18c Data Warehousing Concepts

Course Fees: $1278.00 excl. GST
Printed Manual: $45.00 excl. GST
Course Duration: 1 days
Course Manual

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This course describes the evolution of information management systems. You are introduced to data warehousing and business intelligence, and their role in data analytics. You also get a brief introduction to modern data analytic technologies like machine learning, artificial intelligence (AI) and big data. The students learn to define the Data Warehouse concepts and terminology with focus on Analytic Views. They gain knowledge about the basics of data modelling and the different techniques used for data modelling. Towards the end of the course, they get introduced to the ETL and EL-T processes for extracting, transforming, and loading data in a Data Warehouse.

Learn To:

  • Describe the evolution of information management systems.
  • Identify the need for Data Warehousing and information management in real time business scenarios.
  • Define Data Warehousing and BI, related concepts and terminology.
  • Understand the limitations of Data Warehousing for prescriptive analysis and the evolution of Big Data.
  • Define different techniques of data modeling used with Data Warehousing.
  • Describe the process of extraction, transformation, and loading with reference to ETL and EL-T methodologies.
  • Explain multi-dimensional model and analytic views.

Prerequisites

Suggested Prerequisite

  • Oracle Database 12c: Analytic SQL for Data Warehousing Ed 1
  • Good working knowledge of the SQL language
  • Knowledge of client-server and relational server technology

Required Prerequisite

  • There are no required pre-requisites for this course
  • Data Warehouse Analyst
  • Data Modelers
  • Data Warehouse Developer
  • Data Scientist
  • Data Analyst
  • Data Warehouse Administrator
Oracle Database 11g: Data Warehousing Fundamentals
  • Explain the different data modelling techniques for data warehousing
  • Describe methods and tools for extracting, transforming, and loading data
  • Discuss the different Oracle tools to implement data warehousing on-premise
  • Discuss Autonomous Data Warehouse Cloud (ADWC) and Data Integration Platform Cloud (DIPC)
  • Define the terminology and explain the basic concepts of data warehousing
  • Describe the analytic views and multi-dimensional model
  • Introduce machine learning, artificial intelligence, and big data

Course Overview

    Evolution of Information Management and Data Warehousing

    • Evolution of Information Management
    • Data Warehousing and Business Intelligence (DW & BI)
    • Machine Learning and Artificial Intelligence
    • Big Data

    Overview of Data Warehouse and Multi-Dimensional Model Concepts

    • Data Warehouse Definition and Characteristics
    • Data Warehouse Architectures
    • Data Warehouse Development Approaches
    • Data Warehousing Process Components
    • Analytic Views and Multi-Dimensional Model

    About Business, Logical, Dimensional, and Physical Models

    • Data Warehouse Modeling Issues
    • Data Warehouse Design Phases
    • Defining the Business Model
    • Designing the Logical Model
    • Defining the Dimensional Model
    • Defining the Physical Model

    Introduction to Extracting, Transforming, Loading Data

    • Extraction, Transformation, and Loading (ETL) Process
    • Extraction, Loading, and Transformation (E-LT) Process
    • ETL: Tasks, Importance, and Cost
    • Examining Data Sources
    • Extraction Methods and Techniques
    • Transforming Data
    • Transformation Techniques
    • Loading Data into the Warehouse

    Introduction to Data Warehousing Platforms and Tools

    • Data Warehousing Platforms
    • Data Warehousing On-Premise
    • Data Warehousing in Cloud