Coursera

Data Engineering Capstone Project (Coursera)

Offered by IBM,
Data Engineering Capstone Project (Coursera)

In this course you will apply a variety of data engineering skills and techniques you have learned as part of the previous courses in the IBM Data Engineering Professional Certificate. You will assume the role of a Junior Data Engineer who has recently joined the organization and be presented with a real-world use case that requires a data engineering solution.

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Course 13 of 13 in the IBM Data Engineering Professional Certificate.

Syllabus

WEEK 1
Data Platform Architecture and OLTP Database
In this module, you will design a data platform that uses MySQL as an OLTP database. You will be using MySQL to store the OLTP data.

WEEK 2
Querying Data in NoSQL Databases
In this module, you will design a data platform that uses MongoDB as a NoSQL database. You will use MongoDB to store the e-commerce catalog data.

WEEK 3
Build a Data Warehouse
In this module you will design and implement a data warehouse and you will then generate reports from the data in the data warehouse.

WEEK 4
Data Analytics
In this module, you will assume the role of a data engineer at an e-commerce company. Your company has finished setting up a data warehouse. Now you are assigned the responsibility to design a reporting dashboard that reflects the key metrics of the business.

WEEK 5
ETL & Data Pipelines
In this module, you will use the given python script to perform various ETL operations that move data from RDBMS to NoSQL, NoSQL to RDBMS, and from RDBMS, NoSQL to the data warehouse. You will write a pipeline that analyzes the web server log file, extracts the required lines and fields, transforms and loads data.

WEEK 6
Big Data Analytics with Spark
In this module, you will use the data from a webserver to analyse search terms. You will then load a pretrained sales forecasting model and predict the sales forecast for a future year.

WEEK 7
Final Submission and Peer Review
In this final module you will complete your submission of screenshots from the hands-on labs for your peers to review. Once you have completed your submission you will then review the submission of one of your peers and grade their submission.

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