Become a Data Engineer: Mastering the Concepts
English | Tutorial | Size: 1.86 GB
Build extensive data engineering and DevOps skills as you learn essential concepts. With this learning path, master the tools of the trade and how to apply them in real-world data project environments and platforms.
Data Science Foundations: Data Engineering
Discover the basics of big data with a data science expert. Learn about how to perform core data engineering tasks including staging, profiling, cleansing, and migrating data.
NoSQL Essential Training
Get a high-level view of the basics of NoSQL, from how it differs from relational databases to its pros and cons.
Apache Spark Essential Training: Big Data Engineering
Learn how to make Apache Spark work with other Big Data technologies and put together an end-to-end project that can solve a real-world business problem.
Architecting Big Data Applications: Batch Mode Application Engineering
Learn about use cases and best practices for architecting batch mode applications using big data technologies such as Hive and Apache Spark.
Architecting Big Data Applications: Real-Time Application Engineering
Learn about use cases and best practices for architecting real-time applications using big data technologies, such as Hazelcast and Apache Spark.
SQL: Data Reporting and Analysis (2019)
Get the data you need for analysis and reporting by writing your own SQL code. Learn how to write basic SQL queries, sort and filter data, and join results from different tables.
SQL Tips and Tricks for Data Science
Get Ben Sullins’s 12 must-have SQL techniques for data science pros-engineers, DevOps, data miners, programmers, and other systems specialists.
Cloud NoSQL for SQL Professionals
Learn how to choose a cloud-based NoSQL database solution that’s right for your organization.
Advanced NoSQL for Data Science
Explore the fundamentals of NoSQL. Learn the differences between NoSQL and traditional relational databases, discover how to perform common data science tasks with NoSQL, and more.
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