When looking at the setup of a Data Tower, it can be broken down into multiple different teams. Each team has their individual roles and responsibilities within the construct.

Data Governance (Example: Data Governance Team – monitoring data integrity)

At the core of the Data Tower stands the Data Governance team. This team acts as the guardian of data integrity, setting policies, standards, and procedures to ensure that data is accurate, consistent, and aligned with organizational objectives. Also, Data Governance becomes the guiding force that navigates the complex terrain of data management and establishes the data governance framework.

Data Migration (Example: Data Migration Team – specialists for seamless transitions)

Now, to orchestrate a seamless transition the Data Tower is equipped with Data Migration experts. This dedicated team oversees end-to-end operational migration activities, encompassing tasks such as data extraction, transformation, loading, and validation. Their role is fundamental in ensuring a smooth transition to S/4, minimizing downtime, and mitigating risks associated with data loss.

Data Quality Management (Example: Data Quality Team – improved basis for decision-making)

Additionally, to elevate the standards, the team of Data Quality Management plays a relevant role in the foundation of informed decision-making. This team focuses on profiling, cleansing, and enriching data to ensure it meets the highest standards possible. Their efforts guarantee that the S/4 system operates with accurate and reliable information, enhancing the overall efficiency of the organization.

Data Design (Example: Data Experts – creating consistency)

Within this framework, the Data Design team, consisting of Data Experts and Data Clusters, is responsible for shaping and overseeing essential master data objects, such as customer, supplier, material, etc. Through the establishment and upkeep of a single source of truth, MDM guarantees uniformity throughout the organization, mitigating the risks of duplicates and inconsistencies that may arise during the S/4 transformation process.

Data Operations (Example: Data Stewards – representing the business focus at the operational layer)

Lastly, the Data Operations maintain data integrity and excellence, by serving as first and second levels of support. They are responsible for harmonizing requirements, driving issue resolution within their respective areas, and ensuring standardization and quality for the specific data elements.