Apache Spark's ability to improve the compute needs surrounding big data applications has increased its popularity. Many claim that Spark is the world's most popular open-source project.
Its success is due to the breadth of programming paradigms, supported APIs (Scala, R, and Python), and machine-learning libraries. Additionally, Spark enables connectivity to numerous data sources, including SQL-based relational database systems and NoSQL systems.
It's no surprise that Spark is preferred by data engineering globally.
It should also be no surprise that companies value employees who possess Apache Spark Certification.
For around $300, big data engineers and data scientist can achieve Spark certification. Any data science job postings will reveal the strong demand for Spark professionals.
A breadth of offerings can be found online. For programmers looking to advance their careers around Spark, Scala certification is also widely available.
Through the proper data engineer training, gaining Spark certification is manageable and almost certain to elevate your big data career to the next level.
SPARK AND SNOWFLAKE
The versatility of Spark goes hand in hand with the power and compatibility of Snowflake.
Snowflake's connectivity to and from Spark along with the rising status in data management analytics studies underscores the value of Spark certification.
Spark and Snowflake together -- among other things -- can simplify often complex ETL processes for machine learning pipelines. Snowflake's Spark ETL tutorial provides a step-by-step guide to capitalizing on these capabilities.
While the certified data analyst has already reaped benefits from the industry, those handy with Spark are now beginning to see their stock rise.
Explore Snowflake's free coursework and get a hand's on look a the cloud data platform or earn a data analyst certificate through our Data Cloud Academy.
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