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The ecosystem of data science tools based on the Hadoop and NoSQL stack is a crucial and growing part of the future of the industry. Data engineers need a broad knowledge of the components of this platform, and this learning path enables learners to dig in and skill up.
- Extend your general Hadoop knowledge.
- Branch into related tools such as Kafka, HBase, Hive, and Cassandra.
- Build your NoSQL skills.
Overview
Syllabus
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- Course 1: Analyzing Big Data with Hive
- Learn how to use Hive to analyze large datasets and derive information from Hadoop. Learn how to work with tables, structures, aggregations, clauses, functions, and more.
- Course 2: 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.
- Course 3: Cloud Hadoop: Scaling Apache Spark
- Generate genuine business insights from big data. Learn to implement Apache Hadoop and Spark workflows on AWS.
- Course 4: Apache Kafka Essential Training: Building Scalable Applications
- Learn about the scalability and manageability aspects of Apache Kafka and how to build asynchronous applications with Kafka and Java.
- Course 5: Hadoop for Data Science Tips, Tricks, & Techniques
- Get up to speed with Hadoop. Learn tips and tricks for doing data science work in this popular big data platform.
- Course 6: NoSQL Data Modeling Essential Training
- Get started with data modeling for NoSQL databases and learn how to work with common design patterns.
- Course 7: Cassandra Data Modeling Essential Training
- Learn about the architecture of Cassandra—a popular NoSQL database capable of handling large amounts of fast-changing data—and discover how to design Cassandra data models.