Data Warehousing and Business Intelligence
This course builds on “The Nature of Data and Relational Database Design” to extend the process of capturing and manipulating data through data warehousing and data mining. Once the transactional data is processed through ETL (Extract, Transform, Load), it is then stored in a data warehouse for use in managerial decision making. Data mining is one of the key enablers in the process of converting data stored in a data warehouse into actionable insight for better and faster decision making.
Monthly Subscription Starting at AED 99 + VAT
- Level Foundation
- Duration 7 hours
- Course by University of California, Irvine
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Offered by
About
This course builds on “The Nature of Data and Relational Database Design” to extend the process of capturing and manipulating data through data warehousing and data mining. Once the transactional data is processed through ETL (Extract, Transform, Load), it is then stored in a data warehouse for use in managerial decision making. Data mining is one of the key enablers in the process of converting data stored in a data warehouse into actionable insight for better and faster decision making. By the end of this course, students will be able to explain data warehousing and how it is used for business intelligence, explain different data warehousing architectures and multidimensional data modeling, and develop predictive data mining models, including classification and estimation models. IN addition, students will be able to develop explanatory data mining models, including clustering and association models.Modules
Overview of Data Warehousing
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7
Readings
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1
Discussion
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1
Assignment
1
Assignment
- Module 1 Knowledge Check
1
Discussions
- Activity
7
Readings
- Need for Data Warehousing
- Data Warehousing Architectures
- Extract, Transform, Load (ETL)
- Data Marts
- Operational Data Stores
- Data Warehousing in the Cloud
- Supplemental Resources
Multidimensional Modeling for Data Warehousing
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6
Readings
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1
Discussion
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1
Assignment
1
Assignment
- Module 2 Knowledge Check
1
Discussions
- Activity
6
Readings
- Data Modeling for Data Warehousing
- Multidimensional Data Modeling
- Star Schema
- Snowflake Schema
- NoSQL, Big Data, Data Lakes, and Data Warehousing
- Supplemental Resources
Data Mining for Prediction and Explanation
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5
Readings
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1
Discussion
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1
Assignment
1
Assignment
- Module 3 Knowledge Check
1
Discussions
- Activity
5
Readings
- Overview of Data Mining for BI
- Data Mining Process
- Data Mining Methods
- Data Mining Algorithms for Predictive Modeling
- Supplemental Resources
Data Mining for Clustering and Association
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4
Readings
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1
Discussion
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1
Assignment
1
Assignment
- Module 4 Knowledge Check
1
Discussions
- Dataset Clustering
4
Readings
- Unsupervised Data Mining for Explanatory Modeling
- Clustering and Segmentation
- Association and Market Basket Analysis
- Supplemental Resources
Tim Carrington