PORTFOLIO OPTIMISATION

Non-Relational to Relational DBMS Conversion

Our Database Conversion solution empowers true business intelligence by integrating non-relational databases still on the mainframe with relational data warehouses. This service is non-invasive, does not require a migration, and does not add to your mainframe footprint. It enables holistic visibility and analysis of key operational data which was previously unavailable while reducing MIPS consumption, shifting reporting functionality off mainframe. Mainframe DataShare, the software behind our Data Conversion solution offers automated provision, ongoing replication, and confirmation of data from non-relational DBMS to Oracle, SQL Server, PostgreSQL, or Db2.

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Know the details, reduce the risk: How to begin your mainframe modernisation journey

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Why modernise?

CHALLENGES

Scarcity of domain expertise

Developers and database administrators who understand mainframe technology are reaching retirement age and no one is trained to replace them, resulting in a steadily diminishing talent pool. As this shortage grows, the costs and risk of relying on legacy systems will continue to rise.

Limited flexibility

Successful digital transformation and business agility hinges on good data. Non-relational databases and the underlying assets that support them were not designed for today’s business demands or modern IT. This results in difficult integrations, inaccessible data, and limited flexibility.

Exorbitant costs

Mainframes cost as much as 4,500 per cent more to operate than equivalent Cloud counterparts. This figure is compounded by rising licensing and maintenance fees for ancillary mainframe applications and databases.

Data Replication

OUR SOLUTION

Being unable to share data across the enterprise makes it difficult to develop new products, understand real costs, and cultivate new business. Replacing a legacy system altogether can be expensive, risky, and could require developer re-training.

Our Data Replication solution offers an alternative approach to migration, detailed below using IDMS as an example. IDMS data is held in a rigid, context-sensitive format which makes business intelligence queries and ETL very complex. Our solution unlocks data into a queryable format while maintaining the data context and business logic. This flexible, automated, and full-featured solution enables companies to achieve integration goals with zero footprint on the mainframe.

Our Data Replication solution consists of three primary modules: The Data Dictionary, Initial Loader, and Ongoing Replication.

Solution implementation begins with data modeling and schema mapping leveraging the Data Dictionary module. The Data Dictionary module includes our System Dictionary, a complete metadata repository, Windows UI navigation, and data mapping rules. This Data Dictionary system generates the Initial Loader configuration and translation engine, target relational database scripts, begins table creation, and creates SQL load scripts. XML definitions of schemas may be used to generate programs and documentation as well. The Data Dictionary system manages all IDMS constructs in this example, including set membership and sequence, redefines / occurs. The Data Dictionary module also handles the next step, establishing conversion rules. IDMS schema and segments are imported via DDDL and the relational schema is automatically generated from the system dictionary. There is a one-to-one relationship between IDMS and relational models by default, and relational schema can be adjusted within the system dictionary. Data mapping rules can also be adjusted within the system dictionary, which also contains views of IDMS, the relational database, and the relationship between the two. Lastly, a relational data model is generated.

Once data modeling, schema mapping, and conversion rules are prepared, the next steps are the initial data load and ongoing replication (including validation and verification).

Initial load is simple and straightforward. We start by transferring the existing REPO backups to Windows, then we run our Loader tool. The Loader converts the non-relational data (IDMS in this example), then runs the generated target database load scripts to populate the relational database.

Ongoing replication is achieved in an equally flexible and straightforward manner. We start by transferring IDMS journals to Windows upon release, then execute our Rollforward utility. This utility ‘rolls forward’ the IDMS updates against the relational database. Validation and verification are critical components of successful delivery. Loader contains its own validation to ensure the referential integrity of the data in the IDMS database is correct, and is maintained during the replication process. Integrity may also be proven by implementing constraints to carry-forward the IDMS integrity rules into the relational database (automatically generated from the system dictionary). We also ensure row counts agree between IDMS, our loader, SQL loader, and relational database, validate the set membership and sequence is the same, and verify that aggregate totals of fields match as appropriate.

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Over 35 years of mainframe modernisation experience

More than 500 successful modernisation projects completed

Over 2.5 billion lines of code refactored through automation

Additional insights to help you modernise

RESOURCES

  • 2021 Mainframe Modernisation Report

    Explore the the impact Covid-19 is having, and will continue to have, on modernisation plans, and the case for application modernisation amongst large enterprises with annual revenues over $1 billion.

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  • Liberate legacy data

    This whitepaper provides insight to the common challenges in handling legacy data and options for solving them.

    Read whitepaper
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  • Live Discussion: The 2021 Mainframe Modernisation Business Barometer Report

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  • Dwr Cymru Welsh Water I Utilities

    Tools Read case study
  • Liberating Legacy Data from IDMS and IDMSX

    Webinar Watch on demand
  • Companies House I Government

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News & Opinions

BLOG // 07-09-2021

IMS Conversion: A Technical Snapshot

by Brandon Edenfield, Managing Director of Application Modernisation

IMS Conversion: A Technical Snapshot