Data Modelling for BI Administrators - Fudgelearn

Data Modelling for BI Administrators

Date
Time
Price
18-May-2020
03:00 PM BST - 11:00 AM BST
£ 998
Date
Time
Price
Location
Date
Start time
Price
Location
Version title
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In this Data Modelling for BI Administrators course you will learn how to use Data Modeler to create data models from various source types, such as star and snowflakes.A data model is a design that presents business data for analysis in a manner that reflects the structure of the business. Data models enable analysts to structure queries in the same intuitive fashion as they ask business questions.

Learn How To:

  • Create and Configure the Oracle Analytics Cloud instance on Oracle Cloud
  • Configure the Prerequisites for Provisioning the OAC
  • Create the Data Model in OAC 
  • Add Fact and Dimension tables to a Data Model
  • Publish the Data Model in OAC
  • Add Measures and attributes to a Data Model
  • Define the Hierarchies and levels to Drill and Aggregate a Model
  •  Create variables ,Derived attributes  and Securing the Data Model
  •  Troubleshoot in Data Models

Benefits to You:

As a business analyst, learn to build data models to present data for analysis that better reflects the structure of the business using Oracle Analytics Cloud.

  • Analyst
  • Business Analyst
  • Data Analyst


  • Understand Data Models and its components
  • Learn to use data modeler
  • Learn to create source views
  • Learn to create a Time Dimension
  • Learn to define Hierarchies and Levels to Drill and Aggregate
  • Learn to secure your data model

    Introduction to Data Modeler

    • Explain Data Modeler and its components
    • Explain Star Relationships and Snowflake Relationships
    • Explain Normalized Sources and Modelling Denormalized Sources
    • Analyze the Workflow of Modeling the Data
    • Launch Data Modeler
    • Create a Data Model
    • Explore Data sources and Create Source Views
    • Manage database connections for a Data Model and Rename a Data Model

    Add Fact and Dimension Tables to a Data Model

    • Describe Dimension and Fact tables
    • Create Fact and Dimension tables from a Single table or view
    • Join Fact  and Dimension tables
    • Synchronize the Data Model with source objects in the database
    • Create a Time dimension

    Publishing and testing the Data Model

    • Validate a Data Model
    • Refresh a Data Model 
    • Publish a Data Model
    • Export, Import and Delete a Data Model 
    • Build Visualization for model testing

    Add Measures and Attributes to a Data Model

    • Edit Measures and Attributes
    • Specify Aggregation for Measures in Fact Tables
    • Create calculated Measures
    • Create Derived Attributes 
    • Create Expressions in the Expression Editor 
    • Copy Measures, Attributes and Model Objects

    Define Hierarchies and Levels to Drill and Aggregate to a Model 

    • Describe Hierarchies and Levels
    • Understand the typical workflow to define Hierarchies and Levels
    • Create Hierarchies 
    • Edit Hierarchies and Levels
    • Set Aggregation Levels for Measures

    Creating Variables , Derived Attributes and Securing the Data Model

    • Secure a Data Model
    • Create Variables to Use in Expressions
    • Secure Access to Objects in a Model
    • About Secure Access Data

    Troubleshooting in Data Models

    • Data Modelling Errors and Solutions to handle errors in Data Model
    • General Errors and Solutions to handle the errors
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    £ 998
    2 Days
    Live Virtual Class
    1 Event available
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    Data Modelling for BI Administrators

    Course Overview

    In this Data Modelling for BI Administrators course you will learn how to use Data Modeler to create data models from various source types, such as star and snowflakes.A data model is a design that presents business data for analysis in a manner that reflects the structure of the business. Data models enable analysts to structure queries in the same intuitive fashion as they ask business questions.

    Learn How To:

    • Create and Configure the Oracle Analytics Cloud instance on Oracle Cloud
    • Configure the Prerequisites for Provisioning the OAC
    • Create the Data Model in OAC 
    • Add Fact and Dimension tables to a Data Model
    • Publish the Data Model in OAC
    • Add Measures and attributes to a Data Model
    • Define the Hierarchies and levels to Drill and Aggregate a Model
    •  Create variables ,Derived attributes  and Securing the Data Model
    •  Troubleshoot in Data Models

    Benefits to You:

    As a business analyst, learn to build data models to present data for analysis that better reflects the structure of the business using Oracle Analytics Cloud.

    Virtual Class
    2 Days
    Date
    Start time
    Price
    Location
    18-May-2020
    03:00 PM BST
    £ 998
    Live Virtual Class
    Audience
    • Analyst
    • Business Analyst
    • Data Analyst


    Objectives
    • Understand Data Models and its components
    • Learn to use data modeler
    • Learn to create source views
    • Learn to create a Time Dimension
    • Learn to define Hierarchies and Levels to Drill and Aggregate
    • Learn to secure your data model
    Topics

      Introduction to Data Modeler

      • Explain Data Modeler and its components
      • Explain Star Relationships and Snowflake Relationships
      • Explain Normalized Sources and Modelling Denormalized Sources
      • Analyze the Workflow of Modeling the Data
      • Launch Data Modeler
      • Create a Data Model
      • Explore Data sources and Create Source Views
      • Manage database connections for a Data Model and Rename a Data Model

      Add Fact and Dimension Tables to a Data Model

      • Describe Dimension and Fact tables
      • Create Fact and Dimension tables from a Single table or view
      • Join Fact  and Dimension tables
      • Synchronize the Data Model with source objects in the database
      • Create a Time dimension

      Publishing and testing the Data Model

      • Validate a Data Model
      • Refresh a Data Model 
      • Publish a Data Model
      • Export, Import and Delete a Data Model 
      • Build Visualization for model testing

      Add Measures and Attributes to a Data Model

      • Edit Measures and Attributes
      • Specify Aggregation for Measures in Fact Tables
      • Create calculated Measures
      • Create Derived Attributes 
      • Create Expressions in the Expression Editor 
      • Copy Measures, Attributes and Model Objects

      Define Hierarchies and Levels to Drill and Aggregate to a Model 

      • Describe Hierarchies and Levels
      • Understand the typical workflow to define Hierarchies and Levels
      • Create Hierarchies 
      • Edit Hierarchies and Levels
      • Set Aggregation Levels for Measures

      Creating Variables , Derived Attributes and Securing the Data Model

      • Secure a Data Model
      • Create Variables to Use in Expressions
      • Secure Access to Objects in a Model
      • About Secure Access Data

      Troubleshooting in Data Models

      • Data Modelling Errors and Solutions to handle errors in Data Model
      • General Errors and Solutions to handle the errors