À propos de ce cours
4.5
656 notes
130 avis
100 % en ligne

100 % en ligne

Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Dates limites flexibles

Dates limites flexibles

Réinitialisez les dates limites selon votre disponibilité.
Heures pour terminer

Approx. 18 heures pour terminer

Recommandé : 5 hours/week...
Langues disponibles

Anglais

Sous-titres : Anglais

Compétences que vous acquerrez

Extraction, Transformation And Loading (ETL)PentahoData IntegrationData Warehouse
100 % en ligne

100 % en ligne

Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Dates limites flexibles

Dates limites flexibles

Réinitialisez les dates limites selon votre disponibilité.
Heures pour terminer

Approx. 18 heures pour terminer

Recommandé : 5 hours/week...
Langues disponibles

Anglais

Sous-titres : Anglais

Programme du cours : ce que vous apprendrez dans ce cours

Semaine
1
Heures pour terminer
4 heures pour terminer

Data Warehouse Concepts and Architectures

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 historical reasons for development of data warehouse technology, learning effects, business architectures, maturity models, project management issues, market trends, and employment opportunities. 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 the software this week before assignments begin in week 2....
Reading
8 vidéos (Total 53 min), 15 lectures, 1 quiz
Video8 vidéos
Course objectives video lecture4 min
Course topics and assignments video lecture4 min
Motivation and characteristics video lecture8 min
Learning effects for data warehouse development video lecture9 min
Data warehouse architectures and maturity video lecture10 min
Data Warehouse Examples video lecture9 min
Employment opportunities video lecture6 min
Reading15 lectures
Powerpoint lecture notes for lesson 110 min
Optional textbook10 min
Powerpoint lecture notes for lesson 210 min
Powerpoint lecture notes for lesson 310 min
Powerpoint lecture notes for lesson 410 min
Powerpoint lecture notes for lesson 510 min
Powerpoint lecture notes for lesson 610 min
Powerpoint lecture notes for lesson 710 min
Overview of software requirements10 min
Pivot4J installation10 min
Pentaho Data Integration installation10 min
Overview of database software installation10 min
Oracle installation notes10 min
Making connections to a local Oracle database10 min
Optional textbook reading material10 min
Quiz1 exercices pour s'entraîner
Module 1 quiz30 min
Semaine
2
Heures pour terminer
3 heures pour terminer

Multidimensional Data Representation and Manipulation

Now that you have the informational context for data warehouse development, you’ll start using data warehouse tools! In module 2, you will learn about the multidimensional representation of a data warehouse used by business analysts. You’ll apply what you’ve learned in practice and graded problems using WebPivotTable or Pivot4J, open source tools for manipulating pivot tables. At the end of this module, you will have solid background to communicate and assist business analysts who use a multidimensional representation of a data warehouse....
Reading
7 vidéos (Total 45 min), 9 lectures, 1 quiz
Video7 vidéos
Data cube operators video lecture6 min
Overview of Microsoft MDX video lecture6 min
Microsoft MDX statements video lecture6 min
Overview of Pivot4J video lecture6 min
Overview of WebPivotTable video lecture4 min
Pivot4J software demonstration video lecture5 min
Reading9 lectures
Powerpoint lecture notes for lesson 110 min
Powerpoint lecture notes for lesson 210 min
Powerpoint lecture notes for lesson 310 min
Powerpoint lecture notes for lesson 410 min
Powerpoint lecture notes for lesson 510 min
Powerpoint lecture notes for lesson 610 min
Optional textbook reading material10 min
Pentaho Pivot4J tutorial10 min
WebPivotTable Tutorial10 min
Quiz1 exercices pour s'entraîner
Module 2 quiz20 min
Heures pour terminer
4 heures pour terminer

Multidimensional Data Representation and Manipulation: Lesson Choices

Choice 1: If completing this assignment, you should also complete the WebPivotTable quiz. | Choice 3: If completing this assignment, you should also complete the Pivot4J quiz....
Reading
4 quiz
Quiz2 exercices pour s'entraîner
Quiz for module 2 assignment - WebPivotTable
Quiz for module 2 assignment - Pivot4J26 min
Semaine
3
Heures pour terminer
4 heures pour terminer

Data Warehouse Design Practices and Methodologies

This module emphasizes data warehouse design skills. Now that you understand the multidimensional representation used by business analysts, you are ready to learn about data warehouse design using a relational database. In practice, the multidimensional representation used by business analysts must be derived from a data warehouse design using a relational DBMS.You will learn about design patterns, summarizability problems, and design methodologies. You will apply these concepts to mini case studies about data warehouse design. At the end of the module, you will have created data warehouse designs based on data sources and business needs of hypothetical organizations....
Reading
6 vidéos (Total 47 min), 8 lectures, 2 quiz
Video6 vidéos
Table design patterns video lecture8 min
Summarizability patterns for dimension tables video lecture6 min
Summarizability patterns for dimension-fact relationships video lecture6 min
Mini case for data warehouse design video lecture8 min
Data warehouse design methodologies video lecture8 min
Reading8 lectures
Powerpoint lecture notes for lesson 110 min
Powerpoint lecture notes for lesson 210 min
Powerpoint lecture notes for lesson 310 min
Powerpoint lecture notes for lesson 410 min
Powerpoint lecture notes for lesson 510 min
Powerpoint lecture notes for lesson 610 min
Practice problems for module 310 min
Optional textbook reading material10 min
Quiz1 exercices pour s'entraîner
Module 3 quiz20 min
Semaine
4
Heures pour terminer
2 heures pour terminer

Data Integration Concepts, Processes, and Techniques

Module 4 extends your background about data warehouse development. After learning about schema design concepts and practices, you are ready to learn about data integration processing to populate and refresh a data warehouse. The informational background in module 4 covers concepts about data sources, data integration processes, and techniques for pattern matching and inexact matching of text. Module 4 provides a context for the software skills that you will learn in module 5. ...
Reading
6 vidéos (Total 48 min), 7 lectures, 1 quiz
Video6 vidéos
Change data concepts video lecture7 min
Data cleaning tasks video lecture5 min
Pattern matching with regular expressions video lecture9 min
Matching and consolidation video lecture8 min
Quasi identifiers and distance functions for entity matching video lecture7 min
Reading7 lectures
Powerpoint lecture notes for lesson 110 min
Powerpoint lecture notes for lesson 210 min
Powerpoint lecture notes for lesson 310 min
Powerpoint lecture notes for lesson 410 min
Powerpoint lecture notes for lesson 510 min
Powerpoint lecture notes for lesson 610 min
Optional reading material10 min
Quiz1 exercices pour s'entraîner
Module 4 quiz30 min
4.5
130 avisChevron Right
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Meilleurs avis

par EKDec 16th 2015

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.

par MHDec 13th 2016

Good learning for Data integration and ETL learning. How data from source to target table transform over the business requirement to be ready for processing

Enseignants

Avatar

Michael Mannino

Associate Professor
Business School, University of Colorado Denver

À propos de 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....

À propos de la Spécialisation Data Warehousing for Business Intelligence

Evaluate business needs, design a data warehouse, and integrate and visualize data using dashboards and visual analytics. This Specialization covers data architecture skills that are increasingly critical across a broad range of technology fields. You’ll learn the basics of structured data modeling, gain practical SQL coding experience, and develop an in-depth understanding of data warehouse design and data manipulation. You’ll have the opportunity to work with large data sets in a data warehouse environment to create dashboards and Visual Analytics. You will use of MicroStrategy, a leading BI tool, OLAP (online analytical processing) and Visual Insights capabilities to create dashboards and Visual Analytics. In the final Capstone Project, you’ll apply your skills to build a small, basic data warehouse, populate it with data, and create dashboards and other visualizations to analyze and communicate the data to a broad audience....
Data Warehousing for Business Intelligence

Foire Aux Questions

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