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1 The Mainframe Data Access & Replication Conundrum In Today's Heterogeneous IT Environment.

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Presentation on theme: "1 The Mainframe Data Access & Replication Conundrum In Today's Heterogeneous IT Environment."— Presentation transcript:

1 1 The Mainframe Data Access & Replication Conundrum In Today's Heterogeneous IT Environment

2 2 Mainframe Integration without Compromise

3 3 Agenda Introduction to Treehouse Software Today’s Situation IT Objective tcACCESS Data Integration tcACCESS SQL Engine tcACCESS Demo tcVISION Data Replication CDC Methods Processing Stages tcVISION Demo Summary

4 4 Introduction to Treehouse Software Established in 1982 Mainframe system tools vendor Leading ISV for Software AG 70% penetration in North American market Consultants with 20+ years experience More than 300 man years of experience Supporting all mainframe operating systems Focus for the past 15+ years on data migration, replication, and integration Over 700 customers worldwide 20 products 30 employees

5 5 Treehouse Customers

6 6 Today’s Situation Heterogeneous IT environments Legacy applications High-availability information systems Data silos Increasing data volumes Exploding costs

7 7 IT Objective Intelligent data integration Efficient data synchronization Cost effective solution Enterprise-wide Data Management through:

8 8

9 9 Enterprise Data Integration Bi-directional data-exchange across heterogeneous systems Direct data access across heterogeneous systems Data transformation for data analysis and exchange tcACCESS Concepts

10 10 Enterprise Data Integration Relational access to legacy data and applications Data federation – heterogeneous data views Integration of mainframe files and DBMS structures Data federation between mainframe and Windows/Open Systems data tcACCESS Concepts

11 11 tcACCESS SQL Engine Host/PC & Host & Web Integration

12 12 tcACCESS SQL Engine More than 90 SQL functions supported Operators (+, -, *, /, ||) Conditional Operators (>, <, =, BETWEEN, LIKE) Logic Operators (AND, OR) INNER and OUTER JOINS GROUP BY, ORDER BY Security may be applied (RACF, ACF/2, Top Secret) Stored Procedure Support

13 13 tcACCESS SQL Engine Different data sources can be JOINed: SELECT IMS.NR, IMS.NAME, VSAM.ADDRESS FROM IMS, VSAM WHERE IMS.NR = VSAM.ID VIEWS can be created Control Options available (MAXIO, MAXROW, NOORDERBY, etc) Global SQL Exit available Field Level Exits available

14 14 tcACCESS Architecture

15 15 Demo

16 16

17 17 CDC Replication Different data formats Different data models Large data volumes Limited batch window Requirement for up-to- date information Moving/replicating data... as much as needed as little... as transparent... as flexible... as secure......AS POSSIBLE The Problem: The Solution:...with

18 18 Data Latency Change Data Capture

19 19 Data volume Change Data Capture

20 20 Mainframe Change Data Capture Change Data Capture Efficient transfer of entire databases Analysis for data consistancy Best for Initial Load prior to log processing Best for periodic mass data transfer One step data transfer

21 21 Mainframe Change Data Capture Change Data Capture Comparison of data snapshots Efficient transfer of changed data since last processing IMS/DB, DL/I, VSAM, DB/2, ADABAS, CA-IDMS, DATACOM, sequential files Flexible processing options (SORT etc.) Automatic creation of deltas by tcVISION

22 22 Mainframe Change Data Capture Change Data Capture Usage of the DBMS logging capabilities IMS/DB, VSAM, DB/2, DL/I, ADABAS, IDMS, DATACOM Transfer of changed data in scheduled time frame Best for batch window Best for processing right after logfile creation

23 23 Mainframe Change Data Capture Change Data Capture Realtime capture of changed data Changes directly obtained from DBMS CA-IDMS, IMS/DB, VSAM, DB/2, DATACOM, ADABAS Secure data storage even across DBMS restart Flexible propagation methods

24 24 Stage 0: Data in internal raw format Stage 1: Data in tcVISION format (before and after images) Stage 2: Data normalized with structure definition Staged Processing Stage 3: Data in DML or Loader format

25 25 Stage 0: Data in internal raw format Stage 1: Data in tcVISION format (before and after images) Stage 2: Data normalized with structure definition Stage 3: Data in DML or Loader format Staged Processing Exit points available at every stage

26 26 Demo

27 27 Summary Relational access to legacy data and applications Data Federation – heterogeneous data views Change Data Processing Bi-Directional real time replication

28 28 Summary tcVISION Architecture

29 29 Summary Bi-directional data-integration and data-synchronization

30 30 E-mail: sales@treehouse.comsales@treehouse.com


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