Data Warehousing

Data Warehousing

About The Course Course Topic Overview and Description: A data warehouse (DW) is a database used for reporting. The data is uploaded from the operational systems and may pass through an operational data store for additional processes before it is used in the data warehouse for reporting. This introductory course will discuss its benefits and concepts, the twelve rules which should be followed, the lifecycle of data that is warehoused, the flow and the architecture of data warehouse. It will also teach learners the applications of data warehousing, its challenges and its future. Requirements Basic understanding of the IT Industry Knowledge of the English language Benefits of taking this course: Introduction of to the data warehouse, its advantages & disadvantages Know the concepts, lifecycle and rules of the data warehouse Importance and techniques of data warehouse modeling Recognize the different applications of data warehousing The course is for 5 days. Various instructional methods will be used to teach the objectives mentioned above. The training method would be completely interactive and participative. Students will receive course materials which will be discussed during class. Who Should Attend: This course is designed for recent graduates looking to get a foothold in the IT industry. Finance professionals wanting to learn about Data Warehouses for reporting and analysis purposes. IT professionals wanting to learn more about data storage, data warehousing modeling, or data warehousing applications. Related Job Functions: Data Warehousing & Analytics Consultant Data Warehousing/Business Intelligence Developer Data Warehouse Engineer Warehouse Manager Course Delivery: The course will be delivered using formal lectures combined with questions based on the topics. The class will be conducted both online and in-person. 

    

Day 1

  • Introduction
  • Definition
  • History of Data Warehousing
  • Advantages & Disadvantages
  • Benefits of Data Warehousing
  • Online Transaction Processing
  • Data Store
  • Data Mart
  • Design Schemas
  • Meta Data 

Day 2

  • Data Webhouse and Data Warehousing Queries
  • Extract, Transform, Load
  • Data Warehouse Lifecycle
  • Design
  • Prototype
  • Deploy
  • Operate
  • Enhance
  • Data Warehouse Cycle of Cycles
  • First, Second, Third, & Fourth Loop

Day 3

  • Related Factors
  • Rules of Data Warehouse
  • Data Warehouse Architecture
  • Key Components
  • Benefits of Data Warehouse Architecture
  • Typical Architecture of Data Warehousing
  • Common Architecture
  • Data Warehouse Information Flow
  • Importance of Data Modeling
  • Data Modeling Techniques

Day 4

  • Entity-Relationship Modeling
  • Limitations of ER
  • Dimensional Modeling
  • Benefits of Dimensional Modeling
  • Data Warehouse Application
  • Retail Industry
  • Manufacturing and Distribution
  • Bank
  • Insurance Company
  • Health Care Providers

Day 5

  • Government Agencies
  • Internet Companies
  • Telecommunications
  • Sports
  • Challenges to Data Warehousing
  • Ensuring Data Quality
  • Ensuring Performance
  • Testing the Data Warehouse
  • Reconciliation of Data
  • User Acceptance
  • Future of Data Warehouse
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