1November 2007

Modernizing Data:

Issues and Approaches

2November 2007

Introduction to Treehouse Software

Issues

Approaches and Solutions

Keys to Success: Standards, Metadata and Experience

Q&A

Agenda

3November 2007

Established in 1982

Leading ISV for Software AG

70% penetration in North American market

Consultants with 20+ years SAG experience

More than 300 man years of experience

Over 700 customers worldwide

20 products

30 employees

Introduction to Treehouse Software

4November 2007

Strategic Partners

Anubex

ACS Government Systems

Benaroya

B.O.S. Software Service und

Vertrieb GmbH

CCA Software Pty. Ltd.

CA

Cronus Consulting Pty

Cubeware GmbH

DataMirror Corporation (IBM)

EDS Atlantic Region

E-Net Corporation

Harvest Moon Computing Pty. Ltd.

Intelligent Commerce Network LLC

NatWorks, Inc.

Policy Studies, Inc.

SAIC

Solution Specialists, Inc.

The Software Revolution, Inc.

Wostmann & Associates

Technology Partners

Fujitsu Siemens Computers

Hewlett-Packard

IBM Corporation

Microsoft

Oracle

SAP*

Sun Microsystems

Marketing Representatives

AustraliaCCA Software Pty Ltd.

Brazil 3CON Consultoria e Sistemas Ltd.

Germany VersaTec IT Services

JapanE-Net Japan

Singapore and Far EastBachoJames Inc.

South AfricaBateleur Software (Pty) Ltd.

Partnerships give

Treehouse

international

presence and

broaden our

capabilities

5November 2007

Treehouse Offerings

Data Management

• ADAMAGIC

• ADAREORG

• ADASTRIP

• AUDITRE

• SECURITRE

• TRIM

Mainframe Emulation

• SEDIT

• S/REXX

• S/REXX Debugger

Professional Services

• Data Warehousing and

Business Intelligence

• Data Transfer

• Application Modernization

and Migration

• DBA Services

• Performance and Tuning

• Product Installation

• Training

Data Transfer

• tRelational

• tRelationalPC

• DPS

• DPSync

• DPS X-Link

• NatQuery

• NatCDC

• tcACCESS

• DataMirror Products

Application Management

• CHART

• N2O, N2O/3GL

• EspControl

• PROFILER

6November 2007

Treehouse Customers

7November 2007

"I would strongly recommend the use of the tRelational and DPS products for

any other State agencies that are currently utilizing ADABAS, especially if they

need to do any migration to another platform for data warehouses."

Nancy Kane

Systems & Programming DBA Manager

Arizona Department of Economic Security

"tRelational and DPS are the tools that allowed us to reach our goals in a

pragmatic and non-invasive way."

Roberto Licandro

Architect - IT Architectures 
B-Source SA

Treehouse Customers

8November 2007

"In our deployment of field identification

capabilities, having current data available on

criminal histories as part of that process is

critical.”

Captain Dickerson

Commander of Technical Services

Sacramento County Sheriff's Department

"DPSync allows us to take a big step forward

without replacing CJIS.”

Albert Locher

Assistant Chief in the

Sacramento County District Attorney’s Office

"...it was clear that tRelational/DPS was the leading

product for ADABAS-to-RDBMS data transfer.”

Doug Kauffroath

MIS Director for the Sacramento Superior Courts

Treehouse Customers

9November 2007

Federal Government

– Department of Justice

– National Business Center

State and Local Government

– State of Alaska – Department of Public Safety

– State of Arizona – Department of Economic Security

– State of Delaware – Department of Technology Services, Department of Revenue

– State of Utah – Department of Workforce Services

– State of Washington

– State of Hawaii

– County of Sacramento

– UK Driver and Vehicle Licensing Agency (DVLA)

– City of Calgary

– Service Nova Scotia

Sample Data Transfer Customers

10November 2007

Higher Education

– Case Western Reserve University

– Florida Community College Software Consortium

– Miami University of Ohio

– Penn State University

– University of Texas Austin

Private Sector

– Argus Health Systems

– B-Source

– Cutler Hammer

– Dexia Banque Internationale à Luxembourg S.A.

– First American Real Estate Solutions (FARES)

– Food Lion

– GMAC

– Kansas Nebraska Energy (KNE)

– National Fuel Gas

Sample Data Transfer Customers

11November 2007

Legacy modernization initiatives view data modernization as a small component

- yet -

Failure of the data modernization process can and does cause failure of the entire project

Issues in Data Modernization

Whenever a particular data representation is to be expressed in a

foreign representation, there is great opportunity for mistranslation

12November 2007

Lack of useful, up-to-date, a accurate documentation

Discrepancies between logical and physical definitions

Discrepancies between processing environments (e.g., development vs. production)

Discovery/Analysis of Source Data Structures

nd

13November 2007

Domain analysis

Unused elements

“Seasonal” or “state change” elements

Record typing

Index usage

Validation of application assumptions

Insight into Actual Data Content

14November 2007

Hidden aspects of the data model

Multiple usages of fields/columns, records/rows and files/tables

Feature and datatype usage that cannot be accurately represented in the target environment or database

Proprietary Aspects of the Source

15November 2007

Need to not only reflect the structure and content of the legacy source, but also its behavior

Must specify, design and implement appropriate mappings and transformations

Requires deep technical knowledge of the source and the target technologies

Data Modeling and Design of the Target

16November 2007

Need a central store of information on the source, the target, and the relationships between them

Must support iterative and interim development

Metadata needs modernization too—legacy data documentation should not be discarded

Maintaining the Metadata Repository

17November 2007

“Lowest common denominator” leaves too much to be desired

Throughput needs to be maximized

Ensure correct interpretation and formatting

Leveraging Rich Native Interfaces

18November 2007

Iteration is inevitable

Deployments must be tested repeatedly and comparatively

Data currency demands may escalate

Employing an Evolutionary Methodology

19November 2007

Different modernization approaches place different demands on aspects of the technology architecture

Necessity to make legacy data available to new applications rarely fits conveniently into “batch windows”

Tight DBA resource control may no longer be feasible

Impact on Production Systems

20November 2007

Approaches and Solutions

21November 2007

Extracting legacy data changes (CDC) by:

Comparison to prior state

Capture from database log or exit

Programmatically by timestamp

Generally requires initial Extract-Transform-Load (ETL)

May be accomplished in batch, in near-real time or in real time

Products include: DPSync, tcVISION, NatCDC, DataMirror Transformation Server (/ES)

Data Replication

22November 2007

Advantages:

Low impact on source

Low volume of data to be transmitted

Can process only committed transactions

Disadvantages

Always some degree of latency

Multidirectional replication is extremely complex

Requires robust recovery and monitoring capabilities

Data Replication

23November 2007

Inserting one or more technology layers (servers) between the legacy source and the consuming application

May be read-only or read/write

Products include: tcACCESS, DPS X-Link

SQL/SOA Enablement

24November 2007

Advantages:

Zero latency in data

Legacy data directly integrated into applications

Disadvantages

Difficult to control amount of data transmitted and resources used

Query isolation may be assumed but not delivered

Consuming applications need metadata

SQL/SOA Enablement

25November 2007

Extraction of source data with appropriate transformation to meet the needs of the target platforms and applications

Products include: tRelational/DPS, NatQuery

Data Migration

26November 2007

Advantages:

Applications work with native, modern data sources—no compromises

Ultimately, reduction in cost and complexity of technology architecture

Disadvantages

―Big bangs‖ are not feasible, so coexistence/phased implementation support is needed

Must select a point in time to migrate

Data Migration

27November 2007

Keys to Success

28November 2007

Discovery and analysis of ADABAS source data structures

Compares FDT to PREDICT

Flags post-implementation changes to either

Insight into actual data content and use of proprietary ADABAS datatypes and features

Analyses of MU/PE fields, datatypes

Validation of application assumptions

All information captured into metadata repository

TSI’s tRelational/DPS as a Case Study

29November 2007

TSI’s tRelational/DPS as a Case Study

30November 2007

Data modeling and design of the RDBMS tables

High-productivity modeling environment

Supports mapping to many complex simultaneous RDBMS targets

Complete, native RDBMS schema generation

Generation of capabilities to mimic ADABAS features

Complete, standards-based Java data-access layer generation

TSI’s tRelational/DPS as a Case Study

31November 2007

TSI’s tRelational/DPS as a Case Study

The product implements and applies detailed technical

knowledge of the source and target

32November 2007

Native interfaces to source and target

Direct processing of static data source generated by ADABAS utility

Native formatting of output for RDBMS loader

Supports an evolutionary methodology

High productivity and performance enables iteration

Early and iterative response to data quality issues

Facilitates prototyping of new applications

TSI’s tRelational/DPS as a Case Study

33November 2007

Minimized extraction impact

No workload placed on ADABAS

Support for phased ADABAS-to-RDBMS migration project implementation

Native log processing for CDC

Transformation to RDBMS-native SQL

Seamless adaptation to real-time processing with DPSync

Bidirectional and multidirectional replication capabilities available via tcACCESS and DataMirror

TSI’s tRelational/DPS as a Case Study

34November 2007

TSI has led the ADABAS-to-RDBMS market with constant innovation for over 12 years

Products have benefited from know-how derived from real-world projects

TSI is able to offer an array of solutions to meet any ADABAS data modernization requirement

TSI partners with companies like Microsoft, Oracle, TSRI, Anubex, and innoWake to mitigate the risk of ADABAS data modernization

Experience Counts

35November 2007