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No cloud migration without data governance and data management


The cloud enables companies to make their processes more agile and efficient. This applies to individual applications as well as to the migration of the entire IT infrastructure. However, it is important to take the right steps in a cloud migration to fully unleash the potential of cloud services. Clean data governance and clearly organized data management are essential for a successful migration process.


Potentials of the cloud  

Compared to on-premise infrastructures, cloud technologies promise various opportunities to optimize processes - this is already clear to many companies. High scalability and rapid adaptability to changing requirements are major advantages here. IT managers can flexibly design the IT infrastructure using cloud tools and services. Subscription models can be more cost-effective than purchasing hardware and software yourself. Cloud servers or serverless functions ensure fast provisioning and high availability of capacities. Cloud providers provide reliable redundant infrastructures and failover systems for this purpose. They also have special security measures and compliance programs to ensure the security of applications and data. Another increasingly important benefit is the more efficient use of energy. Cloud usage yields energy consumption savings of about 80 percent, according to a study by AWS. According to a Microsoft study, the CO2 savings potential is over 90 percent compared to on-premise architectures.


Set data standards for interoperability

But beware: Cloud architectures can be complex. The requirements for integrating applications and processes are correspondingly high. Therefore, the basic prerequisite must be created in the form of a newly established data architecture with consolidated data in an appropriate data quality. This applies to every migration, whether to the cloud or, for example, due to system updates. True to the motto "Crap In - Crap Out", the same applies to the cloud: If outdated, redundant or faulty data forms the basis, the migration will not be able to exploit its potential and will only optimize customer-related processes to a very limited extent. 
The data standards now defined are also needed for data portability from cloud to cloud, or for interoperability between cloud and on-premise environment. Without this prerequisite, the cloud is in the worst case no more than another data silo, which contributes neither to process optimization nor to data economy. 
No migration should start without preparing the data basis with careful consolidation from heterogeneous systems and data sources and a new data architecture. So how should companies proceed to make their data cloud-ready and avoid the risks mentioned?

Data governance and data management 

Even without a migration project, the following applies: Data management is the be-all and end-all, because it regulates the technical and operational aspects of data management: How do we record our data correctly? How do we store it? How do we process and use it? How do we maintain high data quality? A variety of tools help those responsible for data, because these tasks can hardly be handled consistently by hand. Data governance provides guidelines and regulations for this and ensures that data is used in accordance with corporate goals and requirements. It also defines responsibilities. Data governance is an important building block for compliance
It pays to pay constant attention to data and its quality. But before, during and after migration, focus is essential to ensure that processes and applications can run smoothly and efficiently.


Data consolidation 

In the first step, companies must create the technical prerequisites for the migration. To do this, the data from all sources and systems must be brought together at a central point, ideally through direct integration with the Uniserv Customer Data Hub. This provides the necessary functionalities to cleanse and validate the data, identify duplicates and enrich data records - before the migration and beyond. 
In the Customer Data Hub, the defined new standard data model takes the optimized information from all source data models, prepares the data, and translates it into the new standard data model. In the second step, identification of duplicate data sets takes place across all sources. In addition, the data records are intelligently merged into golden records. By now, at the latest, it is clear that simply "copy-pasting" the data into a new system cannot accomplish this preparation. 
Companies must view data consolidation as an important and independent project that must be allocated sufficient capacity. This is the only way to achieve a database that is as compact, correct and of the highest quality as possible.
The migration is a fitting occasion to establish a future-proof data model. This would be much more time-consuming and expensive in retrospect. At the same time, the migration offers a welcome opportunity to discuss future data requirements from different previous perspectives, to anchor a new, common data model and to further optimize it iteratively during the migration. This step has a significant influence on the success and acceptance of the new business applications in the specialist departments. 


Appoint data owners and data stewards 

For the migration project itself, not only technical but also organizational prerequisites must be created. After all, every migration to new business applications is a change project. Companies must not only plan sufficient resources such as time, knowledge and manpower, but also define responsibilities.
At this point, at the latest, data owners and data stewards come into play. Since they define how the data should function in the future and provide operational support for the migration project during data consolidation, they play a key role in shaping the change. As they build up a great deal of data knowledge, it pays to retain these roles even after the migration. They are the multipliers for internal acceptance of the migration in the business units as well as the enablers of the long-term performance increase of the company processes through the optimized data. At best, they are already familiar with the company's data governance prior to the migration project and continue to develop it during the migration. 


Cloud migration as a change project 

The new and individual cloud architecture is created on the basis of the business objectives, the expectations for cloud optimization and the degree of cloud utilization. It is successful in terms of data and its migration when the data has been qualitatively consolidated and transferred to the new data architecture. Migration is an appropriate time to define rights and roles in relation to the data and to implement these both technically and organize them via governance functions. Together, data and cloud governance ensure compliance with the new cloud landscape. In parallel, cloud security must be designed in such a way that the new data world in the cloud is protected.

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