- Cloud data migration involves moving data storage and applications into the cloud, which can include consolidating and transferring data from on-premises data warehouses to cloud-based solutions.
- A successful cloud data migration requires careful planning, including defining future business goals, cataloging data, standardising and cleansing data, and managing metadata to ensure smooth data integration and governance.
Cloud data migration involves not only moving data and applications to the cloud, but also standardising, cleaning, and managing data to ensure data quality and governance. Cloud data migration involves defining future goals, data cataloging, data standardisation and cleaning, and metadata management to support automating the data migration process and simplifying data discovery and management.
What is cloud data migration
Cloud data migration refers to the process of transferring data storage and applications from traditional on-premises systems to cloud-based environments. This can include the consolidation and relocation of data from older, in-house data warehouses to cloud-based data warehouses, the establishment of new cloud data warehouses or data lakes, or the implementation of a hybrid cloud data management strategy that integrates both cloud and on-premises solutions.
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Checklist for cloud data migration
When undertaking a cloud data migration, it is vital to ensure that the data is managed and utilised efficiently. To achieve this, organisations need to follow a number of key steps to ensure that the data migration process is both smooth and efficient. Below you will find four core strategies that will guide organisations in successfully migrating data to the cloud while ensuring data quality, security and availability.
1. Establish a future target state: When selecting a cloud data management solution, you should first define your business objectives and then select a solution that meets your current needs while being future-proof. This solution should be scalable to support business growth without replacing existing work, while providing multi-cloud support to work with the cloud service provider of your choice.
2. Data cataloguing: An intelligent data catalogue provides detailed information about data, including its location, usage and protection needs. It simplifies finding and accessing data, helps quickly identify high-value data, prioritises migration to new cloud data warehouses, and enables data consumers to start using new technologies immediately, while development teams seamlessly replenish data.
3. Data standardisation and cleansing: Prior to cloud data migration, data quality and governance should be emphasised to reduce preparation for subsequent cloud analytics. Look for a complete set of pre-built data quality rules to cleanse, standardise and enrich data without coding, ensuring that data users can trust the data they receive.
4. Metadata management: Metadata management is critical to automate data migration to a cloud data warehouse or data lake, simplifying data discovery, tagging, correlation and configuration. An effective cloud data management solution should collect metadata from all enterprise systems, including technical, business, operational, infrastructure and usage metadata. In addition, the solution should collate metadata, add business context, and be able to infer data pedigree and inter-entity relationships.
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Benefits of cloud data migration
Cloud data migration offers numerous benefits, including cost savings through reduced capital expenditures and optimised resource usage, enhanced scalability to accommodate fluctuating workloads, and improved security with advanced cloud provider protections. It also provides better performance and accessibility, ensuring a superior user experience and global reach. Additionally, cloud migration supports business continuity and robust disaster recovery, fosters innovation and competitive advantage through faster feature deployment, and offers powerful data management and analytics tools for informed decision-making.
