The Role of Data Engineers in Analytics and Data Science 2025
The Connection Between Data Engineering and Data Science
Understanding Demand Forecasting
Demand forecasting is a crucial process that helps businesses predict future product demand based on historical data. For instance, a retail company with thousands of vending machines needs to forecast the demand for various products, such as Doritos chips and sodas. This forecasting relies heavily on the historical sales data collected from these machines.
The Role of Data Engineers in Data Collection
Data engineers play a pivotal role in gathering historical data. In our vending machine example, each time a product is dispensed, data is sent to a transactional database (OLTP). This database stores detailed information about each transaction, including device ID, SKU, transaction ID, and more. However, this raw data cannot be directly used for forecasting.
Transforming Data for Analysis
From OLTP to OLAP
To facilitate effective data analysis, the data must be transformed and moved to an Online Analytical Processing (OLAP) database. Data engineers are responsible for this transformation process. They extract the necessary data from the OLTP system and prepare it for analysis.
Utilizing Cloud Technologies
Data engineers utilize cloud technologies, such as AWS, to automate the extraction, transformation, and loading (ETL) of data. In our scenario, the data engineer extracts sales-related data from the OLTP database and transforms it to meet the specific needs of the data science team. This process ensures that only relevant historical sales data is loaded into a more efficient database like Snowflake or Databricks.
The Importance of Data Engineers in Data Science
Enabling Data Scientists
Without data engineers, data scientists would struggle to access the quality data they need for analysis. Data engineers ensure that data is not only collected but also cleaned, transformed, and made readily available for data scientists to use in their forecasting models.
Automation and Efficiency
The automation of data processes developed by data engineers allows for real-time or batch processing, depending on the requirements of the data scientists. This efficiency enables quicker insights and more accurate demand forecasting, ultimately benefiting the business.
Conclusion
In conclusion, the role of a data engineer is integral to the success of data science and analytics in 2024. They bridge the gap between raw data and actionable insights, ensuring that data scientists have the resources they need to make informed decisions. As data continues to drive business strategies, the significance of data engineers will only continue to grow. Understanding this role is essential for anyone looking to thrive in the data-driven landscape.
Unlock Your Career Potential
Frequently asked questions
Haven’t found what you’re looking for? Contact us at [email protected] — we’re here to help.
What is the Data Engineering Academy?
Data Engineering Academy is created by FAANG data engineers with decades of experience in hiring, managing, and training data engineers at FAANG companies. We know that it can be overwhelming to follow advice from reddit, google, or online certificates, so we’ve condensed everything that you need to learn data engineering while ALSO studying for the DE interview.
What is the curriculum like?
We understand technology is always changing, so learning the fundamentals is the way to go. You will have many interview questions in SQL, Python Algo and Python Dataframes (Pandas). From there, you will also have real life Data modeling and System Design questions. Finally, you will have real world AWS projects where you will get exposure to 30+ tools that are relevant to today’s industry. See here for further details on curriculum
How is DE Academy different from other courses?
DE Academy is not a traditional course, but rather emphasizes practical, hands-on learning experiences. The curriculum of DE Academy is developed in collaboration with industry experts and professionals. We know how to start your data engineering journey while ALSO studying for the job interview. We know it’s best to learn from real world projects that take weeks to complete instead of spending years with masters, certificates, etc.
Do you offer any 1-1 help?
Yes, we provide personal guidance, resume review, negotiation help and much more to go along with your data engineering training to get you to your next goal. If interested, reach out to [email protected]
Does Data Engineering Academy offer certification upon completion?
Yes! But only for our private clients and not for the digital package as our certificate holds value when companies see it on your resume.
What is the best way to learn data engineering?
The best way is to learn from the best data engineering courses while also studying for the data engineer interview.
Is it hard to become a data engineer?
Any transition in life has its challenges, but taking a data engineer online course is easier with the proper guidance from our FAANG coaches.
What are the job prospects for data engineers?
The data engineer job role is growing rapidly, as can be seen by google trends, with an entry level data engineer earning well over the 6-figure mark.
What are some common data engineer interview questions?
SQL and data modeling are the most common, but learning how to ace the SQL portion of the data engineer interview is just as important as learning SQL itself.