Brainmatics

Building Data Warehouse with SQL Server 2012

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Dunia bisnis saat ini sangatlah kompetitif. Manajemen harus bertindak dan mengambil keputusan dengan cepat. Keputusan yang diambil harus tepat sehingga membutuhkan data pendukung. Data pendukung keputusan ini dapat bersumber dari banyak lokasi. Data warehouse merupakan solusi yang dapat digunakan oleh manajemen untuk mendapatkan data penunjang keputusan dengan cepat, tepat dan akurat.

Dengan membangun data warehouse, perusahaan mengintegrasikan data yang berasal dari berbagai sumber (Sarka, 2012). Dengan demikian, data akan terpusat dan dapat dianalisis dengan cepat. Manajemen akan mendapatkan waktu respons yang lebih cepat jika memerlukan data penunjang. Bentuk laporan yang disajikan melalui data warehouse dapat disusun berbagai sudut pandang. Penerapan data warehouse juga mewajibkan perekaman data secara historis dan lengkap untuk menunjang analisis. Hasilnya kualitas data menjadi meningkat dan lebih akurat.

Training Building Data Warehouse with SQL Server 2012 membahas logical design data warehouse, metode pengimplementasian data warehouse, pembuatan SSIS package, pembuatan Control Flow, pembuatan Data Flow, pengimplementasian Dynamic Package, metode troubleshooting package, metode meningkatkan performa, instalasi Data Quality Service, pengimplementasian Master Data Services, pengelolaan Master Data, dan lain sebagainya. Training disertai dengan berbagai studi kasus yang dipraktikkan untuk mempersiapkan peserta menghadapi berbagai kasus data warehouse di dunia nyata.

 

OBJECTIVES

  1. Memahami konsep data warehouse
  2. Mampu mendesain dan mengimplementasikan data warehouse
  3. Mampu mengimplementasikan Data Flow pada SSIS Package
  4. Mampu melakukan troubleshooting dan meningkatkan performa SSIS Package

 

AUDIENCE

  1. Business Intelligence Developer
  2. Datawarehouse Implementor

 

PREREQUISITES

Querying Microsoft SQL Server 2012 (70-461) Exam Preparation

 

CONTENT

1. Data Warehouse Logical Design

1.1. Introducing Star and Snowflake Schemas
1.2. Designing Dimensions
1.3. Designing Fact Tables

2. Implementing a Data Warehouse

2.1. Implementing Dimensions and Fact Tables
2.2. Managing the Performance of a Data Warehouse
2.3. Loading and Auditing Loads

3. Creating SSIS packages

3.1. Using the SQL Server Import and Export Wizard
3.2. Developing SSIS Packages in SSDT
3.3. Introducing Control Flow, Data Flow, and Connection Managers

4. Designing and Implementing Control Flow

4.1. Connection Managers
4.2. Control Flow Tasks and Containers
4.3. Precedence Constraints

5. Designing and Implementing Data Flow

5.1. Defining Data Sources and Destinations
5.2. Working with Data Flow Transformations
5.3. Determining Appropriate ETL Strategy and Tools

6. Enhancing control flow

6.1. SSIS Variables
6.2. Connection Managers, Tasks, and Precedence Constraint Expressions
6.3. Using a Master Package for Advanced Control Flow

7. Enhancing Data Flow

7.1. Slowly Changing Dimensions
7.2. Preparing a Package for Incremental Load
7.3. Error Flow

8. Creating a Robust and Restartable Package

8.1. Package Transactions
8.2. Checkpoints
8.3. Event Handlers

9. Implementing Dynamic Packages

9.1. Package-Level and Project-Level Connection Managers and Parameters
9.2. Package Confgurations

10. Auditing and Logging

10.1. Logging Packages
10.2. Implementing Auditing and Lineage
10.3. Preparing Package Templates

11. Installing SSIS and Deploying Packages

11.1. Installing SSIS Components
11.2. Deploying SSIS Packages

12. Executing and Securing Packages

12.1. Executing SSIS Packages
12.2. Securing SSIS Packages

13. Troubleshooting and Performance Tuning

13.1. Troubleshooting Package Execution
13.2. Performance Tuning

14. Installing and Maintaining Data Quality Services

14.1. Data Quality Problems and Roles
14.2. Installing Data Quality Services
14.3. Maintaining and Securing Data Quality Services

15. Implementing Master Data Services

15.1. Defining Master Data
15.2. Installing Master Data Services
15.3. Creating a Master Data Services Model

16. Managing Master Data

16.1. Importing and Exporting Master Data
16.2. Defining Master Data Security
16.3. Using Master Data Services Add-in for Excel

17. Creating a Data Quality Project to Clean Data

17.1. Creating and Maintaining a Knowledge Base
17.2. Creating a Data Quality Project
17.3. Profiling Data and Improving Data Quality

18. SSIS and Data Mining

18.1. Data Mining Task and Transformation
18.2. Text Mining
18.2. Preparing Data for Data Mining

19. Implementing Custom Code in SSIS Packages

19.1. Script Task
19.2. Script Component
19.3. Implementing Custom Components

20. Identity Mapping and De-Duplicating

20.1. Understanding the Problem
20.2. Using DQS and the DQS Cleansing Transformation
20.3. Implementing SSIS Fuzzy Transformations

 

INSTRUCTOR

 

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Satya Sanjaya Menamatkan pendidikan tinggi jurusan teknik mesin di Universitas Indonesia. Aktif sebagai konsultan dan telah menyelesaikan banyak project dibidang System Programmer Administrator dan Database Administrator, seperti dalam penerapan Microsoft Windows NT Server, Microsoft SQL Server, Microsoft Sharepoint, dan ASP.Net MVC. Sekarang aktif sebagai pengajar/trainer diberbagai training center di Jakarta, untuk materi training berbasis Microsoft seperti Visual Basic, Visual Interdev, SQL Server, Visual Studio.Net, Microsoft Windows Server, Microsoft SharePoint, Microsoft Project, Crystal Report.