SAP S/4HANA to Snowflake Migration is a complex and critical undertaking. This process involves meticulous planning, strategic execution, and substantial investment to ensure seamless data transition and integration. While migration offers significant benefits, it also comes with its own set of challenges.
One widely adopted strategy is the “lift and shift” method, a broad category that encompasses various approaches to migrating applications and data to the cloud with minimal changes. Within the lift and shift framework, there are multiple implementations tailored to different business needs and technical requirements. In this article, let's take a look into SAP’s migration approaches using their proprietary tools and systems, examining their benefits and limitations.
SAP Migration Tools
BW Extractors
BW Extractors are specialized tools within SAP BW/4HANA designed to extract data exclusively from native SAP systems, such as SAP S/4 HANA and SAP ECC, for migration and reporting purposes. They enable seamless data integration within the SAP ecosystem, ensuring that data flows smoothly from your ERP environment to the modern platform of choice such as Snowflake. Additionally, BW Extractors support advanced transformation processes, allowing for the customization of data formats to meet specific business requirements.
Initially developed for SAP’s BW/BI data warehouse systems, BW Extractors are optimized to process complex data structures. Using Remote Function Calls (RFC), they extract data in packages, with built-in SAP logic and delta queues streamlining operations. Customizing these extractors to meet advanced business needs requires the involvement of SAP experts, who can embed specialized logic and optimize performance for specific requirements.
Strengths:
Efficient Data Transfer: Handles large volumes of structured data seamlessly.
Data Integrity: Ensures consistency during migration.
Complex Transformations: Manages intricate data mappings effectively.
CDS Views
CDS (Core Data Services) Views within SAP HANA enable the creation of semantically rich, reusable data models, simplifying access to complex databases and enhancing flexibility. As the newest approach in the SAP S/4HANA suite, CDS Views help develop virtual data models, facilitate the creation of BW Extractors, and publish OData services for seamless integration. These views allow business users and developers to interact with data intuitively, promoting easier maintenance and scalability.
Strengths:
Optimized Performance: Enhanced query execution and reduced redundancy.
Flexibility: Allows for complex data representations.
Consistency and Reusability: Streamlines development across applications.
SAP HANA Embedded Analytics
SAP HANA Embedded Analytics integrates advanced analytical capabilities directly into the SAP HANA database, enabling real-time insights and enhanced data processing. This integration allows businesses to perform complex analyses without separate analytical tools, accelerating decision-making and boosting operational efficiency.
Built on SAP CDS Views, SAP S/4HANA Embedded Analytics empowers users to analyze transactional data in real time, without needing deep knowledge of the underlying data structures. These views can be used as-is or combined with others to create new models, which external BI tools and visualization platforms can further consume to meet specific business analytics needs.
Strengths:
High-Speed Processing: Facilitates interactive reporting without external tools.
Advanced Features: Includes predictive analytics and machine learning integration.
Reduced Latency: Improves decision-making with real-time data.
Common drawbacks of SAP Migration Solutions
While SAP’s migration solutions offer robust tools for data management and analytics, organizations frequently encounter significant challenges. SAP’s standard extractors are limited to native SAP systems, making it difficult to meet specialized data requirements without custom extraction solutions.
The migration process involves complex data modeling tasks where data engineers must manually reconstruct business logic and often overlook essential metadata from the source ERP system, necessitating separate analysis and development cycles.
Existing automation tools primarily address technological aspects like data pipelines and orchestration but lack support for business modeling automations, necessitating increased manual interventions and prolonging project timelines.
High implementation costs, complexity, and steep learning curves are prevalent across all solutions, often requiring substantial investments in time and resources. Additionally, scalability issues and integration complexities with legacy systems can hinder seamless migrations.
This may lead you think:
How can we shorten the time it takes to produce SAP analytical solutions within Snowflake while minimizing our reliance on SAP Subject Matter Experts?
To minimize the learning curve for data and analytical engineers, how can we best utilize their time and skills?
When creating effective data models outside of the source systems, how can we make sure that the integrity of the business logic is preserved?
Lastly, how can we use the metadata to create knowledge repositories that are useful for both business and IT?
Are there better alternatives that are economical and efficient?
While SAP’s migration solutions provide powerful tools for data management and analytics, they come with significant limitations such as high costs, complexity, and scalability challenges that can impede successful migrations.
What if there is a more efficient and cost-effective way to handle your SAP S/4HANA to Snowflake migration needs?
indigoChart offers a framework that addresses these issues head-on. Stay tuned for our next blog to discover why this framework may be a better option for your SAP S/4 Hana to Snowflake migration plan.
Visit us at www.indigoChart.com or drop us a line at hello@indigochart.com
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