tRelational/DPS Overview

Agenda ADABAS Data Transfer: business needs and issues tRelational & DPS Overview Summary Questions? Demo

Business Needs 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 Issues 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

Reporting & Business Intelligence

Product Components These are areas that draw upon our existing expertise in ADABAS, relational databases, performance monitoring, and development. Mention that DPS and tRelational are a strategic focus for TSI, a significant amount of our current staff resources are dedicated to their development. TSI has been working on tRelational since 1993 and DPS (in some fashion) since 1994. 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)

tRelational Features Modeling and Mapping “Code” Generation These are areas that draw upon our existing expertise in ADABAS, relational databases, performance monitoring, and development. Mention that DPS and tRelational are a strategic focus for TSI, a significant amount of our current staff resources are dedicated to their development. TSI has been working on tRelational since 1993 and DPS (in some fashion) since 1994. 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 and DPS Functionality

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

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

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.

tRelational and DPS Functionality tRelational generates all input parameters needed to begin Materialization and Propagation.

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

tRelational Data Analysis and Modeling

tRelational and DPS Functionality The Materialization process requires NO DIRECT ADABAS ACCESS

tRelational and DPS Functionality Extracts from an ADABAS utility backup.

tRelational and DPS Functionality The extracted data is transformed Into a relational form.

tRelational and DPS Functionality RDBMS tables are then populated by the native RDBMS loader utility (e.g., Oracle SQL*Loader).

tRelational and DPS Functionality The Propagation process requires NO DIRECT ADABAS ACCESS

tRelational and DPS Functionality ADABAS transaction data is extracted from the ADABAS Protection Log files.

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

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

tRelational File Implementation Fields that are defined logically and physically different are highlighted.

tRelational ADABAS File Analysis One time capture of statistical analysis of repeating data (MUs and PEs), candidate variable text data, and descriptors for improved modeling.

tRelational ADABAS File Analysis Statistics of MUs and PEs for sizing of child tables and potential de-normalization of tables to individual column(s).

tRelational ADABAS File Analysis Statistics of alphanumeric fields for candidate variable character text columns.

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

RDBMS Schema Auto-Generation Generates table(s), columns, constraints, and mappings for a selected implemented file.

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

tRelationalPC Auto-Generation Auto Generation Example: Four tables with Primary Key and Foreign Key constraints, and the added DPS PE Sequencer (PE occurrence).

Output Generated from Metadata 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

Generated RDBMS DDL

DPS Architecture 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 Materialization (ETL)

DPS Materialization 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 Data Contains all row images to be loaded into the RDBMS repository. Each row is prefixed with a Table ID, and is formatted and delimited natively for the RDBMS loader.

DPS Materialization SQL Utility Load Control Native loader control statements are automatically generated with each DPS Materialization run.

DPS Propagation (CDC)

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

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

Summary of Benefits 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