CMS/20767B : Implementing a SQL Data Warehouse

5 gün (30 Saat) İleri Sınıf / Online İş Zekası ve İleri Analitik

Bu etkinlik yakında başlıyor. Hemen kayıt olun!

Eğitmen : Abdullah Kise - MCT, MVP, MSCE (DP&BI)

Yer : Online

Ücret : ₺ 48.900+ kdv (%20) | 81.500+ kdv (%20) (%40 ↓)

Durum : Genel Katılıma Açık

Kontenjan : 10

Hemen Kayıt Olun!

23

Haziran 2025

Tamamlandı

Microsoft SQL Server ürün ailesi ile uçtan uca büyük ölçekli kurumsal iş zekası projelerinizi yürütebilirsiniz. İş zekası projelerinin belkemiğini oluşturan kaynakların keşfi, veri ambarı tasarımı, veri taşıma ve veri kalitesini arttırma konusunda teknik ve teknolojilere odaklanıyoruz. "Implementing a SQL Data Warehouse" eğitimi genel olarak SQL Server, SQL Server Integration Service, Data Quality Services, Master Data Services, ColumnStore Indexs ve tasarım prensiplerini içermektedir. Dilerseniz bu eğitimden sonra Microsoft'un 70-767 sınavına giriş yapabilir, İş Zekası Uzmanı olma yolunda büyük bir adım atabilirsiniz.

Eğitim İçeriği

Module 1: Introduction to Data Warehousing

  • Lesson
    • Overview of Data Warehousing
    • Considerations for a Data Warehouse Solution

Module 2: Planning Data Warehouse Infrastructure

  • Lesson
    • Considerations for data warehouse infrastructure.
    • Planning data warehouse hardware.

Module 3: Designing and Implementing a Data Warehouse

  • Lesson
    • Data warehouse design overview
    • Designing dimension tables
    • Populer Dimensional Design Principles
    • Designing fact tables
    • Physical Design for a Data Warehouse

Module 4: Columnstore Indexes

  • Lesson
    • Introduction to Columnstore Indexes (Clustered, NonClustered)
    • Creating Columnstore Indexes
    • Working with Columnstore Indexes

Module 5: Creating an ETL Solution

  • Lesson
    • Introduction to ETL with SSIS
    • Exploring Source Data
    • Implementing Data Flow

Module 6: Implementing Control Flow in an SSIS Package

  • Lesson
    • Introduction to Control Flow
    • Creating Dynamic Packages (variables and parameters)
    • Using Containers
    • Managing consistency (Transactions and Checkpoints)

Module 7: Debugging and Troubleshooting SSIS Packages

  • Lesson
    • Debugging an SSIS Package
    • Logging SSIS Package Events
    • Handling Errors in an SSIS Package

Module 8: Implementing a Data Extraction Solution

  • Lesson
    • Introduction to Incremental ETL
    • Extracting Modified Data
    • Loading modified data
    • Temporal Tables
  • Lab : Extracting Modified Data
    • Using a datetime column to incrementally extract data
    • Using change data capture
    • Using the CDC control task
    • Using change tracking
  • Lab : Loading a data warehouse
    • Loading data from CDC output tables
    • Using a lookup transformation to insert or update dimension data
    • Implementing a slowly changing dimension
    • Using the merge statement

Module 9: Enforcing Data Quality

  • Lesson
    • Introduction to Data Quality
    • Using Data Quality Services to Cleanse Data
    • Using Data Quality Services to Match Data
  • Lab : Cleansing Data
    • Creating a DQS knowledge base
    • Using a DQS project to cleanse data
    • Using DQS in an SSIS package
  • Lab : De-duplicating Data
    • Creating a matching policy
    • Using a DS project to match data

Module 10: Extending SQL Server Integration Services (SSIS)

  • Lesson
    • Using scripting in SSIS
    • Using custom components in SSIS

Module 11: Deploying and Configuring SSIS Packages

  • Lesson
    • Overview of SSIS Deployment
    • Deploying SSIS Projects
    • Planning SSIS Package Execution
  • Lab : Deploying and Configuring SSIS Packages
    • Creating an SSIS catalog
    • Deploying an SSIS project
    • Creating environments for an SSIS solution
    • Running an SSIS package in SQL server management studio
    • Scheduling SSIS packages with SQL server agent

Module 12: Consuming Data in a Data Warehouse

  • Lesson
    • Introduction to Business Intelligence
    • An Introduction to Data Analysis
    • Introduction to reporting
    • Analyzing Data with Azure SQL Data Warehouse
  • Lab : Using a data warehouse
    • Exploring a reporting services report
    • Exploring a PowerPivot workbook
    • Exploring a Power BI report

Öncesinde Önerilenler

Sonrasında Önerilenler