18c Data Warehousing Concepts

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

Wellington

05 Apr - 05 Apr

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
  • Good working knowledge of the SQL language
  • Knowledge of client-server and relational server technology
  • 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

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

    Overview of Data Warehouse and Multi-Dimensional Model Concepts

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

    About Business, Logical, Dimensional, and Physical Models

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

    Introduction to Extracting, Transforming, Loading Data

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

    Introduction to Data Warehousing Platforms and Tools

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