Best Practices in Cloud Data Migration

by Dynamix Group Writer

Enterprises are increasingly migrating to the cloud to benefit from the productivity and data access capabilities of modern data architectures. With close to 60% of Indian firms planning on leveraging the cloud for greater agility, there is significant momentum across industries to scale up cloud adoption.

To truly benefit from comprehensive digital transformation, businesses need to outline a robust data migration strategy. The strategy needs to incorporate best practices in cloud data migration while ensuring cost-effectiveness, accessibility, and cyber security at scale. Leveraging best practices also ensure that the cloud data migration initiative is ROI-focused and does not lead to overruns or costly re-migration processes. Here’s how it is done:

Incorporating robust data governance protocols

While spending on public cloud services is set to grow to 29.4% in 2021 in India, businesses need to have robust data governance policies to manage the rapid generation of real-time data. Data governance policies ensure effective input-control and data source mapping to prevent the formation of a data swamp.

Data governance policies also establish critical controls to analyze meta-data, perform data analytics initiatives, and update key databases. Firms can also establish different rules for handling different data types to align the modern cloud architecture better to business needs. Modern database management is strengthened significantly with the tools that data governance protocols provide.

Leveraging automation to expedite data transformation

Automation is a critical tool to enhance the accuracy and speed of cloud migration. Through automated protocols, firms can correctly assess the right data migration candidates while prioritizing databases for effective migration. Automated tools also transform the data to cloud equivalents and optimize schema to ensure compatibility to the new data platform without manual inputs.

An essential benefit that automated transformation tools provide is validating the translated data sets to ensure quality control. Reconciliation scripts are automatically generated with granular-level analysis of the transformed data. Firms can also perform semantic and syntactical validation of the converted logic to ensure minimal errors.

Ensuring effective cyber security measures

Cyber security is a key area of focus throughout the lifespan of cloud data management. Complex deployments that are not protected from common threats can be prone to zero-day attacks, phishing/spoofing, ransomware, crypto-jacking, etc. Misconfigurations and unencrypted data sets can lead to significant issues with cyber security, especially as cloud adoption scales up to enterprise-wide.

Firms need to focus on cyber security from a policy and technology perspective. While most cloud platforms have built-in security tools, businesses need to incorporate regular pen-testing, phishing tests, and audits to ensure that they are ahead of industry trends.