5 SQL Certifications for Your Data Career in 2024
A database or SQL certification may help you reach your goals in the world of data science. Here are five to consider.
February 18, 2021
Article
Data engineering is the process of designing, transforming, and architecting data infrastructure. Businesses rely on data engineers to create organized, meaningful data to make decisions. Get started in your dream data career with these resources.
Get started with these courses
Skills you'll gain: Data Management, Apache, Extract, Transform, Load, Big Data, Data Engineering, Distributed Computing Architecture, Machine Learning, Databases, Data Warehousing, Data Architecture, Kubernetes, NoSQL, SQL, Cloud Applications, Cloud Computing, Cloud Storage, Data Visualization, Database Administration, Leadership and Management, Python Programming, Data Analysis, Network Security, Linux, Business Intelligence, Computer Programming, Data Visualization Software, Statistical Programming, Data Science, PostgreSQL
Build toward a degree
Beginner · Professional Certificate · 3 - 6 Months
Skills you'll gain: Data Engineering, Data Management, Extract, Transform, Load, Databases, Network Security, Big Data, Data Analysis, Data Warehousing, Leadership and Management, SQL, Cloud Computing, Computer Programming, Data Science, NoSQL, PostgreSQL, Python Programming
Beginner · Specialization · 3 - 6 Months
Multiple educators
Skills you'll gain: Data Architecture, Feature Engineering
Intermediate · Professional Certificate · 3 - 6 Months
Working with data is an exciting career path with in-demand skills. That's why we've collected resources on data engineering and other data topics, including:
AI and machine learning
Data analytics
Data basics
Data science
Generative AI and ChatGPT
Data engineering is a subfield of data science responsible for designing, building, and maintaining data infrastructure to collect, process, store, and deliver data so that it can be used and analyzed at scale. Data engineering is extremely important for navigating today’s big data landscape because it enables organizations to generate timely data analysis to guide more effective decision-making.
Data engineers are tasked with the responsibility of preparing massive amounts of data for analysis by data scientists. By using frameworks like Apache Spark to pull data from Hadoop data lakes, data engineers can deliver data for analysis quickly. With the use of machine learning platforms such as TensorFlow, they can train and use neural networks to help decipher unstructured data like video, audio, and image files. And, by using cloud database platforms like Cloudera, data engineers can leverage the power and scalability of cloud-based approaches for their work.
Big data is changing the way we do business and creating a need for data engineers who can collect and manage large quantities of data. Learn more about the role of a data engineer and find out how to become one.
When starting to learn data engineering, you might need to already have strong experience in working with data projects. A four-year college degree in computer science would be highly beneficial, but more often than not, companies might be more interested in someone who has a strong understanding of the fundamentals of computers, software, coding, and programming languages. You will need to have a comprehension of the data engineering ecosystem, databases, and languages like Python, Sequel, and C. It would also help to possess a keen analytical ability to see through the data weeds to offer some insights and understanding to others in your organization.
Yes! Coursera offers a wide range of online courses and Specializations in data engineering and related topics like machine learning and data science. You’ll be taking these courses from top-ranked institutions and organizations like the University of California San Diego, the University of Colorado, Google Cloud, and IBM, so you don’t have to sacrifice the quality of your education to learn online. Coursera also offers the opportunity to get professional certificates in data engineering and data science from Google Cloud and IBM, so you can continue to add to your credentials on your own flexible schedule.
Choosing the right data engineering course depends on your current skill level and career aspirations. Beginners should look for courses that introduce the basics of data engineering), including data modeling, database management, and ETL processes. Those with some experience might benefit from intermediate courses focusing on big data technologies, data warehousing, and cloud platforms like AWS, Google Cloud, or Azure. Advanced learners or professionals seeking specialized knowledge might consider courses on real-time data processing, data pipeline automation, or advanced data architecture. Reviewing course content, instructor expertise, and learner feedback can help ensure the course aligns with your goals.