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Learn Apache Beam with online courses and programs

Unified, portable, and flexible, Apache Beam simplifies and streamlines large-scale data processing to help businesses generate important analytical insights. Learn Apache Beam with online courses delivered through edX.

What is Apache Beam?

Apache Beam is an open-source unified model for defining data processing pipelines. A data processing pipeline moves information from one database to another while changing its format and correcting any errors. Pipelines are then executed by back-ends like Apache Flink, Apache Spark, and Google Cloud Dataflow.Footnote 1 This is an essential step that helps facilitate seamless data analysis. 

Data and software engineers can use one or more language software development kit (SDK) to build powerful, versatile pipelines on Apache Beam. Python, Java, SQL, and Go are just a few programming languages that offer users variety and flexibility.Footnote 2

Apache Beam focuses on defining two types of data parallel processing pipelines: batch and streaming. Batch-data processing collects large amounts of information over time, then performs deep analysis. This is convenient for companies that don't need immediate insights, and for use cases like payroll or billing.Footnote 3 Streaming data processing analyzes data continuously and in real time, which can be useful for more sensitive, urgent uses like fraud detection.Footnote 4

With Apache Beam, users can worry less about the logistics of parallel processing and rest assured that every task is executed properly.Footnote 5 As a result, businesses can analyze large data sets and discover key insights in a more efficient manner.Footnote 6

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Apache Beam tutorial course curriculum

An Apache Beam course may first explore the concept of big data frameworks and why they’re important. Companies often have to work with large data sets; a big data framework is a powerful tool that helps them process information quickly and at scale. 

Then, learners can dive into Apache Beam by reviewing its basic concepts and functions. They may practice setting up data pipelines via different SDKs, whether it’s batch, streaming, or both. Some courses may also explain how to use data processing engines on Apache Spark or Flink, and get learners accustomed to real-world scenarios where Apache Beam is most prevalently used.

Jobs that use Apache Beam

Apache Beam is primarily used for data processing and analytics. Data analysts, data scientists, and even developers use Apache Beam to perform various data processing tasks. They build and maintain pipelines, extract important findings, and mitigate future performance issues. 

If you’re looking to pursue a career in these fields, you may want to begin by building a strong educational foundation. edX offers a variety of online educational opportunities for learners interested in expanding their knowledge in these fields. You can earn a relevant bachelor’s degree as well as a master’s degree — or search for a boot camp that provides an intensive overview of specialized subjects. 

How to use Apache Beam for data processing

If you want to learn Apache Beam, it’s important to thoroughly understand the basics of data processing. Data processing allows companies to collect information from various sources. Before running an analysis, companies must ensure that data is transformed and formatted in a way that helps them easily identify insights.Footnote 7 Learners should be familiar with every step of this process. For instance, data professionals begin by installing a Beam SDK in their preferred programming language. They then set up a data pipeline and run it on an execution engine, which parses through the data and analyzes its patterns. 

It may also be beneficial to learn about machine learning, anomaly detection, and different types of analytics to gain a bigger perspective of how effectively Apache Beam works.Footnote 8 You can begin sharpening your data skills by pursuing a bachelor’s degree in data science or enrolling in a data analytics boot camp to put your learning into practice.

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