1 trelational/dps overview. 2 adabas data transfer: business needs and issues trelational & dps...

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tRelational/DPS Overview

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ADABAS Data Transfer: business needs and issues

tRelational & DPS Overview Summary Questions? Demo

Agenda

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Transfer legacy ADABAS data to integrate: Business intelligence Reporting systems Web enablement Purchased COTS/ERP application(s)

One-time conversions Application reengineering/conversion Platform change

Business Needs

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Cost: development, operation and maintenance Time: deployment, execution, and maintenance Resources: human and machine Risk: data discovery/integrity and project

deadlines Complexity: ADABAS to RDBMS transformations Performance: coexistence with with ADABAS

OLTP Flexibility: response to discovery and change in

application or requirements Vendor: product focus, experience and longevity

Business Issues

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Reporting & Business Intelligence

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tRelational, an ADABAS-to-RDBMS modeling, mapping, and data analysis tool

Data Propagation System (DPS), an ADABAS-to-RDBMS data migration and propagation system for data distribution and warehousing

tRelationalPC, a Windows-based client/server GUI data modeling and mapping environment (included with tRelational)

Treehouse Remote Access (TRA), middleware that allows tRelationalPC to communicate with tRelational on the mainframe (included with tRelational)

Product Components

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Modeling and Mapping Native ADABAS/NATURAL application Predict metadata “discovery” and ADABAS file analysis Automated generation of normalized RDBMS

schemata with explicit ADABAS field to RDBMS column mapping

Robust modeling and mapping – normalize, denormalize, substring, concatenate

Single rule base and metadata repository

“Code” Generation RDBMS Data Definition Language (DDL) – create

tables, columns, and constraints DPS Parameters – extract and transformation

parameters

tRelational Features

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tRelational and DPS Functionality

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tRelational and DPS Functionality

Captures Logical (PREDICT) and Physical (ADABAS FDT) file definitions and resolves any discrepancies. The implementedfile provides the basis for modeling and mapping to the RDBMS table(s).

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tRelational and DPS Functionality

Captures statistical analysis to provide or confirm the understanding of the sourcedata. The analysis provides for improved modeling and early identification of “problem” data.

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tRelational and DPS Functionality

Provides physical modeling and explicit ADABAS to RDBMS mapping. Auto Generation provides intelligent and “automatic” modeling and mapping from an Implemented File.

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tRelational and DPS Functionality

tRelational generates all input parameters needed to beginMaterialization and Propagation.

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tRelational and DPS Functionality

tRelational generates output for the creation of tables, columns, and constraints for your target RDBMS.

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tRelational Data Analysis and Modeling

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tRelational and DPS Functionality

The Materializationprocess requires

NO DIRECTADABAS ACCESS

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tRelational and DPS Functionality

Extracts from anADABAS utility backup.

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tRelational and DPS Functionality

The extracted data is transformedInto a relational form.

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tRelational and DPS Functionality

RDBMS tables are then populatedby the native RDBMS loader utility(e.g., Oracle SQL*Loader).

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tRelational and DPS Functionality

The Propagationprocess requires

NO DIRECTADABAS ACCESS

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tRelational and DPS Functionality

ADABAS transaction data isextracted from the ADABASProtection Log files.

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tRelational and DPS Functionality

The extracted data is transformed into SQL “UPDATE”, “INSERT”,and “DELETE” statements.

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tRelational File Implementation

Capture logical (Predict) file,Userviews, and physical(FDT) definitions.

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tRelational File Implementation

Fields that are definedlogically and physicallydifferent are highlighted.

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tRelational ADABAS File Analysis

One time capture of statisticalanalysis of repeating data (MUs and PEs), candidatevariable text data, and descriptors for improvedmodeling.

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tRelational ADABAS File Analysis

Statistics of MUs and PEs forsizing of child tables and potential de-normalization oftables to individual column(s).

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tRelational ADABAS File Analysis

Statistics of alphanumericfields for candidate variablecharacter text columns.

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tRelational ADABAS File Analysis

This screen shows descriptor/superdescriptor usage statistics to determine candidate Primary Keys and indexed columns.

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RDBMS Schema Auto-Generation

Generates table(s), columns,constraints, and mappings fora selected implemented file.

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tRelationalPC offers an alternative GUI-based modeling and mapping environment communicating via TCP/IP with the mainframe tRelational repository.

tRelationalPC

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Auto Generation Example:Four tables with Primary Key andForeign Key constraints, and theadded DPS PE Sequencer (PE occurrence).

tRelationalPC Auto-Generation

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RDBMS Data Definition Language (DDL) DPS specifications (parameters) for ETL

and CDC Processing Metadata reports (Summary and Detail) tRelational API enables Metadata export

to other tools and repositories

Output Generated from Metadata

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Generated RDBMS DDL

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Written in Assembler for efficiency Executed as batch job No calls to active ADABAS required

No impact on production environment External Transformation Routines (ETRs)

A call to a linked object Dozens of built-ins Custom transformation and data

cleansing

DPS Architecture

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DPS Materialization (ETL)

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Provides initial load of the RDBMS Extracts from ADASAV Intelligent transformation based on

model/mappings Generates rows for target table(s) and SQL

Utility Load Control statements Provides refresh of the RDBMS when

required or desired

DPS Materialization

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Contains all row images to beloaded into the RDBMS repository.Each row is prefixed with a Table ID,and is formatted and delimited nativelyfor the RDBMS loader.

DPS Materialization Data

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Native loader control statementsare automatically generated witheach DPS Materialization run.

DPS Materialization SQL Utility Load Control

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DPS Propagation (CDC)

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Provides periodic synchronization of the RDBMS target with the source ADABAS database

Extracts from PLOG archives Intelligent transformation based on update

and model/mappings Generates SQL for Inserts, Updates,

Deletes, and Commits

DPS Propagation

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DPS Propagation

Sample SQL resulting from an update toPersonnel ID, mapped to a Primary Key, showing the Deletes and Inserts generated to maintain referential integrity.

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Sample SQL resulting from an update toLANG (MU), modifying GER, ENG toENG, showing the Update and Delete generated to reflect MU “compression”.

DPS Propagation

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A product, not a consulting engagement

Fast configuration and implementation

Data analysis and quality assessment

Automated schema/mapping generation and “code” generation

Supports complex transformations out of the box

Native RDBMS integration out of the box

RDBMS integrity assurance

Cost efficient operation

Zero contention with ADABAS applications

Proven, scalable, reliable, and extensible architecture

Reduced risk and improved quality

Seamless “upgrade” to real-time processing with DPSync

Flexible and easy to maintain

11 Years of Treehouse focus and commitment

Summary of Benefits

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