Relational Database Support for Data Warehouses is the third course in the Data Warehousing for Business Intelligence specialization. In this course, you'll use analytical elements of SQL for answering business intelligence questions. You'll learn features of relational database management systems for managing summary data commonly used in business intelligence reporting. Because of the importance and difficulty of managing implementations of data warehouses, we'll also delve into storage architectures, scalable parallel processing, data governance, and big data impacts. In the assignments in this course, you can use either Oracle or PostgreSQL.
von


Über diesen Kurs
Karriereergebnisse der Lernenden
33%
17%
20%
Kompetenzen, die Sie erwerben
Karriereergebnisse der Lernenden
33%
17%
20%
von

University of Colorado System
The University of Colorado is a recognized leader in higher education on the national and global stage. We collaborate to meet the diverse needs of our students and communities. We promote innovation, encourage discovery and support the extension of knowledge in ways unique to the state of Colorado and beyond.
Lehrplan - Was Sie in diesem Kurs lernen werden
DBMS Extensions and Example Data Warehouses
Module 1 introduces the course and covers concepts that provide a context for the remainder of this course. In the first two lessons, you’ll understand the objectives for the course and know what topics and assignments to expect. In the remaining lessons, you will learn about DBMS extensions, a review of schema patterns, data warehouses used in practice problems and assignments, and examples of data warehouses in education and health care. This informational module will ensure that you have the background for success in later modules that emphasize details and hands-on skills.You should also read about the software requirements in the lesson at the end of module 1. I recommend that you try to install Oracle or PostgreSQL this week before assignments begin in week 2. If you have taken other courses in the specialization, you may already have installed Oracle or PostgreSQL.
SQL Subtotal Operators
Now that you have the informational context for relational database support of data warehouses, you’ll start using relational databases to write business intelligence queries! In module 2, you will learn an important extension of the SQL SELECT statement for subtotal operators. You’ll apply what you’ve learned in practice and graded problems using Oracle SQL for problems involving the CUBE, ROLLUP, and GROUPING SETS operators. Because the subtotal operators are part of the SQL standard, your learning will readily apply to other enterprise DBMSs. At the end of this module, you will have solid background to write queries using the SQL subtotal operators as a data warehouse analyst.
SQL Analytic Functions
After your experience using the SQL subtotal operators, you are ready to learn another important SQL extension for business intelligence applications. In module 3, you will learn about an extended processing model for SQL analytic functions that support common analysis in business intelligence applications. You’ll apply what you’ve learned in practice and graded problems using Oracle SQL for problems involving qualitative ranking of business units, window comparisons showing relationships of business units over time, and quantitative contributions showing performance thresholds and contributions of individual business units to a whole business. Because analytic functions are part of the SQL standard, your learning will apply to other enterprise DBMSs. At the end of this module, you will have solid background to write queries using the SQL analytic functions as a data warehouse analyst.
Materialized View Processing and Design
After acquiring query formulation skills for development of business intelligence applications, you are ready to learn about DBMS extensions for efficient query execution. Business intelligence queries can use lots of resources so materialized view processing and design has become an important extension of DBMSs. In module 4, you will learn about an SQL statement for creating materialized views, processing requirements for materialized views, and rules for rewriting queries using materialized views. To gain insight about the complexity of query rewriting, you will practice rewriting queries using materialized views. To provide closure about relational database support for data warehouses, you will learn about about Oracle tools for data integration, the Oracle Data Integrator, along with two SQL statements useful for specific data integration tasks. After this module, you will have a solid background to use materialized views to improve query performance and deploy the Extraction, Loading, and Transformation approach for data integration as a data warehouse administrator or analyst.
Bewertungen
Top-Bewertungen von RELATIONAL DATABASE SUPPORT FOR DATA WAREHOUSES
Awesome content ,very well drafted and explained course content. I am thankful to the coursera team, who has discovered such kind of really good course and specialization.
Excellent Contents for concepts explained with sample queries and assignments. It is really amazing to go thru all the new concepts within such a short time frame.
Very good course with good quizzes. Although some questions were repeated in more than 1 quiz but still an awesome course to take. Nice collection of assignments!
Great Course for learning for materialized views using business intelligence concepts. Assignments and quiz also helps us to learn a lot.
Über den Spezialisierung Data Warehousing for Business Intelligence
Evaluate business needs, design a data warehouse, and integrate and visualize data using dashboards and visual analytics.

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