in a logical manner which helps in ensuring efficiency, and consistency throughout the data lifecycle., this can be achieved by the help of snowflake and star schemas.
Conclusion
Data engineering is a critical field that empowers organizations to harness the full potential of their data. As a data engineer you need to have familiarized yourself with basics such as programming, data manipulation that is (ETL), know how to use visualization tools such as tableau or power BI, build pipelines and also get to understand how to structure data in logical manner.
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