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返回到 数据仓库的概念、设计与数据整合

學生對 科罗拉多大学系统 提供的 数据仓库的概念、设计与数据整合 的評價和反饋

4.4
996 個評分

課程概述

This is the second course in the Data Warehousing for Business Intelligence specialization. Ideally, the courses should be taken in sequence. In this course, you will learn exciting concepts and skills for designing data warehouses and creating data integration workflows. These are fundamental skills for data warehouse developers and administrators. You will have hands-on experience for data warehouse design and use open source products for manipulating pivot tables and creating data integration workflows. In the data integration assignment, you can use either Oracle, MySQL, or PostgreSQL databases. You will also gain conceptual background about maturity models, architectures, multidimensional models, and management practices, providing an organizational perspective about data warehouse development. If you are currently a business or information technology professional and want to become a data warehouse designer or administrator, this course will give you the knowledge and skills to do that. By the end of the course, you will have the design experience, software background, and organizational context that prepares you to succeed with data warehouse development projects. In this course, you will create data warehouse designs and data integration workflows that satisfy the business intelligence needs of organizations. When you’re done with this course, you’ll be able to: * Evaluate an organization for data warehouse maturity and business architecture alignment; * Create a data warehouse design and reflect on alternative design methodologies and design goals; * Create data integration workflows using prominent open source software; * Reflect on the role of change data, refresh constraints, refresh frequency trade-offs, and data quality goals in data integration process design; and * Perform operations on pivot tables to satisfy typical business analysis requests using prominent open source software...

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LS

2020年9月18日

Great course. It mimics real life case. However, the time required to complete assignments is much more than stated. The assignments are great though, I learned a lot from those.

EK

2015年12月15日

Very nice class, well thought out and organized. The assignments are interesting and the practice assignments are relevant. Getting hands on on Pentaho was a big plus.

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151 - 数据仓库的概念、设计与数据整合 的 175 個評論(共 196 個)

創建者 Paolo F

2018年3月4日

High quality info for a well structured course

創建者 PUNEETH M K

2019年11月4日

It's a nice opportunity to learn and

創建者 Shivam S

2017年6月21日

Nice Lectures Documentations Overall

創建者 Vinay B

2016年1月4日

Great course to learn DWH concepts.

創建者 MIRASOL, S R (

2020年10月29日

Hard course but was worth it.

創建者 vaibhav b

2016年12月25日

The course was very helpful

創建者 Lin Y

2016年5月26日

useful information

創建者 Mugdha G

2019年2月25日

Good course!

創建者 Santosh R

2016年10月6日

Great course

創建者 Dushyant S

2019年1月18日

Good course

創建者 Jair F L M

2018年11月30日

Good course

創建者 Nikhil n

2017年7月26日

excellent

創建者 Haripriya C

2022年3月9日

Good

創建者 karthik D

2019年1月23日

good

創建者 Nikos S

2022年5月29日

The course content is well structured. The lessons' delivery is clear and concise. Apart from that, there is much room for improvement:

The content is very outdated. Also, some of the course material should be rewritten (E.g., I lost count of how many times the course material states something different regarding which RDBMSs can be used for the assignment).

Many topics are presented using Excel or Excel-equivalents:

(a) In module 2, WebPivotTable is used to explain data cubes. WebPivotTable is just Excel pivot tables in a web interface.

(b) In module 3, the assignment tasks us with designing a data warehouse through the combination of a database and an unstructured Excel file. In real business settings, Excel files created and maintained by users should never be used as sources for operational databases/data warehouses, especially by combining them with data produced and maintained by operational IT systems.

(c) In module 5, the Pentaho assignment tasks us with loading Excel and Access files to a database. Data integration tools in real life are used to combine data sources coming from different IT systems and combining them into a single (Or multiple) data warehouse. The process of loading data from a file into a database is a trivial task, and is not handled by tools such as Pentaho. Thus, I think a more representative example should be used to demonstrate the tool's usage.

Topics that I would like to see covered in a course such as this:

(a) More in depth presentation of relational data warehouse schema design.

(b) Presentation of different types of data integration and use cases for each (Batch vs real time).

(c) Presentation of modern data engineering tools, e.g. cloud data warehouse offerings (Amazon Redshift, Google BigQuery, Snowflake, e.tc.), data integration tools (Apache Kafka, Apache Airflow), infrastructure as code tools (Ansible, Terraform, e.tc.) and their usage in data warehouse implementations, programming languages used for data pipeline design (Python, Scala, e.tc.), NoSQL databases and their usage in data engineering.

創建者 Minas-Marios V

2020年10月17日

This course has plenty room for improvement. On one hand, it provides a good understanding of the different data warehousing architectures and design principles, an essential foundation to anyone interested in the field. The material on data integration is also excellent, along with the associated assignment. On the other hand, the peer-graded assignment on data warehousing design is very demanding and isn't clearly described from the lectures and practice problems what the students ought to do to get a perfect grade. Installing the software and getting it to work is also a skill on its own, but it truly is something that a professional will encounter in their work!

創建者 Jason L

2016年5月7日

Pros: Information is perfect for anyone looking at Business Intelligence as a career field, or already in the career field itself. I found the first week to challenge my on-the-job knowledge of a fuller set of concepts and general terminology.

Cons: The wording on the quiz questions, in some cases, seems much different than the PPT slides and the instructor's language. UPDATE: The wording is a significant challenge, even when advancing into the more complex topics. I have had many differences of opinions on the solutions based on wording in the requirements.

創建者 Dragana S

2017年11月13日

Really short lessons, and usually half of lesson is spent on introduction and talking about what will be in the lesson. Nevertheless, course is focused on theory, rather than the practice. I think it should be more detailed and with more practical assignments.

創建者 Linda S

2016年10月4日

Well organized lectures but the documentation is full of errors. This in combination with the lack of response on the a lack of responsiveness on the forums might make this class frustrating for some.

創建者 Tom C

2016年3月19日

This course needs a cleanup of loose ends on some of the assignments. Some assignment requirements are very ambiguous and in some cases the solutions are not matching the requirements of what was due.

創建者 srinivas

2016年3月4日

Real world data warehouse integrations are more complex than just inner joining the tables to drop those rows not found in the original tables. i wish more complex scenarios are covered.

創建者 Shalmoli N

2020年6月8日

Assignments are very good, in fact excellent, but the material could be a bit more descriptive. And the practice exercise of assignment 5 had lots of discrepancy with the actual

創建者 Automation L T

2022年6月15日

I think there is still missing purpose on some explanations, for example, in the last assignment there was requested something we never learned during the course.

創建者 Andy O

2018年1月28日

Some good parts on data integration but the key sections on DW design and in particular the assignment are really poorly written.

創建者 Rohan G L

2021年5月19日

Needs serious updates. A lot of good information, but assignments are thrown together, and instructions are often not clear.