DASVM’s Data Warehousing Training will cover concepts like DW Architecture, Data Modeling,  Data integration, ERwin, ETL fundamentals, Business Reporting and Data Visualisation. This Data Warehousing & BI Certification Training will help you become a expert in Data Warehousing and Business Intelligence techniques.

Data warehousing is the process of centralising, cleaning, and transforming data from multiple sources into a unified repository for analytical purposes It plays a pivotal role in collecting, storing, and managing vast amounts of data, enabling organisations to make informed decisions. This course provides delegates with a comprehensive understanding of data warehousing, including its significance in data analytics, business intelligence, and decision-making processes.

Course Objectives:

At the end of the Data Warehousing Training the participants should be able to:

• To understand the core concepts and principles of data warehousing
• To learn how to design and implement an effective data warehousing system
• To explore data modelling techniques for data warehousing
• To gain proficiency in ETL processes and tools
• To acquire knowledge of data warehouse management and maintenance
• To analyse real-world case studies to apply data warehousing principles
• To collaborate with peers to solve practical data warehousing challenges
• To prepare for real-world data warehousing scenarios and challenges
• Understand Data Warehousing and Business Intelligence concepts
• Use ERwin r9 for developing the Data Warehouse and Data Marts building with Staging Area
• Create Dimensions and Facts tables with Granularity
• Use ETL Tool Talend 5.x for loading the data into staging and warehouse/data marts for various Data Migration, Replication and Integration Projects
• Use BI Tool Tableau 9.x for building and managing the operational and Analytical reports with dashboards

Course content

Introduction to Data Warehouse

• What is Data Warehousing?
• Features of Data Warehouse
• Types of Data Warehouse
• Components of Data Warehouse
• Use of Data Warehouse
• Advantages of Data Warehouse
• Disadvantages of Data Warehouse
• Data Warehouse Tools
• Data Warehouse Applications
• Integrating Heterogeneous Databases

Terminologies 

• Metadata
• Metadata Repository
• Data Cube
• Data Mart
• Virtual Warehouse

Architecture of Data Warehouse

• Understanding the Data Warehousing Architecture
• System used for Reporting and Business Intelligence
• Three-Tier Data Warehouse Architecture
• Data Warehouse Models
• Load, Warehouse, and Query Manager
• Understanding OLAP vs. OLTP
• Introduction to Cubes

Dimensions and Facts

• Facts
• Dimensions

Data Modelling

• Data Warehouse Modelling Overview
• ER Diagram
• The various stages from Conceptual Model
• Logical Model to Physical Schema
• Understanding the Cubes
• Benefits of Cube
• Working with OLAP multidimensional Cube
• Creating Report using a Cube

Data Normalization 

• What is Data Normalization?
• Data Normalization Rules – 1NF, 2NF, 3NF, Data De-Normalization
• Dimensional Modeling – What is DM?, Principles, Benefits, Type and Technique.
• Understanding the process of Data Normalization
• Rules of normalization for first, second and third normal, BCNF, deploying Erwin for generating SQL scripts

Delivery Process

• Delivery Method
• IT Strategy
• Education and Prototyping
• Technical Blueprint

System Processes

• Process Flow in Data Warehouse
• Extract and Load Process
• Clean and Transform Process
• Backup and Archive the Data

SQL Parsing, Cubes & OLAP 

• SQL parsing
• Compilation and optimization
• Understanding types and scope of cubes
• Data Warehousing Vs. Cubes
• Limitations of Cubes and evolution of in-memory analytics

Data Warehouse OLAP 

• Types of OLAP Servers
• OLAP Operations
• OLAP Vs OLTP

Relational and Multidimensional OLAP 

• Relational OLAP
• Multidimensional OLAP
• Three-Tier Data Warehouse Architecture

Data Warehouse Schemas 

• Star Schema
• Snowflake Schema
• Fact Constellation Schema
• Schema Definition

Horizontal and Vertical Partitioning 

• Introduction to Partitioning
• Horizontal Partitioning
• Vertical Partitioning

Metadata Concepts

• Metadata Categories
• Role of Metadata

System and Process Managers 

• System Managers
• Process Managers

Security and Backup

• Security Requirements
• User Access
• Impact of Security on Design
• Hardware and Software Backup

Tuning and Testing

• Tuning
• Testing

Building Data Warehouse with ERwin

• Source System Understanding
• Future Data Requirement and Understanding
• Designing and Developing Dimension Table
• Designing and Developing Fact Table Designing and Developing ER Model With Erwin
• Designing and Developing Entity Relationship Modeling

Building ETL Project With Talend DI Open Studio 5.x

• Building ETL Project Talend DI Open Studio
• Understanding the Data Source System which will be a future Data Requirement
• Identify Business Requirement Gathering
• Building the ETL Talend Technical Design Document
• Building an ETL Project

Introduction to Data Visualization BI Tool Tableau 9.x

• Data Visualization BI Tool : Tableau 9.x-Introduction to Data Visualization with Tableau
• Exploring Data Visualization with Tableau
• What is Data Visualization?
• Exporting Data and Working With Tableau

Building Data Visualization BI Project With Tableau 9.x

• Building Data Visualization BI Project With Tableau 9.x
• BI Reporting Understanding
• Report and Dashboard Template Document
• Tableau Design and Development Database Source Connection

An Integrated Data Warehousing & BI Project

• An Integrated Data Warehousing & BI Project
• Developing a Data Warehouse and BI Project
• Source System understanding today’s data that will be the future  data requirement
• Identify the Business Requirement Gathering
• Report and Dashboard Template Document
• Designing and Developing Models
• Designing and Developing the Staging Area
• Finalizing the Dimension Modeling Type
• Designing and Developing Dimension Modeling

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