The availability and processing of data is an important part of day-to-day business for digitized companies. All applications, from personnel management software to online shops, are connected to databases and feed their processes from their stocks. If database queries take too long, the applications that access them also stutter. This also affects users and customers through timeout errors. Database migration to the cloud can help.
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Database migration: More efficient structuring of IT processes
The migration of databases from their own data center to the cloud offers companies the opportunity to make access more efficient, to structure IT processes more efficiently and to be more flexible in the long term. Such advantages can only be achieved if the cloud is used as efficiently as possible. To ensure this, companies should ensure that they implement the following five steps before and during the migration.
Database migration: Determine functional requirements
For the move to the cloud, as well as to any other platform, the following applies to companies: You have to check in advance to what extent there are discrepancies between the old and the new system in order to be able to address them as best as possible. For example, when switching from an SQL server to an SQL database in the cloud, some properties of the existing database may not be supported by the provider of the cloud.
The rapid development of cloud services ensures that the list of unsupported elements is becoming ever shorter. However, if companies fail to check this at an early stage, this can cause considerable difficulties in the course of business. When choosing a suitable cloud provider, the potential challenges should be clarified at an early stage.
Clean up databases and organize them efficiently
The cost advantages in the cloud are determined by the efficient use of storage space. If, for example, obsolete database archives, which have almost been forgotten in the on-premises environment, are migrated to the cloud, the savings potential can quickly vanish. When it comes to managing databases, the cloud marks a new beginning for companies: In order to be able to do this smoothly, database administrators must first clean up the database by deciding which to keep and which are no longer needed. This not only makes database migration quicker.
The storage space – and thus the costs – is kept to a minimum. The duration of the individual database queries can thus be kept as short as possible, which makes the system work extremely smoothly. In addition to efficiency, companies should also pay special attention to compliance when cleaning up their data. For some categories of data in the cloud, different regulations may apply to local storage. If data records fall within the scope of the GDPR, for example, the server location of the cloud provider plays a decisive role. In the course of this, it must also be checked to what extent the level of protection for sensitive data is sufficient or whether additional measures are required.
Document the origin and processing routes of the data
Comprehensive documentation is inevitably associated with data cleansing. Unfortunately, practical experience shows that only a few companies operate it sufficiently. However, if the migration to the cloud is pending, extensive documentation in which the origin of all data in the system is explained is essential. It is important to clarify where individual data come from and which stations they have passed since they were created.
For example, data can originate in a POS system that stores data in flat files, which are then moved to a SQL server with intermediate storage every night. The data is then cleaned up, transformed, and transferred from the staging server to the production database using a Python program. Finally, the data is moved to the production database and aggregated on a data warehouse server, where end users can run their own reports and analyzes.
In this exemplary system, the data origin has a depth of four levels or five, if one also includes all end-user reports and analyses. The background to detailed documentation is the question of whether data needs to be modified before migrating to the cloud – because not all aspects of data stored on-premises are suitable for the cloud. If there is data that needs to be kept locally, the documentation helps to keep track of which data needs to be moved and which does not.
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Database migration: operate the old and new systems in parallel
There are two main aspects to consider during the migration itself: the ETL process (extracting, transforming, loading) the data and, on the other hand, the applications, both of which must be operated in parallel between the old and the new system. For ETL, companies can have the data replicated to the new cloud system while users are still working with the existing data in the local environment.
There are two options for the applications. The simplest variant would be to switch from the old, locally installed application with a connected database to the new cloud application and the associated database in one step. However, this is impossible in the overwhelming majority of cases. Therefore, the DBA teams need to understand how their current applications are configured so that they can rewrite the programming code for the cloud. Every application layer must be replicated exactly.
Often, they need to add new code to use cloud-native features without sacrificing functionality. It is critical for database administrators (DBAs) and the departmental staff who use the application to subsequently test the two systems against each other, as some local applications may be slightly behind the updated version that was rewritten for the cloud, may lag behind or easily provide other calculated values.
Extensive testing before completing the database migration
A common problem with cloud migrations is that teams do not monitor their cloud system after it is deployed and, consequently, it is only after the monthly bill arrives that they discover that they are dramatically exceeding regular costs. As soon as the cloud system is ready for operation, the most important task is to test the new system against the old one in parallel to ensure that queries and transactions deliver identical results in both systems.
For a certain transition period, IT teams should closely monitor both systems, run a series of tests, and generate reports. Regular routine tests – such as monthly, quarterly, or annual reports – should also be carried out on a trial basis. Many reporting processes require additional CPU, IO, and storage space during processing. If it is checked in the test phase whether such processes work smoothly, IT teams can ensure that they do not experience any nasty surprises in the cloud at the end of a reporting period. Only when this point is reached can the final migration to the cloud be completed.
When migrating databases to the cloud, the main thing is to avoid an error: Assume that all local functions are of course also available in the cloud. Instead, companies must first evaluate the database management of the existing system. This creates the right conditions for a successful migration and smooth database operation from the cloud.
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