Data Warehousing and Data Mining (DWDM)

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Objectives: Students will be enabled to understand and implement classical models and algorithms in data warehousing and data mining. They will learn how to analyze the data, identify the problems, and choose the relevant models and algorithms to apply. They will further be able to assess the strengths and weaknesses of various methods and algorithms and to analyze their behavior.
Syllabus

  • Data warehousing
  • SQL OLAP extensions
  • Multi-dimensional Join
  • Data warehouse performance
  • Data Analysis and Uncertainty
  • Classification and Prediction
  • Cluster Analysis
  • Association rules
Organization
The course organization is divided in two parts that are thaught in parallel: a data warehousing part and a data mining part. The exercises consist in doing a project alone or in groups of 2-3 students (more details below). Textbooks

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SOA Curriculum

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SOA Course Description

Course Introduction


SOA – Service-oriented architecture is an approach that helps systems remain scalable and flexible while growing, and that also helps bridge the business/IT gap. The approach consists of three major elements:
·         Services, which on the one hand represent self-contained business functionalities that can be part of one or more processes, and on the other hand, can be implemented by any technology on any platform.
·         A specific infrastructure, called the enterprise service bus (ESB), that allows us to combine these services in an easy and flexible manner.
·         Policies and processes that deal with the fact that large distributed systems are heterogeneous, under maintenance, and have different owners.

This course is an in-depth discussion of specific technologies, an exploration of implementation issues of SOA development. This course is divided into two parts.

·         In the first part, we study the basis:
Ø  Motivation
Ø  SOA
Ø  Services
Ø  Loose Coupling
Ø  The Enterprise Service Bus
Ø  Service Classification
Ø  Business Process Management
Ø  SOA and the Organization
Ø  SOA in Context
·         The second part, Discusses specific aspects of introducing and running SOA:
Ø  Message Exchange Patterns
Ø  Service Lifecycle
Ø  Versioning
Ø  SOA and Performance
Ø  SOA and Security
Ø  Technical Details
Ø  Web Services
Ø  Service Management
Ø  Model-Driven Service Development
Ø  Establishing SOA and SOA Governance
Ø  Epilogue

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The Complete Guide to Dimensional Modeling Course Description

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Building The Data Warehouse Course Description

Course Introduction

Dimensional modeling has emerged as the only coherent architecture for building distributed data warehouse systems. The core dimensional modeling tech­niques those are the concepts such as slowly changing dimensions, heterogeneous products, factless fact tables, and architected data marts continue to be discussed in data warehouse design workshops around the globe.

This course is started with basic con­cepts and introduce more advanced content as the book unfolds. And later this course will developing the design techniques by example is an extremely effective approach because it allows us to share very tangible guidance. 


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Building The Data WareHouse Curriculum

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Building The Data Warehouse Course Description

 

 

Course Introduction

Data Warehouse - the modern way to build systems is to separate the operational from the informational or analytical processing and data. Today we know with certainty the following:
·         Data warehouses are built under a different development methodology than applications. Not keeping this in mind is a recipe for disaster.
·         Data warehouses are fundamentally different from data marts. The two do not mix—they are like oil and water.
·         Data warehouses deliver on their promise, unlike many overhyped technologies that simply faded away.
·         Data warehouses attract huge amounts of data, to the point that entirely new approaches to the management of large amounts of data are required.

This course is discussions of specific technologies, about the analytical (the decision support systems (DSS)) environment and the structuring of data in that environment, and issues to a guideline for the designer and the developer.

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