Whether you’re an aspiring data engineer, data architect, business analyst, or data scientist, strong data warehousing skills are a must. With the hands-on experience and competencies, you gain on this course, your resume will catch the eye of employers and power up your career opportunities. A data warehouse centralizes and organizes data from disparate sources into a single repository, making it easier for data professionals to access, clean, and analyze integrated data efficiently. This course teaches you how to design, deploy, load, manage, and query data warehouses, data marts, and data lakes. You’ll dive into designing, modeling, and implementing data warehouses, and explore data warehousing architectures like star and snowflake schemas. You’ll master techniques for populating data warehouses through ETL and ELT processes, and hone your skills in verifying and querying data, and utilizing concepts like cubes, rollups, and materialized views/tables. Additionally, you’ll gain valuable practical experience working on hands-on labs, where you’ll apply your knowledge to real data warehousing tasks. You’ll work with repositories like PostgreSQL and IBM Db2, and complete a project that you can refer to in interviews.
PM
practical knowledge as per real time project is more important that is not provided here
JP
R​eally great introduction to Data warehouses, applications and operations inside them.
DL
It was awesome experience to Data warehousing and BI analytics
CM
Great content with awesome labs to test your new skills. I like the bussiness to analytics regarding facts and dimensions table.
SB
Well-rounded. I do not realize when this course made me confident with designing DWs, I just followed the course actively.
DS
G​ood course, theory and hands-on alligned! In special, operations in cubes, such as: rollup, drill down, drill up, pivot and others. Thanks!
RM
A great course. it will be good if you can add more real life examples and case studies
LA
best course ,with a ver clear outline and enjoyable labs
KW
This is a really good course which covered the basics as well as some intermediate concepts. It was easy to follow and the exercises helped me to solidify my knowledge.
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peer review assignment instructions are causing confusion as other people have commented. There is no correct answer provided for grading for the cognos questions. Some python libraries are failed to be installed in the provided environment but yet no instructions were provided to address those (as others also commented).
buggy, buggy, buggy. please to yourself a favor and don't take any IBM Data Engineering Course - it's not worth it
I did not like the quality of the course.
Labs are terribly designed.
This course does not deliver. The content itself is good, but it was delayed and the labs were broken. Things were not even tested before they were published. If Skills Network Labs is buggy, then at least provide us a way to practice locally. After several great MOOCs on Coursera, I finally found the one that it is disappointing.
The videos are not engaging. Some aspects are explained in great detail and with good illustrations, other import parts are quickly glossed over and assumed to be familiar. I would only recommend this course if you've been working in IT for a while.
The worst course in IBM Data Engineering path.
very poor instructor just read the same thing that is written on the page definitely not recommended
The lab was not avaiable for a few days to complete the final assignment. Poor services.
While I am thankful to dive into the syntax and UI of mongodb, cassandra, and cloudant, and that hands-on does provide some value, this course needs an overhaul. The final project is a test of patience. The instructions have typos. There are over 200 threads of frustrated students trying to make their way to the end of the project due to the previously mentioned mistakes in the instructions and unanticipated issues a student may encounter. This could be so much better and I see it as an injustice that this course is great on the outside but rotten on the inside. I suspect dishonesty.
Not a good course
This is a good course and introduces useful practical skills. However, I get the feeling that the effort put on the third week is less than the usual standard in the IBM Data Engineering Certification: the lab material needs to be updated and the quiz questions should rely moref in the practical experience in the labs.
practical knowledge as per real time project is more important that is not provided here
This is a really good course which covered the basics as well as some intermediate concepts. It was easy to follow and the exercises helped me to solidify my knowledge.
An OK quick introduction to data warehousing. I learned some new SQL for analytics that I didn't know about before (I have a dev background). Course materials and quizzes are a bit lazy. For example, in the final assignment, the initial data format doesn't match the schema of the actual data provided for analysis. Also, the quizzes quite often ask specific, non-generalisable questions like "what is the URL to sign up for IBM Cognos".
useful course on Data warehousing. More focus on promoting IBM cognos analytics tool!
No depth to the course, hardly any mention of SCD which is one of the fundamentals in data warehouse modeling
There is no content in the SQL editor.
Great course. It gives a core knowledge of DB Warehousing as well as it describes what are facts and dimensions. Gives some practice creating it from scratch. Knowledge of SQL is quite essential to complete the final assignment.
Practice labs will help as everything is described. Cognos Analytics part is very short but there is the standalone course with more comprehensive practice.
Every course in this professional certification program designed such way that to get hands on real time project experience. The courses are well explained and labs were designed to get hands on experience. I congratulate and wish the team who designed this program and content. Thank you so much all and thanks coursera for this opportunity.