enterprise information integration – die

Enterprise Information Integration –die Schlüsselkomponente fürerfolgreiche SOA-Infrastruktur

Dr.Siegmund Priglinger

[email protected]

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Informatica im Überblick

• Founded: 1993

• Headquarters: Redwood City, California

• Employees: 1,100+

• Offices: North and South America, Europe, Asia Pacific

• Revenue: $267 million (2005)

Fast Facts• Market share leader (Gartner Dataquest)

• Customers: 2,600+

• 83 of Fortune 100

• 80%+ of Dow Jones

• Government organizations in 20 countries

Unsere MissionWir helfen Firmen, eine “Data Services Architecture” zuimplementieren, um damit ihre Daten optimal für den eigenenGeschäftserfolg einsetzen zu können.

Unser FokusData Integration Products and Services

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Agenda

• Die “ewigen” Integrationsthemen

• Der Prozess- und Informationsfluss

• Die Vision von “Data Services”

• BestPractice Beispiele

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Die „ewigen“ Integrationsthemen

Book: ICC Integration Competency Center, John Schmidt + David Lyle, Informatica 2006

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Agenda





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Der Prozess- und der Informationsfluss (1)

SAP-Modellschema für Prozesse

Branchenm odell

R /3-R eferenzprozeßm odell

M odellfilter

K undenm odell

M odellfilter

Projekt 1 Projekt 2K undenm odell

M odellfilte r

SA PSA P

K undeK unde K undeK unde

K undeK unde

Wo ist da der Datenfluss beschrieben ?

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EPK-Modellelemente

Wo ist da der Datenfluss beschrieben ?


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SADT-Modellelemente

Input Output

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A B

Anwendung A Anwendung B

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Data Services: Lagerstammdaten

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Anwendung A Anwendung B

Objektmodell A Objektmodell B

Redundante Daten: Synchronisation durch Data Services,NICHT durch Messages zwischen Methoden.

a~b

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Beispiel: Versicherung

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Generisch konfigurieren …

• Modelle mappen

• Business Object Levelversus

• Relational Table Level

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Agenda





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Die Vision: Data Services… “entwirren” diese Komplexität

• … greifen auf Daten zu, wosie auch sind.

• … bringenDatendefinitionen in Einklang miteinander ( konsistent, wiederverwendbar).

• … führen zu garantierterDatenqualität, zu richtigenund vollständigen Daten.

• … wandeln Daten jedenFormats in nutzbare Datenum.

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Enterprise

SCM HR

CustomPLMCRM

ERP

External Data

SaaS

BPO

ITO

Data Services

Die Vision von Data Services“On-Demand” Integration von Daten

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Data Governance oder „was fehlt…“

Data Governance ist in etwa so definierbar:

„Data Governance“ ist das System, mittels dessen das Unternehmen den internen und externen Informations-

fluss steuert und die gesamte Datenstrategie und deren

Architektur festlegt. Die „Data Governance“ legt die

Prozesse, die Fähigkeiten, die Führungsart und die

Anlagen fest, die erforderlich sind, um die Informations-ressourcen des Unternehmens erfolgreich einsetzen zu

können.

�� Gesichtspunkte eines „ERP for IT“

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Data Explorer Data Quality

Audit, Monitor, ReportSicherstellung von Datenkonsistenz, Analyse von Fehlerquellen und laufende

Datenqualitätsüberwachung

PowerCenterPowerExchange

Access

Auf jedesSystem imBatch oderReal-time

DeliverIntegrate

KorrekteDaten überallzur richtigen Zeit

Transformation und Daten-harmonisierung

CleanseDiscover

Validieren, korrigieren und standardisieren

Data Profiling sämtlicherDaten ausbeliebigenQuellen

Informatica Produkte und LösungenIntegrierte Plattform für eine unternehmensweite automatisierteDatenintegration

Develop & ManageZusammenarbeit auf Basis gemeinsamer Repositories und Metadaten

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Service Orientierte Datenintegration

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Agenda




• Best Practice Beispiele

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Data fragmentation is a key barrier to realizing the full business potential of your initiatives

Challenge How We Helped Business Value

• Downtime could trigger costly interruptions to time-sensitive engineering

• PowerCenter

• Grid support

• 24x7 data availability

• Nearly 3x improvement in data load performance

• Three-year ROI of $2.5 million in reduced development time

Goal: Support Engineering Development

• Ensure 24x7 availability of data for worldwide team to

engineer and deliver solutions

Manufacturing

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Challenge How We Helped Business Value• Migrate 30+ J.D Edwards

and legacy application instances to SAP and SAP applications to new SAP platform

• Build 150 interfaces to enable synchronization

• PowerCenter

• PowerCenter Connect for SAP

• Certified SAP integration -IDOCS, ABAP, ALE, BAPI, and DMI

• 75% component reuse to accelerate deployment across multiple projects

Goal: Integrate M&A and Rationalize IT EnvironmentManufacturing

• 80% improved productivity; millions of dollars in ROI

• End-to-end data integrity through validation and MDM

• Improved business agility and precision with unified, global SAP data infrastructure

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• Integrate SAP Data with 6 Legacy Applications

• PowerCenter

• Native capability to treat SAP IDocs as flat files

• 30% increase in IT personnel efficiency

• Improved data quality & customer satisfaction

• Greater precision in manufacturing and business processes

Goal: Enhance Manufacturing and Business Processes

• Support transaction processing calibrating replenishment,

production, distribution and billings to drive business insight,

efficiency, and maximize profitability

Manufacturing

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• Time-consuming, manual effort to integrate data across supply chain, vendors

• Need to access disparate sources

• PowerCenter

• PowerCenter Connect for SAP

• Highly productive development tools

• Native connectivity to SAP, i2, BroadVision

• ~$10M monthly supply chain savings

• Increased inventory turns

• Reduced IT staff from 25 to 5

Goal: Gain Global Supply Chain Visibility

• Provide global, enterprise wide real-time visibility of supply

chain via dashboards

• Supplier collaboration through a portal for vendor managed

inventory

Manufacturing

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• Enterprise data distributed across the business

• Various development tools; custom code

• PowerCenter

• PowerCenter Connect for SAP and BW

• One standardized platform

• Improved performance and forecasting capabilities

• Improved development productivity

Goal: Gain Global View of Business OperationsManufacturing

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• Reporting data scattered across spreadsheets, Access databases and other silos

• Business users lack easy access to information

• Pre-built access to Oracle and other sources

• Built-in data presentation capabilities

• $15M per month savings in supplier spend

• Low administration overhead / costs

Goal: Single Source of Truth for Supply Chain

• Consolidate 6 versions of the truth– 1 for each business unit–

down to 1

• Reduce supply chain costs

Manufacturing

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• Time to implement had to be less than one year

• PowerCenter

• Quicker, more risk free and cost effective implementation

• $2 million savings from improved delivery of analytic information

• Anticipated tens of millions of dollars in savings through improved, real-time, global supply chain visibility

Goal: Improve Supply Chain Visibility

• Real-time visibility into global supply chain to view inventory

and sales records

• Analytic dashboards for metrics-driven management across

the organization

Manufacturing

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• Migrate from legacy mainframe environment to client server

• PowerCenter

• Real-time access into warehouse inventory levels, sales and marketing activity

• Improved productivity, leading to cost savings (reduction of 40%)

• Sharp reduction in number of customer redeliveries

Goal: Modernize MainframeManufacturing

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Challenge How We Helped Business Value• Limited visibility into

business operations, product and sales performance

• Tremendous overlap in products

• PowerCenter

• PowerCenter Data Analyzer

• Significantly lowered IT maintenance; lowered IT staff by 10

• Saved $3-$4 million in implementation costs with fast implementation

• Real-time view of product and customer profitability

Goal: Integrate M&A• Gain a holistic view of organization

Manufacturing

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• Reliable customer and vehicle information not easily accessible

• PowerCenter

• Data Analyzer

• Provided single view of customer

• Increased accuracy and response of call center agents

• Increased customer satisfaction and loyalty

• Better data visibility for executives

Goal: Deliver Superior Customer ServiceManufacturing

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Challenge

Reuters - Increasing effectiveness of Global CRM

processes through data quality

Solution Expected Results• Lack of ROI on Siebel due to

low quality data

•Inaccurate mailing processes

•Inefficient marketing processes

• Informatica Data Quality

• To implement a Data Quality Scorecard per country

•To implement one off cleansing and standardization

• Informatica Data Explorer

• Increase in salesforce and marketing efficiency

• Recognised Data Quality metrics process in place

Key Business Requirements:• “Fix data quality within existing Siebel systems”

Approach:• Provide data quality metrics to drive improvement

processes•Implement one off and ongoing data quality processes

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Informatica In ActionKEY BUSINESS IMPERATIVE

INFORMATICA ADVANTAGE RESULTS/BENEFITSTHE CHALLENGE

IT/BUSINESS INITIATIVE:

DATA QUALITY INITIATIVE:

ref123

Regulatory Reporting

DQ Reporting & Monitoring

Regulatory Compliance• Compliance with anti-money laundering regulations

• Provide robust DQ reporting and metrics system for AML Unit

Third Largest Bank in the US

• Enable AML team to build, manage and customize AML business rules

• Track and monitor data quality across key systems

• Data quality workbench for business users

• Scorecard aggregating data quality metrics from multiple systems

• Avoided regulatory penalties of up $20m

• Implemented AML DQ Monitoring ahead of deadline using existing AML team resources

• Saved estimated $3m+ cost of bespoke of AML solution

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Informatica In ActionKEY BUSINESS IMPERATIVE

INFORMATICA ADVANTAGE RESULTS/BENEFITSTHE CHALLENGE

IT/BUSINESS INITIATIVE:

DATA QUALITY INITIATIVE:

ref123

System Consolidation

Data Match & Consolidation

Merge & Acquire• Successful and cost effective post merger integration

• Build an integration hub for effective integration and data quality management of new data sources

Supplying Gas & Electricity in 5 States

• Rapid post-merger data consolidation and quality management

• DQ platform to drive standardization and re-usability across multiple merger projects

• End-to-end data quality solution for all data types

• DQ as part of data integration platform

• Will deliver savings of $Ymillion per year through faster post-merger business integration

• Will reduce time and cost of post-merger data consolidation by X%

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Challenges

P&G – Implementation of data quality processes as a

critical element of Master Data Management (MDM)

Solution Expected Results• Requirement to synchronize

Gillett SAP instance with P&G SAP instance for master data (following the acquisition of Gillette)

• Enablement of global data quality analysts to implement data quality projects


• to Identify & categorise low quality data

• Implement a DI-Q process as part of a synchrosization process

• Informatica PowerCenter

• Increased quality of master data

• Better management of master data

• Recognised Data Quality metrics process in place

Key Business Requirements:• Implementation of data Quality processes to improve

master data management (MDM) data quality

Approach:• Provide data quality dimensions, metrics and cleansing

functionality to drive improvement processes as part of data integration processes with PowerCenter

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Challenges

VWR – Implementation of data quality processes for a

SOX initiative including “Know Your Customer” and “Know Your Product”

Solution Expected Results• Build an effective business

case for data quality

• Recognise that data quality was impact the core business processes

• Provide a solution for data quality

• Informatica Data Quality to:

• Replace mannual DQ processes via automated processes

• Rationalise master data

• Be proactive by enabling data analysts

• Increased quality of master data

• Reduced mannual review process (team of 20 people)

• Recognised Data Quality metrics and cleansing process in place

Key Business Requirements:• Implement data Quality processes to improve master

data management (MDM) across the organisation to

support SOX processes

Approach:• Provide a standard process for data quality management

including data quality dimensions, metrics and cleansing functionality to support a Master Data Management strategy

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Challenge

AIB Bank Data Governance / Stewardship

Solution Results

• Due to some high profile errors in data i.e. overcharging, AIB needed to ensure 100% accurateness in customer information

• Inability to measure quality of data within compliance datawarehouse (Teradata)

Key Business Requirements:• Retail CRM unit: Data Quality processes for all

customer data within AIB group

• Compliance: Basel II, IFRS & SOX processes

Approach:• Implementation of Data Quality metrics processes to

support both retail and compliance led solutions

• Informatica Data Quality to

• Cleanse and standardize data

• Implement a data quality scorecard

• Implement ongoing cleansing processes

• Massive improvement in CRM processes.

• Compliance with Basel II, IFRS and SOX regulations though the implementation of Data Accuracy Scorecards

• Vastly improved data governance and data remediation processes

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Challenge

Nestle Data Standardization in preparation for SAP implementation

Solution Results

“Nestlé selected Informatica Data Quality to carry out data cleansing and transformation as it offered an easy to use, flexible and complete data quality solution with powerful reporting capabilities.”

-- Data Manager IS/IT – Application Development / Data Conversion Nestec GLOBE

• Streamline business processes for implementation of central SAP ERP system

• Standardizing product, inventory and customer data across 60 locations

• Defining internal data standards

• Validating & standardizing information from Nestle companies around the world

• Providing centralized control while enabling local data analysts to ensure DQ to local & global standards

• Tracking DQ via scorecard process

• Nestle rolled Data Quality out across its International operations in less than six months

• Significantly mitigated the risk associated with the GLOBE project

• Increased operational efficiency due to single reliable view of product and item data

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Challenge

Stryker Data Migration to Oracle ERP in Four Regions

Solution Results

• Streamline business processes with Oracle ERP

• Extract master reference data from source systems, standardize, cleanse and integrate into Oracle

• Mostly product and inventory data to be migrated

• Quality of the data must exceed 98%

Informatica Data Quality for:

• Profiling & analyzing all data

• Designing business and conversion rules

• Providing exception files

• Automated cleansing and standardization

• Creating extracts for ERP

• DQ monitoring over time

• Significant data quality improvement in weeks instead of months

Key Business Requirements:• Implement data Quality processes to reduce risk

during an Oracle ERP implementation

Approach:• Provide a robust data quality process to prepare the master

data prior to the data migration process across several manufacturing plants in the US and EMEA

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Challenge

eircomData Governance / Stewardship

Solution Results

“Informatica Data Quality is an open product that is easy to understand and to use. It is also flexible, it can be used across different types of data sets and in different operating environments.”

-- Daragh O’Brien, Data Quality Manager, eircom

• Large number of inefficient legacy systems

• Underperforming CRM and Business Intelligence applications due to poor data quality


• Ongoing name and address data cleansing from multiple systems

• Day to day reporting of DQ from source systems

• Automated cleansing of ‘simple single line’ entries

• Reporting on key performance indicators (KPI) in individual business areas

• Increased efficiency in CRM & BI systems

• Reduced costs due to reduction in headcount at telephone directory unit

• Revenue growth

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Danke für Ihre Aufmerksamkeit !

enterprise information integration – die

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