Friends from Europe and Across the U.S. Visit the Treehouse

Friends from Europe and Across the U.S. Visit the Treehouse

The week of September 21, 2017 found Elisabeth Schwarz and Beat Münch from Treehouse Software’s German partner, B.O.S. Software Service und Vertrieb GmbH paying us a visit.

B.O.S. stands for Better Operative Solutions. B.O.S. originally developed and distributed software that made 3270 applications more user friendly before focusing on Enterprise Data and Application Integration with Treehouse-marketed tcACCESS and tcVISION – Direct Data Access and Data Synchronization / Replication / Exchange / Migration.

While Elisabeth and Beat were in town, we decided to have the entire Treehouse staff come in to Pittsburgh headquarters as well. The week was a very productive one, with Treehouse and B.O.S. staff having meetings on many new product initiatives and current customer developments.

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Treehouse Software staff and friends outside of Treehouse headquarters in Sewickley, PA (from left to right): Rolf Vollmer, European Sales Manager (Germany); Mitch Doricich, National Sales Manager; Elisabeth Schwarz, General Manager at B.O.S.; Norbert Geuettner, Senior Developer; Kevin Heimbaugh, Senior Technical Representative; Hans-Peter Will, Senior Technical Representative (Germany); George Szakach, President; Karen Dunlap, Senior Developer; Mike Kuechenberg, Senior Technical Representative; Lynn McIntyre, Technical Coordinator; Frank Griffin, Senior Developer; Andy Jones, Senior Technical Representative; Linda Woodham, Secretary; Dan Webster, National Sales Manager; Russell Roll, CFO; Chris Rudolph, Senior Technical Representative; Beat Münch, Chief Technology Officer at B.O.S.; Paul Linn, Senior Developer; Joe Brady, Marketing and Documentation Manager.

Of course, there can’t be a get-together at the Treehouse without some fun, and Michael Szakach, Treehouse Marketing Consultant and Event Organizer saw to it that our guests and staff enjoyed visiting some of Pittsburgh’s more unusual and fun attractions, in addition to a very nice night out with great food and conversation!

The Treehouse caravan brought everyone to downtown Pittsburgh to visit Bicycle Heaven Museum, Randyland, The Mattress Factory Art Gallery, and Johnny Angel’s Ginchy Stuff and Music Museum.

Bicycle Heaven Museum

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Bicycle Heaven Museum is the world’s largest bicycle museum and shop, as seen in the New York Times and Associated Press. Rated on Trip Advisor as the #1 Pittsburgh Museum and voted top bike shop in Pittsburgh.   You can get your bike fixed, tuned up, or trade it in for a newer (or older) bicycle.


Randyland

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Randyland is the home of artist, Randy Gilson. Located in the Mexican War Streets district of Pittsburgh’s Northside. Visitors are welcome to come and explore the public art displays in and around the property.


The Mattress Factory

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The Mattress Factory is a contemporary art museum and experimental lab featuring site-specific installations created by artists in residence from around the world.


Johnny Angel’s Ginchy Stuff and Music Museum

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Johnny Angel has been in the music and entertainment industry for over 45 years and has great stuff to go along with his illustrious career. From autographed pictures to memorabilia, he has it all at Johhny Angel’s Ginchy Stuff. Johnny has what you thought you had forgotten about – from pennants to pictures, and 45s to 78s, he has it all!


The last full evening, Emilie and George Szakach invited all 24 staff and visitors to dinner at one of our local favorite restaurants, called Willow.

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Overall, everyone had a very productive and fun week. We look forward to continued success with our friends from B.O.S., and of course, more visits!


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Visit our website for more information on Treehouse Software.

 

Treehouse Software Eases the Challenges for Mainframe-to-Modern Platform Transformation Programs for Systems Integrators

Unlock Your Customers’ Business Value Faster with Frequent Production Deliveries, Using Agile Methods

Treehouse Software’s product, tcVISION has proven to be vital for the ease and success of many mainframe modernization initiatives.

A big problem for a Systems Integrator (SI), or any mainframe modernization vendor, is the myriad of dependencies between mainframe and open systems data and components. As part of a mainframe modernization project, these vendors need to determine the ordering of phases or waves of applications to be migrated. There are often shared databases that can make it very difficult to move one set of applications without moving others. This can result in the conclusion that they must go with a “big bang” approach, which can lead to a bid for a program with one large delivery at the end with all of the integrated components in place. This is very unappealing to customers as they are paying out big dollars without the corresponding business value of a production deployment. This approach also significantly increases the project risk.

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With Treehouse Software’s bi-directional replication product, tcVISION, a subset of applications can be migrated, and tcVISION’s data synchronization capabilities can be used to bridge specific shared legacy mainframe databases to the modern database versions on open systems. This allows them to deliver in phases, thus getting modernized modules in production faster. In addition, it decreases risk as issues can be found much faster with the more frequent production deployments. When the last modules are deployed to production, they would no longer need the synchronization.

As an example, a large Treehouse customer is currently involved in gradually modernizing and replacing a set of applications, and is using a similar approach. The customer will be using their mainframe Adabas database synced with Oracle on Linux, while in the process of modernizing the applications. Treehouse Software’s experts and tcVISION product are making sure the customer’s transition goes smoothly and seamlessly.


Enterprise ETL and Real-Time Data Replication Between Virtually Any Source and Target

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.

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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, 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, Hadoop/HDFS, MongoDB, Oracle Database, Microsoft SQL Server, IBM DB2 LUW and DB2 BLU, IBM Informix, PostgreSQL, etc.


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

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

tReDPS_DIAGRAM

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.