Migrating your reporting platform to the Azure cloud

Before migrating to Azure cloud, defining your reporting platform requirements is essential. These requirements should cover your reporting platform's features, functionality and performance characteristics. You should also consider the data sources you will use and how you will integrate them into your reporting platform. For example, you should determine if you will incorporate historical data from your system. If your new reporting platform is being designed in the middle of a large ERP migration to the cloud, there are a few things to keep in mind.

The first step is to evaluate your on-premises architecture and code. Reviewing the existing code and identifying any potential issues or performance bottlenecks that may arise during the migration process is vital. It is also essential to consider the code’s long-term maintenance and scalability. In many cases, it may be more effective to reuse the good parts of the code while rebuilding the features that have been poorly designed. However, this approach should be balanced against the need to minimize the risk of migration and the cost of rebuilding, which can be significant. Long story short, our advice would be to reinvent the wheel only if absolutely necessary, but definitely not to recycle legacy code that has been proven to be a pain and source of issues in the past.

Migrating historical data to a Data Lake on Azure can be a complex process. It is essential to plan the migration carefully to ensure that the data is accurate and accessible. Once you have identified the historical data that needs to be migrated, you must prepare the data for migration by cleansing and transforming it. Next, you can upload the data to the Data Lake using an appropriate method, such as Azure Data Factory or Azure Storage Explorer. Finally, it is necessary to validate the migrated data to ensure that it is accurate and accessible. If you aim to bring that data into your daily analysis, that’s also a good opportunity to challenge the business needs: do they really need everything? Indeed, even if a structure such as a Data Lake or a Synapse Dedicated Pool can support thousands of terabytes of data, you still need to wrap it up in your visualization tool, which could lead to performance issues – that’s also an opportunity to do some cleaning and keep only the relevant data. 

Security, compliance and access to data are crucial considerations in any data migration. When moving to the cloud, ensuring that your data is secure and meets compliance requirements is essential, which can be slightly different from what you do on-premises. An example of critical elements to focus on when migrating to the cloud include data encryption, access controls, identity and access management (IAM) and network security.

Picking the right Azure resource and configuration is important to avoid an overkill infrastructure and unnecessary expensive products. Understanding how you want to evolve your data platform will guide you on this path. Moving to the cloud can result in significant cost savings for businesses, as they no longer need to maintain their infrastructure and can scale their computing resources up or down more flexibly based on demand.

In conclusion, migrating to the Azure cloud requires careful planning and consideration of several key factors. Defining the mission, evaluating your code, migrating historical data, and ensuring security and compliance are crucial for a smooth and successful migration. By taking these steps and using the right services and configurations, businesses can reap the benefits of the cloud, such as cost savings and scalability.