دوره حضوری فشرده و کاربردی BI ه Data Warehouse & ETL, OLAP & BI Modeling, Data Mining

پیش نیاز دوره کاربردی BI:

تسلط به SQL Server DB Engine و توان نوشتن گزاره هاي T-SQL

هدف دوره کاربردی BI:

آشنایی با طراحی و پیاده سازی Data Warehouse بصورت Subject Oriented. آشنایی با ابزار SSIS در طراحی و پیاده سازی فرآیند ETL (Extract / Transform / Load) جهت جمع آوری، یکسان سازی، تجمیع و بارگذاری داده ها در انباره داده. آشنایی با ابزار SSAS جهت طراحی و پیاده سازی يك ساختار چند بعدي جهت آناليز داده ها و چگونگی نگارش گزاره هاي تحليلي. آشنايي با ابزارهای پلتفرم مایکروسافت جهت ساخت گزارشات داشبوردي. آشنايي مقدماتي با چگونگي ايجاد ساختارها و مدل هاي داده كاوي جهت انجام تحليل هاي پيشرفته تر.

کاربرد در:

راه اندازی سیستم های BI و ساخت داشبوردهای مدیریتی

مهندس سعید یوسفی، راجع به Business Intelligence توضیحاتی ارائه می نماید که به صورت فایل صوتی قابل استفاده برای علاقه مندان به هوشمندی کسب و کار می باشد. برای دریافت این فایل صوتی به صورت MP3 روی دکمه زیر کلیک کنید.

سرفصل دوره:

Data Warehouse Design - 6 Hours

Understanding BI
Understanding Data Warehouse Design
Stages of Making a BI System
Designing Data Warehouse
OLAP Modeling
Star Schema
Snowflake Schema
Constellation Schema
Designing Dimension
Designing Fact

Extract, Transform & Load Data -15 Hours

Introduction to SSIS
Getting Started
Creating SSIS Packages and Data Sources
Creating and Editing Control Flow Objects
Using the Maintenance Plan Tasks
Using Containers
Sequence Container
For Loop Container
Foreach Loop Container
Using Expressions & Variables
Using Parameters
Working with Precedence Constraints
Loading a Data Warehouse
Data Extraction
Data Transformation
Changing Data Types with the Data Conversion Transform
Creating Columns with the Derived Column Transform
Rolling Up Data with the Aggregate Transform
Ordering Data with the Sort Transform
Joining Data using Lookup/Merge Join
Combining Multiple Inputs with the Merge or Union All
Auditing Data with the Row Count Transform
Separating Data with the Conditional Split Transform
Altering Rows with the OLE DB Command Transform
Using Cache Transform Component
Dimension Table Loading
Using SCD(Slowly Changing Dimensions)
Fact Table Loading
Using CDC(Change Data Capture)
SSAS Processing
Implementing Multi-Dimensional Model (24 Hours)
Designing DSV(Data Source View)
Dimensions: Attributes & Members
Dimensions: Hierarchies
Measure Group & Measures
Full Additive vs Semi Additive & Non Additive Measures
Demonstrate results Using Excel Pivot Table
Advanced Dimension Designing
Introduction to MDX language (Multi-Dimensional Expressions)
MDX Query
MDX Expressions
Calculated Member
Named Set
Script Command
Implementing KPI
Adding Translation
Using Perspectives
Managing Data Warehouse
Elementary Partitioning
Elementary Processing
Deployment
Managing Security

Implementing Tabular Model - 9 Hours

Tabular Model Concepts
Tabular Model Concepts
Comparison of Multidimensional and Tabular Models
Tabular Model Implementation
Fetching the Data
Designing Data Model & Understanding Relationships
Active vs Inactive Relationship
Bidirectional Relationship
Introduction to DAX language (Data Analysis Expressions)
Calculated Attributes
Calculated Tables
Measures
Demonstrate results Using Excel Pivot Table
Implementing KPI
Implementing Hierarchy
Using Perspectives
Adding Translation
Managing Data Warehouse
Elementary Partitioning
Elementary Processing
Deployment
Managing Security
Self Service BI (Power Pivot)
Self Service BI Concepts
Power Pivot Implementation Using Excel

Reporting & Dashboard Design - 9 Hours

Introduction to all reporting tools in Microsoft platform
Implementing Power View for Excel
Configuring SSRS
Implementing SSRS Reports
Paginated Reports initial familiarization
Implementing Parameterized Reporting
Implementing Graphical & Geographical Dashboards
Implementing Actionable Reports
Power BI Reports initial familiarization
Mobile Reports initial familiarization

Elementary Data Mining (9 Hours)

Understanding Data Mining
Data Mining Concepts
The Data Mining Process
Understanding Key Concepts
Attribute
State/Value
Case/Nested Case/Case Table/Nested Table
Keys (Case Key/Nested Key)
Inputs & Outputs
Implementing Mining Structure
Implementing Case Table
Implementing Nested Table
Partitioning Sets
Implementing Mining Model
Introduction to Data Mining Algorithms
Browsing & Querying Mining Models
Using Mining Model Viewer
Elementary Prediction with Mining Model Predictions
Introduction to DMX (Data Mining Extensions) in DQL mode