1. 資料整合方案 Real-time integration at the speed of business

2. 資訊整合的挑戰是什麼? Data resides in many different places and systems…
It comes in all sizes and shapes
It has different meanings in different contexts
Try asking five people from different departments
to define “customer”!
It comes in enormous volumes, growing every day
But everyone needs usable information
. . . and needs it now!
常要根據不完整的資訊做決定
Information integration is the solution 2

3. 企業/組織面臨的Business問題 太多的資訊和找不到資訊的重點在哪
Not using demand signals to drive supply chain
Not using customer analysis to tailor marketing and sales
Not leveraging valuable unstructured information
同一個事實 多個版本
Problems managing customer, product and partner interactions
Regulatory compliance inhibited by poor transparency
缺少可信賴的資訊
Incomplete, out-of-date, inaccurate, misinterpreted data
Difficult to understand or control how information is used
資訊彈性不足
Inability to take advantage of opportunities for innovation
Escalating costs due to inflexible systems and changing needs
Key Point: Customers tell us the inhibitors come down to four primary issues.
When we drill down one more layer on our conversations with customers, we find that many of them are facing the same kinds of problems.
Often they tell us that they need to do a better job leveraging information. This comes directly from the CEO survey mentioned on the previous slide. This problem manifests itself in many ways – sometimes companies complain about “information complexity”, or a “deluge of information”, but what that really means is that there is a great deal of valuable information locked away in various databases and systems throughout the business, but the organization has no easy way of using this information to improve the business, to compete more effectively, or to innovate. Often we see retail companies, for example, failing to use demand signals from their stores effectively to drive their supply chains. Across all industries, it is common to find that organizations are not using customer analysis to tailor their marketing and sales activities. In other cases, entire classes of information are being ignored, like unstructured information from s and documents, simply because they are too difficult and expensive to deal with.
Another point we often hear is that organizations have multiple versions of the truth across their systems. This prevents them from being able to completely understand their customers, and tailor their interactions accordingly. It also leads to supply chain collaboration problems, since suppliers and customers have differing concepts and definitions of products. It also causes difficulties when trying to comply with information-centric regulations like Sarbanes-Oxley or Basel II, that require definitive information with associated proof.
The third thing we hear about is trust and control. Organizations don’t have trust in their information because the quality cannot be assured, and the source of the information is often uncertain. At the same time, companies want to control who has access to information, understand how It is being used, and govern sensitive information throughout its lifecycle.
And lastly, organizations tell us that information inflexibility inhibits their ability to respond quickly to change. They can’t take advantage of new opportunities for innovation, and their costs of maintaining IT systems continuously escalate as the business demands change from systems that weren’t build for change.

4. 資訊整合的問題是複雜的 Multiple sources for the same entity
Lack of standards or consistent semantic meanings across systems
Embedded business intelligence
Evolving transformation requirements
Need for batch and real-time and service oriented architectures
Extreme data volumes!
Business rules for resolving data conflicts
Ownership and accountability
This concludes the issues that we mentioned previously

5. 如何有效的利用資訊? We can: Access it, wherever it may be
A typical information
architecture!
We can:
Access it, wherever it may be
Understand what it is, where it is, how reliable it is
Cleanse, merge and correct it
Transform it so it can be understood by applications, people and processes that need it
Deliver it to new destinations for new uses

6. …And Current Approaches Are Limited
Point solutions will not scale
Hand coding is time consuming and difficult to maintain
Multiple tools are costly and the business rules and meta data must be re-created many times
None of these approaches improve the quality of data across the enterprise
The Titanic - Everything’s OK, so far!

7. IBM 創新的資訊整合平台 – Information Server
Trust
Productivity
Collaboration
Scalability
Reuse

8. Subject Matter Experts
Developers
我看到報表的資料是正確吧!
Subject Matter Experts
我要一個有效率簡單的工作方法..
Business Users
有沒有一個方法讓我和developer容易溝通
管理和維護可不可以簡單點
安全性,擴充性,架構的未來性
Architects
DBAs
Data Analysts
為什麼我老是要切換不同工具來做事

9. Subject Matter Experts Unified Metadata Management
協同合作的平台
Business Users
Subject Matter Experts
Architects
Data Analysts
Developers
DBAs
Unified Metadata Management
Simplify Integration
Increase trust and confidence in information
Increase compliance to standards
Facilitate change management & reuse
Design
Operational

10. 完整的資料整合開發週期 Metadata Server and Metadata Workbench Import Industry
Data Models
Exchange Data Structures
Services Oriented Architecture
Rational Data Architect
Information
Services Director
Link
Populate
Deploy
Common Enterprise Vocabulary
Map Sources to Target Model
Transform and Cleanse
Search and Profile Source Data
Link
Define
Create
DataStage and QualityStage
Business Glossary
Information Analyzer
FastTrack
Share
Share
Share
Share
Metadata Server and Metadata Workbench
Active Cross-Platform Administration, Management and Reporting

11. 從報表回溯到資料源, 資料源影響幾支報表 ? Impact Analysis
Import & Browse Full BI Report Metadata
Navigate through report attributes
Visually navigate through data lineage across tools
Increases trust and understanding of business information S
Impact Analysis T
IBM Information Server
Source Tables
So here are some of the key questions that IBM Metadata Workbench helps answer:
Users often wonder where specific data fields on their reports come from. The problem is that their reporting and BI tools are typically disconnected from the integration logic they used to derive the data from their source systems, making this end-to-end view impossible.
IBM Metadata Workbench helps overcome this problem by stitching design & operational data together across tools, providing a complete view of the lineage of information, from third-party reporting and BI tools like Business Objects, MicroStrategy and Cognos all the way back to source systems, or even to source data models. This unique combination of design & operational metadata provides a true understanding of the provenance of information – inspiring trust in the data, and proving the exact derivation of each field of information.

12. Data Cleansing的實施方法 資料 品質 評估 (DQA) 資料重組 (DRE) 調查 標準化 匹配 重新組合
台北市承德路 98 號 12 樓之一
北市承德路 98號 12F A 室
台北市大同區承德路 98 號 12F-1
北市承德路 98 號 12 樓之 1
台北市 | 承德路 | 98 號 | 12 樓 | 之一
北市 | 承德路 | 98 號 | 12 F | A 室
台北市 | 大同區 | 承德路 | 98 號 | 12F-1
北市 | 承德路 | 12 樓 | 之 1
台北市大同區承德路 98 號 12 樓 A 室

13. 將多個系統的資料合併, 行成單一客戶的資料與地址正規化！
客戶資料的正規化
將多個系統的資料合併, 行成單一客戶的資料與地址正規化！
15,999.
10,243.
6,800.
20,069.
銷售額
台北市大同區承德路 98 號 12 樓 A 室
王來富 地址 電話 姓名
53,111.
銷售額
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王來富 地址 電話 姓名

14. 完整符合SOA架構整合 Portal IBM Information Server IBM Information Server
Call Center
Portal
Customer
Order History
Order History Service
Customer
Customer Info
Customer Master Service
IBM Information Server
IBM Information Server
Customer
Order Status
Data Cleansing Service
What you end up with is a series of information services, all published from IBM Information Server. These services provide cleansing, transformation, and delivery of information, and can be shared by portals, processes and applications across the enterprise – providing trusted information as a services. They are designed and maintained by information specialists, independently from the applications, processes, and portals that use them, providing a much more flexible environment.
Receive
Request
Order Handling Process
Check
Account
Ship
Order
Check Order
Policy
Review
Process Server

15. Warehouse and Source Systems
資料整合過程所有MetaData的管理
Data
Warehouse and Source Systems
DataStage &
QualityStage Job
Data
Mart
OLAP
Collection
Report

16. 資料整合過程中Business Metadata的應用

17. + x 你會如何選擇 … ? Point Products Integrated Platform ?
Models
Cleansing
ETL
MDM
Warehouse BI
Integrated Platform
Unified Platform Benefits:
降低風險 %
改善開發效率 %
減少開發人員成本 %