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As we discovered in a previous blog article, data migrations have a lot in common with blood transfusions. Whilst it seems straightforward to carry out either a blood transfusion or a data migration, the actuality proves far more complex.
As organizations strive to adapt and thrive in a rapidly evolving digital landscape, there is an increasing need to transform business systems. This is where, just like how a blood transfusion gives new life to a person, data migration plays a vital role in giving life to a new way of doing business.
But, just like a blood transfusion can go wrong, so can data migrations. In the worst-case scenario, the effect of a bad data migration could be as deadly as a botched blood transfusion. To minimize the risk, blood transfusions are highly standardized procedures, just like data migrations should be.
In this blog article, we will explore the often missing essentiality of data migration: standardization.
To ensure the safety, efficiency, and reliability of blood transfusions, a highly standardized process is followed. This process includes very strict guidelines and regulations governing the collection, processing, storage, and distribution of blood and blood products. It also includes procedures for the collection and testing of blood, compatibility screening, transfusion protocols, documentation, and traceability and leaves room for continuous quality improvement.
In essence, standardization acts as the guiding principle that brings order and reliability to the complex process of blood transfusions.
Standardization in data migration follows a similar approach. Ideally, a framework is established which encompasses best practices, uniform guidelines, templates, and procedures. It includes topics ranging from planning to post-migration operations. The framework is to be based on years of experience whilst, just like with the blood transfusion, leaving room for continuous improvement.
The Camelot Data Migration Framework is a highly standardized approach to data migration.
The framework is suitable whether the project aims for SAP Greenfield, Brownfield, or Hybrid upgrades, and whether it concerns an S/4HANA transformation on-premise or on the cloud. The primary objective of the Camelot Data Migration approach is to enhance transparency and minimize risks by following a well-defined cycle.
We will highlight 3 important aspects of the Camelot Data Migration Framework:
The guidelines are applied throughout the migration process, from the very beginning to the steady state after the systems are live. They include best practices, proven templates, and procedures, all based on years of experience. The templates are not just limited to the migration concept and functional/technical documentation but also include items such as test scripts, test issue register and reports, detailed migration planning, cut-over plans, run sheets, pre-load validation reports, post load comparison reports, naming convention document, development rules, scoping document and the unified data model itself.
The unified data model, along with the migration engine, serves as the core infrastructure of the migration process. Acting as the brain, the data model defines the logic behind the migration, serving as the definitive source of truth on which the entire process relies.
At Camelot, we advocate for the use of a unified data model over migration-specific source-to-target mapping documents (referred to as the generic data model). This preference stems from the unified data model’s ability to provide a single, comprehensive framework for all project teams involved, rather than each team relying on their own isolated documents. This approach facilitates an overarching view of the entire system and illuminates the ripple effects of decisions across the entire process, rather than solely within individual teams.
The importance of the unified data model becomes strikingly evident when considering the potential for significant inconsistencies, underscoring its indispensable role in ensuring data consistency and accuracy throughout the migration process.
Similar to how the human heart circulates blood throughout the body, the Migration Engine facilitates the movement of data from the source to the target system during the migration process.
To achieve a successful migration to the target system, it is imperative to execute transitional processes such as scoping, harmonization, number assignment, data transformation, pre-load validations, and comprehensive reporting on both data quantity and quality prior to the data load. These preparatory steps not only improve the accuracy of migration reports but also act as a protective measure against potential development errors that could conflict with the integrity of the data model itself.
The Camelot Migration Engine encompasses all necessary processes to ensure a high-quality data migration. This engine is applicable to all SAP objects involved in the transformation journey. Even in cases where objects are relatively straightforward and simple, they still engage with the majority of processes within the migration engine.
Standardizing the migration path paves the way for the next significant leap in Data Migration: Automation. By integrating automation into data migration tools and processes, we not only enforce standardization but also significantly accelerate the process whilst reducing human errors.
Overall, standardization and automation form a crucial alliance. Standardization ensures consistency and accuracy, while automation minimizes errors and maintains project efficiency. This powerful duo paves the way for flawless data migration, a must in today’s digital era. Embrace them to deliver excellence in your data journey.
Data migration is one of the key competencies of the Camelot Data Tower.
Camelot’s Data Tower Concept unifies key competencies in Data Governance, Data Migration, Data Quality Management, Data Design, and Data Advisory to offer a comprehensive data management solution. Scalable for businesses of all sizes, this platform provides efficient and secure solutions. It identifies areas for improvement and potential risks, enhances data governance models, improves data quality and maturity, and prepares organizations for a seamless transformation to S/4HANA. With Camelot’s expertise, businesses can confidently navigate their data transformation journey, achieving their strategic goals more effectively.
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