How can you use cloud-based data migration strategies to improve your data storage?

3vs of data (velocity, variety and volume) are important here. Velocity is important because it would tell you how much latency you can afford between data producers/consumers within the corporate network and cloud provider's data center. How much of your data is structured, semi-structured and unstructured? Volume is not an independent parameter, rather it is directly connected to variety and velocity. High velocity data is often high volume data but not always. A particular unstructured data set may be huge but this data is not accumulated every day. Other concerns are data retention, data security and regulatory concerns such as GDPR as well as industry specific legal requirements.

prioritize your data migration plan as per frequency of data access frequently accessed or infrequently used accordingly select storage tier in cloud, scalable object storage helps data loss , avoid duplicate data and compress data before migration, Implement policies to automatically move date to appropriate storage tiers as per age, frequency, also we can use cloud migration tools to enhance storage ,

Every cloud provider provides resilience, security & compliance features at various price points. While these issues seem obvious, one key consideration is often missing: estimate of the compute cost. If the data is in the cloud it makes sense to massage or process it in the cloud rather than on-premise or thin client. This estimation is more complicated due to the fact that we rarely profile CPU/GPU usage when data driven systems are deployed on-premise. There are no clear directions for estimating this based on data size, access patterns based on producers, consumers where these applications are located (same or different cloud providers or on-premise).

A clear and no-brainer option is to store the data in the same format it was stored on-premise. However cloud platforms offer compression and encryption features often at no or low cost. Certain unstructured data such as video file will always go into blob/object storage while design choice for storing structured data can be revisited when migrating the data storage to the cloud. From a security and compliance standpoint, identity/access management as well as network rules are highly important to configure and review.

It is often difficult to classify a migration project as lift-and-shift or refactor or rearchitect or rebuild. Sometimes it is a mix of multiple approaches. Lift-and-shift projects sometimes start with an assumption of cost savings but that kind of savings is only possible when certain features of the new cloud platform are leveraged (a good example is leveraging time travel to get rid of daily inventory snapshots in snowflake). In such cases, rearchitecture is necessary but carries all the risks associated with such an effort. In certain scenarios where a lot of old data is involved but they can be archived, rebuild may save time and money.

An important distinction here is whether only data is being migrated or producers/consumers are being migrated as well? If not, latency is a big consideration, when applications are trying to access the same data simultaneously. If a subset of producers/consumers are migrated as well, the migration process and new applications need to be tested separately and they need to be budgeted for that. Most often an additional dev environment becomes necessary to enable teams performing migration of these applications in tandem

The first phase of the project should determine the metrics based on stated business objectives. As long as metrics are accepted by stakeholders and communicated to the end users of the organization, the migration team's job is to deliver on the metrics. These metrics should create test suites that form the basics of the QA process after the migration development is complete. Certain metrics around security/compliance/performance can only be partially understood initially and if there is a risk associated with this approach, it needs to be identified and documented.