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Data Engineering

Name: Data Engineering
Price: 1196 USD
Availability: InStock

16k studentsBEGINNEREnglish

Korshub's take

A Structured Stack: From Databases to Analytics

A progression through the complete data engineering toolkit. Start with relational database fundamentals—design, schema, and platforms like MySQL, PostgreSQL, and IBM Db2—then master SQL's operational core. Move into NoSQL and distributed systems: MongoDB, Cassandra, Hadoop, and Spark. Learn how Python, Linux, Apache Airflow, and Kafka orchestrate data movement at scale. Capstone focus: design and query data warehouses using proven schemas (Star and Snowflake), then analyze results with Business Intelligence tools like Cognos Analytics.

For those building data careers, this tracks the real-world progression: relational mastery first, then query language depth, then the modern big-data and pipeline tools that process enterprise scale.

About this course

Describe the core concepts, processes, tools and technologies in the field of data engineering. ,Demonstrate your aptitude with RDBMS fundamentals including design & creation of databases, schemas, tables; DB administration, security & working with MySQL, PostgreSQL & IBM Db2. ,Demonstrate your proficiency with SQL query language, SELECT, INSERT, UPDATE, DELETE statements, database functions, stored procs, working with multiple tables, JOINs, & transactions. ,Explain NoSQL and big data concepts including practice with MongoDB, Cassandra, IBM Cloudant, Apache Hadoop, Apache Spark, SparkSQL, SparkML, Spark Streaming. ,Describe ETL tools, data pipelines using Python, shell scripts with Linux, Apache Airflow and Apache Kafka. ,Describe Data Lakes, Data Marts and Enterprise Data Warehouses (EDW) and design them using Star and Snowflake schemas. ,Design and populate Data Warehouses and analyze their data with Business Intelligence (BI) tools like Cognos Analytics.

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