Ementorhub

What you'll learn

Demonstrate proficiency in skills required for an entry-level data engineering role.

Design and implement various concepts and components in the data engineering lifecycle such as data repositories.

Showcase working knowledge with relational databases, NoSQL data stores, big data engines, data warehouses, and data pipelines.

Apply skills in Linux shell scripting, SQL, and Python programming languages to Data Engineering problems.

Skills you'll gain

Data Warehousing

PostgreSQL

MySQL

Extract, Transform, Load

Databases

Apache Spark

Data Infrastructure

Predictive Modeling

Data Pipelines

Dashboard

IBM DB2

Applied Machine Learning

Data Analysis

Big Data

MongoDB

IBM Cognos Analytics

Data Architecture

There are 7 modules in this course

You will demonstrate your knowledge of Data Engineering by assuming the role of a Junior Data Engineer who has recently joined an organization and be presented with a real-world use case that requires architecting and implementing a data analytics platform. In this Capstone project you will complete numerous hands-on labs. You will create and query data repositories using relational and NoSQL databases such as MySQL and MongoDB. You’ll also design and populate a data warehouse using PostgreSQL and IBM Db2 and write queries to perform Cube and Rollup operations. You will generate reports from the data in the data warehouse and build a dashboard using Cognos Analytics. You will also show your proficiency in Extract, Transform, and Load (ETL) processes by creating data pipelines for moving data from different repositories. You will perform big data analytics using Apache Spark to make predictions with the help of a machine learning model. This course is the final course in the IBM Data Engineering Professional Certificate. It is recommended that you complete all the previous courses in this Professional Certificate before starting this course.

Querying Data in NoSQL Databases

Build a Data Warehouse

Data Analytics

ETL & Data Pipelines

Big Data Analytics with Spark

Final Submission and Peer Review