TREETIP: tcVISION now supports IAM Files – a solution of Innovation Data Processing

IAM

“The Innovation Access Method (IAM) is a transparent alternative to VSAM KSDS, ESDS, and (as a cost option) to AIX and RRDS files. The savings achieved over VSAM can vary, but IAM typically uses 40-80% less I/Os, 20-70% less CPU and 30-70% less DASD. Savings in batch elapsed times and online response times can range from 20-80%.“ (INNOVATION Data Processing)

Users of IAM files now have the possibility of replicating data into any DBMS and NoSQL DBMS systems in the distributed systems environment as well as into Cloud and Hadoop platforms in real-time with tcVISION. Thus, the latest technology can easily be used for Analytics and Business Intelligence. tcVISION also supports bidirectional synchronization between IAM files and DBMS in the distributed environment. Therefore data between Oracle, SQL Server, DB2 LUW, Informix, Adabas LUW can be synchronized in real-time without programming effort. The transparent integration of IAM files in a heterogeneous system environment can be easily and quickly implemented.

Find out more about tcVISION — Enterprise ETL and Real-Time Data Replication Through Change Data Capture

tcVISION provides easy and fast data migration for mainframe application modernization projects and enables bi-directional data replication between mainframe, Linux, Unix and Windows platforms.

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tcVISION acquires data in bulk or via change data capture methods, including in real time, from virtually any IBM mainframe data source (Software AG Adabas, IBM DB2, IBM VSAM, IBM IMS/DB, CA IDMS, CA Datacom, even sequential files), and transform and deliver to virtually any target. In addition, the same product can extract and replicate data from a variety of non-mainframe sources, including Adabas LUW, Oracle Database, Microsoft SQL Server, IBM DB2 LUW and DB2 BLU, IBM Informix and PostgreSQL.


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Visit the Treehouse Software website for more information on tcVISION, or contact us to discuss your needs.

Treehouse Proof of Concept: Bi-directional Replication Between Adabas and SQL Server

Chris Rudolph and Kevin Heimbaugh, Senior Technical Representatives for Treehouse Software, visited a customer site (a large retail and distribution company) to perform a five-day proof of concept (POC) of tcVISION with bi-directional replication between Software AG’s Adabas and Microsoft SQL Server.

Chris and Kevin initially met with the customer team, consisting of the DBA, Applications Manager, and a technical applications person. The agenda for the week was set to:

  • Import metadata from several Adabas files
  • Bulk load the Adabas data into SQL Server
  • Set up replication from Adabas to SQL Server
  • Add the bi-directional replication back to Adabas

Additionally, there were a few other items the customer wanted the Treehouse team to address, including support for date formats; timestamps for bi-directional replication to avoid update conflicts; using Predict views to define multiple SQL Server tables; and support for MUs and PEs. Chris noted that everything on the customer’s list is easily supported, and there are several options for the update scenarios that can be used.

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After the tcVISION components were installed, the POC began by using tcVISION’s Control Board to define a metadata repository database in SQL Server. Once that was set, the teams moved on to import the first Adabas file’s metadata using tcVISON’s Metadata Import Wizard. As part of this process tcVISION generated Adabas to SQL Server schemas and field-to-column links as well as created target tables in SQL Server. Bulk Transfer scripts were created using a wizard to read the Adabas file on the mainframe, and load the data into SQL Server using the SQL Server bulk loader. Chris created a control script to show how tcVISION can concurrently bulk transfer multiple Adabas files into SQL Server This required increasing the tcVISION Manager’s VSE partition size to successfully test multiple load scripts executing in parallel.

The teams moved on to define the real-time change data capture (CDC) scripts necessary to process the Adabas PLOG. The tcVISION scripts use a two-phase approach to queue captured Adabas transaction on the open platform, then transform and apply the transactions to SQL Server. The scripts were set up to automatically generate detailed logs to track the PLOG transactions captured, SQL statements successfully applied to SQL Server, failed SQL statements, and informational items such as auto-corrected data and transactions rejected due to processing rules.

Now that several tables were defined and loaded, the bi-directional process was set up. SQL Server CDC was enabled for each table to be replicated. The team made a change within SQL Server and verified that the change show up in the SQL Server CDC tables. The SQL Server-to-Adabas mappings were defined in the tcVISION metadata repository, including the “back update check” to ensure only non-tcVISION transactions are captured, and the scripts on both Windows and mainframe were defined to create the LUWs from the SQL Server CDC and apply the changes to Adabas.

CDC from SQL Server to Adabas was successfully tested. Chris then showed the ability to create Journal replication where each change can be captured by replication type. The team spent time creating a few more mappings so multiple file / table updates could be tested, in addition to doing updates while the scripts were stopped to simulate a lost connection. This included setting up a new script to process copied PLOG datasets created by the ADARES utility.

The team defined the remainder of their Adabas files to the metadata repository. Some were set them up for bi-directional replication, and others were setup for unidirectional replication and Journal replication. Everything work as expected at the wrap-up meeting where the team provided a live demonstration to management of tcVISION and the items accomplished. The final tcVISION presentation and demo went very well, and everyone was pleased with the progress made during the week.


Find out more about tcVISION — Enterprise ETL and Real-Time Data Replication Through Change Data Capture

tcVISION provides easy and fast data migration for mainframe application modernization projects and enables bi-directional data replication between mainframe, Linux, Unix and Windows platforms.

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tcVISION acquires data in bulk or via change data capture methods, including in real time, from virtually any IBM mainframe data source (Software AG Adabas, IBM DB2, IBM VSAM, IBM IMS/DB, CA IDMS, CA Datacom, even sequential files), and transform and deliver to virtually any target. In addition, the same product can extract and replicate data from a variety of non-mainframe sources, including Adabas LUW, Oracle Database, Microsoft SQL Server, IBM DB2 LUW and DB2 BLU, IBM Informix and PostgreSQL.


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Visit the Treehouse Software website for more information on tcVISION, or contact us to discuss your needs.

tRelational / DPS Adabas-to-Oracle Success in South Africa

by Hans-Peter Will, Senior Technical Representative and Joseph Brady, Manager of Marketing and Technical Documentation at Treehouse Software, Inc.

Recently, Hans-Peter Will, Senior Technical Representative for Treehouse Software, traveled to South Africa to assist our partner Bateleur Software (pty) Ltd. with setting up a large public-sector customer’s data replication implementation using our Adabas-to-RDBMS tool set, tRelational / DPS (Data Propagation System).

Arriving in Johannesburg, Peter met with representatives from Bateleur and the IT Organization, where the key players discussed how tRelational / DPS was going to be used in the project. The customer initially wanted to populate sample data into Oracle, so Peter configured tRelational / DPS to process one of the smaller Adabas files to generate some data. He also recommended running an analysis with tRelational to determine whether the file contained a unique key. Peter took this opportunity to show the customer what other benefits they could realize out of the analysis information. Interestingly, they used a personnel file for analysis, and Peter was immediately able to show that 23 of the records had no gender entry and 180 of records had no surname. The customer was very pleased to see these revelations in the first analysis, and looked forward to identifying other data quality issues before commencing data replication.

Customer Replication Scenario with Treehouse Software Product Set…

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The next step was to build the target structure in accordance with the Oracle DBA’s requirements. The DBA had specified that all columns were to be defined as VARCHAR2, except the date information. After the first model was completed, DDL and DPS parameters were generated and a quick materialization of data accomplished the desired result.

At the subsequent kickoff meeting, Peter provided a complete tRelational / DPS overview and discussed the target structure with the attendees and the Oracle DBA. The rest of the day was spent doing Adabas file implementations, analysis and modeling.

Setup was then completed for transferring extracted and transformed Adabas data into the customer’s Windows environment. Adabas Vista is used, so that one logical Adabas file was actually split into two files stored on different Adabas databases, and the customer wanted to combine them into the same target table in Oracle. While there was no unique descriptor, it was discovered that three fields in combination would make a unique key, enabling the model to be created to combine data from the separate physical files into a single Oracle table.

The team proceeded with file implementation, modeling, mapping, DPS executions, and resolving data issues. Various issues that were encountered, like invalid tab characters within the data, negative personnel numbers, duplicates in unique keys (maintained by the application) and the need to add an extra column to the output. These issues were resolved quickly by the customer’s staff.

Within a day, all the files were materialized and the PLOG copy process was modified so that from that point forward, every PLOG copy would automatically be processed through DPS Propagation to update the RDBMS on the target Windows machine.

The next day, Peter was asked by the customer, “How many of the files have been processed so far?”. Peter was pleased to report that every file was processed and was propagating successfully. The happy customer remarked that they never had a project that was completed this far ahead of the deadline.

Throughout the project, Peter never personally laid hands on a customer keyboard, but instead sat with staff, effectively training them and handing over comprehensive knowledge of tRelational / DPS. The customer was very excited to learn that their personnel can now easily use the product set to do any remaining work on their own.

A few days later, we received an e-mail from Bateleur:

“I had a very pleasant meeting with the customer today. They used tRelational to reject the non-unique keys, reran the Materialization, and reran DPS plus update into Oracle. The month-end update of Oracle that was taking nearly three days to complete, now takes five Minutes! Everyone delighted!”

Bjørn (Sam) Selmer-Olsen, Managing Director, Bateleur Software (pty) Ltd


About Treehouse Software’s tRelational / DPS Product Set

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tRelational / DPS is a robust product set that provides modeling and data transfer of legacy Adabas data into modern RDBMS-based platforms for Internet/Intranet/Business Intelligence applications. Treehouse Software designed these products to meet the demands of large, complex environments requiring product maturity, productivity, feature-richness, efficiency and high performance.

The tRelational component provides complete analysis, modeling and mapping of Adabas files and data elements to the target RDBMS tables and columns. DPS (Data Propagation System) performs Extract, Transformation, and Load (ETL) functions for the initial bulk RDBMS load and incremental Change Data Capture (CDC) batch processing to synchronize Adabas updates with the target RDBMS.

Visit the Treehouse Software website for more information on tRelational / DPS, or contact us to discuss your needs.

TREETIP: Integrate Mainframe Data Sources In Your Big Data Initiatives

tcVISION supports a vast array of integration scenarios throughout the enterprise, providing easy and fast data migration for mainframe application modernization projects and enabling bi-directional data replication between mainframe, Linux, Unix and Windows platforms. This innovative technology offers comprehensive abilities to identify and capture changes occurring in mainframe and relational databases, then publish the required information to an impressive variety of targets, both on-premise and Cloud-based.

Analysts have observed that perhaps 80 percent of the world’s corporate data still resides on mainframes. So it’s no surprise that Bloor Research (http://www.bloorresearch.com/research/spotlight/big-data-and-the-mainframe/), notes that “it is necessary today to place the mainframe as a ‘first-class player’ in any enterprise Big Data strategy.”

In February 2017 we highlighted tcVISION’s support for replication to the leading NoSQL database MongoDB. MongoDB continues to increase in popularity as a back end for operational applications with real-time requirements.

tcVISION also supports analytics and “mainframe offload” Big Data use cases that generally leverage Hadoop HDFS and/or streaming data transport. With tcVISION, data from a wide variety of IBM mainframe data source can be quickly and easily replicated to Big Data targets, requiring minimal mainframe know-how and having minimal impact on the mainframe.

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Boost the return on investment for your Big Data initiatives using tcVISION!


Find out more about tcVISION — Enterprise ETL and Real-Time Data Replication Through Change Data Capture

tcVISION provides easy and fast data migration for mainframe application modernization projects and enables bi-directional data replication between mainframe, Linux, Unix and Windows platforms.

_0_tcVISION_Simple_Diagram

tcVISION acquires data in bulk or via change data capture methods, including in real time, from virtually any IBM mainframe data source (Software AG Adabas, IBM DB2, IBM VSAM, IBM IMS/DB, CA IDMS, CA Datacom, even sequential files), and transform and deliver to virtually any target. In addition, the same product can extract and replicate data from a variety of non-mainframe sources, including Adabas LUW, Oracle Database, Microsoft SQL Server, IBM DB2 LUW and DB2 BLU, IBM Informix, and PostgreSQL.


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Visit the Treehouse Software website for more information on tcVISION, or contact us to discuss your needs.

Treehouse Software Onsite Training Classes are Available

New installation of a Treehouse Software product? New employees? Need a refresher course? Want to explore untapped product features? Three-to-five-day training sessions are available for tRelational / DPS and other Treehouse products.

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Treehouse Software training sessions are customized to meet your site’s unique environment and needs. As an example, the following three-day tRelational / DPS training class was conducted at a large University where they are using tRelational / DPS to create an archive of their legacy Adabas data to Oracle in preparation for their upcoming mainframe system retirement.

Over the course of the three-day session, the Treehouse instructor covered:

  • tRelational AUTOGEN feature (auto-generation of complete RDBMS schemata – Tables, Columns, Primary Key, and Foreign Keys – based upon existing ADABAS file structures). AUTOGEN was quite attractive since it will be a very time efficient way to create the Adabas-to-Oracle mappings.
  • The customer wanted to use Relational / DPS to automate as much of the process as possible, and take advantage of the batch functions of tRelational. Generally, the workshops of the class are all online, but in this case, the class ran through one online example after the File Implementation section of the training, and then jumped to the batch section of the training to show how that works. The class then returned to run additional File Implementations, Analysis, and Reporting in batch.
  • The class continued through the Modeling and Mapping section, and ran more batch jobs with some additional Adabas files.
  • Admin and Configuring DPS Parameters sections were next on the agenda. Because of the desire to automate as much as possible, the work focused on how to set up a single job stream that could be generated programmatically, where it was fed in the name of the file to be implemented and then do the AUTOGEN all in the same job. The tRelational AUTOGEN user exit was set up so the customer could identify and cater to the possibility of duplicate table names where multiple Adabas files have the same named MU (like “COMMENTS”); and handle the addition of an ETR (external transformation routine) being automatically added (there were some known HEX values in some fields) and then update the DPSCOLLGTH.
  • The class finished up the Materialization (initial loading of data) training section and then set up the jobs to run Materialization, and installed DPSSPLIT (used to separate the control and data files into one control and one data file per table materialized) on one of their servers. Generally, most class attendees are not the ones responsible for running the Materialization and Propagation (ongoing synchronization of data) jobs, so the instructor doesn’t usually set them up, but in this case, it made sense. The class started out by running the Materialization from a full database ADASAV taken over the weekend. The output of the Materialization job was FTPed to their Server and DPSSPLIT run against it to create the individual loader files. GENDDL (generate the control statements that can be passed to the RDBMS to define the tables and columns) was also run and that output transferred. After setting up the SQL job to process the DDL, the Oracle SQL*LOADER was successfully run to load the data.

Finally, the class went through some additional tRelational / DPS features, and as a final exercise, set up a Propagation job and ran it against a current PLOG just to make sure it worked satisfactorily.


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If you are interested in finding out more about Treehouse training classes for your product, contact Treehouse Software today for more information, or to schedule onsite training.

TREETIP: tcVISION Supports Data Replication to MongoDB

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The tcVISION cross-system integration platform is a robust, proven, and mature solution that is constantly under development to meet the requirements of new technologies, including support for MongoDB.

mongodb

MongoDB is among the leading NoSQL databases in the market and has been developed for the needs of today’s information technology. MongoDB supports a data model with dynamic schemata and is especially suitable to store large amounts of data using GridFS. It contains automatic failure protection using an integrated replication. MongoDB also offers native, idiomatic drivers for nearly all programming languages and frameworks.

Find out more about MongoDB here: https://www.mongodb.com

In addition to support for MongoDB, tcVISION features connectivity to other output targets, such as Hadoop (see previous blog about Hadoop support), Adabas LUW, DB2 BLU, and EXASOL. Additionally, new input sources include z/OS VSAM Logstream (CICS and Coupling Facility / Shared VSAM), z/OS VSAM Batch Extension, z/OS DBMS to Logstream, CA IDMS v17, CA Datacom CDC, IMS Active Log, and SMF data.

Find out more about tcVISION — Enterprise ETL and Real-Time Data Replication Through Change Data Capture

tcVISION provides easy and fast data migration for mainframe application modernization projects and enables bi-directional data replication between mainframe, Linux, Unix and Windows platforms.

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tcVISION acquires data in bulk or via change data capture methods, including in real time, from virtually any IBM mainframe data source (Software AG Adabas, IBM DB2, IBM VSAM, IBM IMS/DB, CA IDMS, CA Datacom, even sequential files), and transform and deliver to virtually any target. In addition, the same product can extract and replicate data from a variety of non-mainframe sources, including Adabas LUW, Oracle Database, Microsoft SQL Server, IBM DB2 LUW and DB2 BLU, IBM Informix and PostgreSQL.


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Visit the Treehouse Software website for more information on tcVISION, or contact us to discuss your needs.

Treehouse Software partner, Cognistx to present at The Big Data Summit 2017 in Germany

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Dr. Florian Metze, Partner and Chief Speech Scientist at Cognistx, will be presenting “Speech and Deep QA (Question Answering) Developments” as part of a special Cognitive Computing track at the Big Data Summit 2017 to be held in Germany, February 16, 2017.

Dr. Metze will be showcasing how Cognitive Computing, Deep QA and context sensitive end-to-end ASR can be utilized to provide extremely intelligent solutions with an extremely simple user interface. The user can ask questions about e.g. their wireless devices and bills, power tools and home appliances, etc. The system proactively engages the user via a Question Generation (QG) module and then provides the right solution or content based on the user queries. The strength of the solution lies in an intuitive voice user interface, an interactive QG module, and its ability to synthesize large quantities of structured and un-structured data to provide the right answer based on the user query.

He will also discuss recent trends in US academia and industry that have been enabled by the rapid development of Artificial Intelligence using large amounts of data and novel machine learning algorithms.

Dr. Florian Metze is an Associate Research Professor at Carnegie Mellon University. He holds a PhD from Universität Karlsruhe (TH), and has previously worked at Deutsche Telekom Laboratories. Dr. Florian is currently a Partner and Chief Speech Scientist at Cognistx.

For more information on this event, visit the BITKOM Big Data Summit website.


The Treehouse Software / Cognistx Connection

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Additionally, representatives from Treehouse will be in attendance with Cognistx at the Big Data Summit. Rolf Vollmer, Treehouse Software European Sales Manager and Hans-Peter Will, Treehouse Software Senior Technical Representative will be available to meet with those interested in learning about how the Cognistx platform complements Treehouse Software’s tcVISION. tcVISION is the comprehensive product that can acquire data in bulk or via change data capture methods, including in real time, from virtually any IBM mainframe data source (Software AG Adabas, IBM DB2, IBM VSAM, IBM IMS/DB, CA IDMS, CA Datacom, even sequential files), and transform and deliver to virtually any target. In addition, the same product can extract and replicate data from a variety of non-mainframe sources, including Adabas LUW, Oracle Database, Microsoft SQL Server, IBM DB2 LUW and DB2 BLU, IBM Informix and PostgreSQL.