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Ca. 18 Stunden zum Abschließen

Empfohlen: 6 hours/week...

Englisch

Untertitel: Englisch

Kompetenzen, die Sie erwerben

Extraction, Transformation And Loading (ETL)PentahoData IntegrationData Warehouse

100 % online

Beginnen Sie sofort und lernen Sie in Ihrem eigenen Tempo.

Flexible Fristen

Setzen Sie Fristen gemäß Ihrem Zeitplan zurück.

Ca. 18 Stunden zum Abschließen

Empfohlen: 6 hours/week...

Englisch

Untertitel: Englisch

Lehrplan - Was Sie in diesem Kurs lernen werden

Woche
1
4 Stunden zum Abschließen

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.

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8 Videos (Gesamt 53 min), 15 Lektüren, 1 Quiz
8 Videos
Motivation and characteristics video lecture8m
Learning effects for data warehouse development video lecture9m
Data warehouse architectures and maturity video lecture10m
Data Warehouse Examples video lecture9m
Employment opportunities video lecture6m
15 Lektüren
Powerpoint lecture notes for lesson 110m
Optional textbook10m
Powerpoint lecture notes for lesson 210m
Powerpoint lecture notes for lesson 310m
Powerpoint lecture notes for lesson 410m
Powerpoint lecture notes for lesson 510m
Powerpoint lecture notes for lesson 610m
Powerpoint lecture notes for lesson 710m
Overview of software requirements10m
Pivot4J installation10m
Pentaho Data Integration installation10m
Overview of database software installation10m
Oracle installation notes10m
Making connections to a local Oracle database10m
Optional textbook reading material10m
1 praktische Übung
Module 1 quiz30m
Woche
2
3 Stunden zum Abschließen

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. After completing this module, you should proceed to module 3 to complete an assignment and quiz with either WebPivotTable or Pivot4J. Because Pivot4J can be difficult to install, I recommend completing the assignment and quiz using WebPivotTable.

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7 Videos (Gesamt 45 min), 9 Lektüren, 1 Quiz
7 Videos
Microsoft MDX statements video lecture6m
Overview of Pivot4J video lecture6m
Overview of WebPivotTable video lecture4m
Pivot4J software demonstration video lecture5m
9 Lektüren
Powerpoint lecture notes for lesson 110m
Powerpoint lecture notes for lesson 210m
Powerpoint lecture notes for lesson 310m
Powerpoint lecture notes for lesson 410m
Powerpoint lecture notes for lesson 510m
Powerpoint lecture notes for lesson 610m
Optional textbook reading material10m
Pentaho Pivot4J tutorial10m
WebPivotTable Tutorial10m
1 praktische Übung
Module 2 quiz20m
4 Stunden zum Abschließen

Multidimensional Data Representation and Manipulation: Lesson Choices

Choice 1 and 2: If completing the WebPivotTable assignment (choice 1), you should also complete the WebPivotTable quiz (choice 2). | Choice 3 and 4: If completing the Pivot4J assignment (choice 3), you should also complete the Pivot4J quiz (choice 4). Due to potential difficulty with installing Pivot4J, I recommend that you complete the WebPivotTable assignment and quiz.

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4 Quiz
2 praktische Übungen
Quiz for module 2 assignment - WebPivotTable
Quiz for module 2 assignment - Pivot4J26m
Woche
3
4 Stunden zum Abschließen

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.

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6 Videos (Gesamt 47 min), 8 Lektüren, 2 Quiz
6 Videos
Summarizability patterns for dimension-fact relationships video lecture6m
Mini case for data warehouse design video lecture8m
Data warehouse design methodologies video lecture8m
8 Lektüren
Powerpoint lecture notes for lesson 110m
Powerpoint lecture notes for lesson 210m
Powerpoint lecture notes for lesson 310m
Powerpoint lecture notes for lesson 410m
Powerpoint lecture notes for lesson 510m
Powerpoint lecture notes for lesson 610m
Practice problems for module 310m
Optional textbook reading material10m
1 praktische Übung
Module 3 quiz20m
Woche
4
2 Stunden zum Abschließen

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.

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6 Videos (Gesamt 48 min), 7 Lektüren, 1 Quiz
6 Videos
Pattern matching with regular expressions video lecture9m
Matching and consolidation video lecture8m
Quasi identifiers and distance functions for entity matching video lecture7m
7 Lektüren
Powerpoint lecture notes for lesson 110m
Powerpoint lecture notes for lesson 210m
Powerpoint lecture notes for lesson 310m
Powerpoint lecture notes for lesson 410m
Powerpoint lecture notes for lesson 510m
Powerpoint lecture notes for lesson 610m
Optional reading material10m
1 praktische Übung
Module 4 quiz30m
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Top reviews from Data Warehouse Concepts, Design, and Data Integration

von 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.

von 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

Dozent

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Michael Mannino

Associate Professor
Business School, University of Colorado Denver

Über 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....

Über die Spezialisierung 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

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