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Today's enterprises have access to more data than ever before. These figures are growing at an alarming rate, both in terms of quantity and change.

Today's enterprises have access to more data than ever before. These figures are growing at an alarming rate, both in terms of quantity and change. Whether it's traditional analytics or cutting-edge technologies such as machine learning and artificial intelligence, centralizing this information from all sources to the cloud repository is critical to the business.

Why migrate? Companies move data to the cloud just as people move to their new homes. Enterprises need to know why they want to migrate, what they need to migrate, and where they plan to migrate. What do companies want from the cloud? Has the current setting exceeded the upper limit? How to better power the enterprise's data analysis or machine learning stack? How do enterprises take advantage of all the features provided by the cloud? Can you take advantage of its architecture? What is its scalability and resilience? What is its security? Are there any cost savings? What will it bring? Is it everything?

If a detailed survey is conducted, people may be surprised by the data from so many sources.

Of course, such a complex move is not on a whim. Instead, it requires an important plan and the right toolset to succeed. Before an enterprise builds a migration list, consider some common considerations:

1. Security.

In a world where data privacy is becoming a good data management practice, it is important to know which data is shareable and which is not. It is critical that individual users ensure that their PII (personally identifiable information) data is not exposed to the wrong parties. Therefore, it is important to comprehensively examine the entire pipeline and database functions to ensure the security of moving and stationary data. Knowing how the data is phased, which systems can access it, and how long to retain it is essential to fully understand the level of exposure of the information.

In addition, like traditional local solutions, you should consider how the application protects objects and data. For example, whether there is role-based access control (RBAC) and whether data can be protected at the appropriate granularity (row or column level) is important. Is unidentifying and blocking data a prerequisite for entering the cloud platform? And is authorized user management a key factor in enterprise operation?

Finally, it is important to know which data objects in the asset list require special processing in order to achieve regulatory or contractual purposes. At the beginning of the migration and planning process, it is critical to ensure that the platform and applications can support these needs of the enterprise.

two。 Performance

When migrating to a cloud platform, it is critical to make data available and as up-to-date as possible. Data analysis can provide business advantages and rely on data. Typically, local solutions are carefully crafted and specially designed to meet the user experience requirements and service level agreements (SLA) of the business. When migrating to a cloud platform, it is critical to fully review and test the performance of pipelines and databases under specific production workloads, regardless of the approach used by the enterprise. This is the only way to understand what performance bottlenecks occur, where they occur, and how to resolve them.

Establishing specific benchmarks and candidate workloads for continuous testing and monitoring is undoubtedly a best practice. This can be done using cloud monitoring services and queries that constantly poll and verify that the platform is running optimally.

3. Capacity

Managing current and future capacity is a science in the field of local solutions. It is closely related to maintaining a consistent level of performance experienced by platform consumers. One of the main ways to migrate to a cloud platform is to realize the benefits of resiliency and automatic scaling as workload and capacity requirements change.

When considering the future cloud computing architecture, it is critical that the engineering design required to respond to peak demand scenarios must be pre-built into the capabilities of the platform. Businesses need to understand their peak needs and ensure that cloud platforms can handle them. It is also critical to ensure that these peak demand scenarios can be continuously tested and monitored.

Take advantage of the cloud platform's native monitoring and reporting services. Let the enterprise DevOps team understand these technologies and build this capability in advance, rather than thinking about it after the migration.

4. Assets and inventory census

Before implementing the cloud migration strategy, the enterprise must capture a complete list of all data assets, their dependencies, and the content that upstream and downstream applications support these assets. Creating and maintaining this list is the basis for all planned activities during the migration phase. Without this list, you cannot fully understand the impact, risk, and cost of migrating each component in the stack to the cloud.

In addition, through this inventory and evaluation exercise, enterprises often find opportunities to restructure and phase out redundant data sources and services. This can help companies avoid wasting resources on projects with limited or no future value. Enterprises can also discover new data sources to migrate.

5. Application migration

This migration guide focuses on data migration to the cloud, but enterprises may also need to migrate applications. You can choose several different ways to migrate their applications. The enterprise's own specific needs and goals will determine which approach is best for them.

Whether the enterprise wants to migrate most applications to the cloud, but avoid making changes to them. This is usually a variation of the "promote and transfer" approach, where existing applications are run in virtual machines hosted in the cloud, rather than customized or replaced. It is faster and less destructive, but it does not take full advantage of all the features provided by cloud computing.

Another approach may be to completely migrate enterprise applications to the cloud native environment. This is more expensive in terms of cost and time, because enterprise applications may need to be customized or even replaced, but eventually the enterprise will have a more powerful system.

In short, enterprises need to understand their assets and their value. Understand its security requirements and assess the risk according to the target architecture of the plan. Ensure that enterprises can provide customers with the same or better service levels, and finally, leverage local cloud architecture services for monitoring and capacity management, building migration strategies as the necessary tools to take business to a new level.

6. Cloud Migration list

Moving to the cloud usually requires tracking a lot of details, which usually helps to list things that enterprises need to remember. For example, do you need to rent a truck? Have you changed your mailing address? When an enterprise moves its business to the cloud, it needs a list:

(1) establish team roles and define success factors. What is the impact of a successful migration on the enterprise? Who will help achieve this goal? (2) understand what the enterprise is migrating, its dependencies, and its impact on application users. Here, enterprises will implement data censuses and can use migration to perform some data cleaning and reduce the residual data to be migrated. At this point, enterprises will begin to understand the capacity they need now and what they may need in the future. (3) perform safety assessment. Ensure that data is protected and complies with compliance or regulatory standards. (4) establish performance benchmarks and standards before adopting the switch. (5) the enterprise determines in advance how its DevOps team will support its applications in the cloud, as well as the cloud native tools that will be used. Update the service level agreement (SLA) to reflect the new environment and configuration. (7) ensure that enterprise applications automatically extend and test these capabilities with local cloud capabilities prior to migration.

Of course, this is basically a jump point, a place for companies to start operating. The actual implementation of enterprises may be more complex or even simpler. Now that the enterprise knows the basics, consider adding some additional steps to the process.

The choice of the road of migration

Although migrating data is a major problem, enterprises should use migration to perform any data transformations that may be needed.

Because the enterprise's data comes from different sources and involves different schemas, migration is an ideal time to remap the data to a common schema. Companies may also want to enrich or clean up data for further analysis.

Most data pipelines provide some kind of conversion support, either before or after loading into the cloud.

Alooma fully supports transforming data during or after loading. In this way, enterprises can enrich or clean up the data before loading, and then use the computing power provided by cloud computing to perform various connections or other transformations in the cloud computing data warehouse.

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