ایجاد و  پیاده سازی انبار داده و سیستم هوشمندسازی کسب و کار ، در پی هم می آیند و از لحاظ  فنی از پروژه های جذاب در زمینه  فناوری اطلاعات می باشد و از نظر سازمانی پروژه های پیچیده ای محسوب می شوند. این دوره امکانی را برای سازمان ها فراهم می کند تا با موفقیت محیط انباره داده و سیستم هوشمند سازی کسب و کار را ایجاد کنند . 

    سرفصل

    Introduction

    Roadmap of project tasks

    Program/Project Planning and Management

    Readiness factors

    Risk assessment and mitigation plans

    Scoping and business justification

    Team roles and responsibilities

    Project plan development and maintenance

    Program management

    Business Requirements Definition

    Program versus project requirements preparation

    Requirements gathering participants

    Techniques for gathering requirements and handling obstacles

    Program/project requirements deliverables

    Requirements prioritization

    Dimensional Modeling

    Role of dimensional modeling in Project, Corporate Information Factory (CIF) and hybrid architectures

    Fact and dimension table characteristics

    4-step process for designing dimensional models

    Transaction fact tables

    Fact table granularity

    DE Normalizing dimension table hierarchies

    Degenerate dimensions

    Date and time-of-day dimension considerations

    Dealing with nulls

    Surrogate key for dimensions

    Star versus snowflake schemas

    Centipede fact tables with too many dimensions

    Fact-less fact tables

    Additive, semi-additive, and non-additive facts

    Workshop: Converting requirements and source data realities into dimensional model

    Consolidated fact tables

    Dimension table role-playing

    Allocated facts at different levels of detail

    Complications with operational header/line data

    Multiple currencies

    Junk dimensions for miscellaneous transaction indicators

    Periodic and accumulating snapshot fact tables

    Implications of business processes on data architecture

    Enterprise Data Warehouse Bus Architecture and matrix for master data and integration

    Conformed dimensions – identical and shrunken roll-ups

    Exercise: Translate business requirements into DW Bus Matrix

    Slowly changing dimensions – type 1, 2, 3 and hybrid techniques for current and point-in-time attribute values

    Mini-dimensions for large, rapidly changing dimensions

    Exercise: Design review to identify common dimensional modeling flaws

    Design review dos and don’ts and mistakes to avoid

    Dimensional modeling process, tasks, and deliverables

    Exercise: Design enhancements to embellish existing design

    Mature DW/BI System Check-ups

    Symptoms of sponsorship, data, infrastructure, and business acceptance disorders

    Prescribed treatment plans for common maturity problems

    Technical Architecture Design

    Architecture concepts

    Topology options – independent data marts, enterprise data warehouse, and conformed data warehouse

    Common components and functionality

    ETL system

    Exercise: Processing slowing changing dimensions type 2

    Presentation servers (RDBMS/OLAP)

    Real time options – direct to source, ODS, and real time layer

    BI application types and services

    Creating the architecture plan

    Exercise: Translating requirements into architecture implications

    Product Selection and System Setup

    Architecture-based evaluation approach and matrices

    Infrastructure considerations

    Metadata management

    Securing the system

    Physical Database Design

    Standards and naming conventions

    Physical model development

    Initial aggregation, indexing and storage plans

    Column-oriented database alternative

    Usage monitoring

    Extract, Transformation and Load

    Design the ETL system

    Determine design patterns and implement key subsystems

    Quality assurance and data validation system

    Warehouse operations system

    ETL development workflow

    Create high-level and detailed ETL schematics

    Extract to create, filter and transfer source data

    Cleaning and conforming dimensions and facts

    ETL development workflow continued

    Preparing and delivering dimensions and facts

    Data integration and master data management

    Dealing with data quality issues

    Aggregate management

    Load cycle management

    Exercise: “High-level ETL schematic” case study

    BI Applications

    BI application types (ad hoc, standard reporting, analytic applications, dashboards) and audiences

    Specification of templates, applications and navigation framework

    Development of applications and BI portal

    DW/BI System Deployment and Support

    System deployment

    Communication and documentation

    Training and support

    On-going user, data and system maintenance

    DW/BI System Growth

    Planning for growth

     


    6.1.7.0
    گروه دورانV6.1.7.0