is the process of transferring data from one system to another, and it's a critical aspect of many business operations. We'll explore what is, its benefits, and some common .
Here are the key takeaways from the article:
- involves moving data from one system to another while maintaining and accuracy.
- There are several benefits to , including increased efficiency, improved data security, and enhanced .
- Some common for include system upgrades, , and merging data from multiple systems.
- A successful requires careful planning, a thorough understanding of the source and , and effective testing and validation processes.
- Choosing the right and working with experienced professionals can help ensure a smooth and successful .
In the article, we'll delve deeper into each of these points and provide more information on the benefits andof , as well as some best practices for ensuring a successful migration.
Table of Contents
- When is Needed?
- Tips to Consider Before
- Stages of a
- Building Migration Solution
- Mitigating the Risk Factors in
- Difference between , , and Data Conversion
, as the name suggests, refers to a multi-step process of transferring data from one application, file , or to another. With enterprise organizations producing ever-increasing , it has become imperative to select environments that can optimally store this data to amplify the value extracted from it.
Generally, survey results from different sectors, only an estimated 16% of the are successfully delivered within the stipulated time and budget because of the complexity and constraints involved in the process.involves decommissioning by mapping data to . Today, a common of this is migrating data systems and infrastructure to environments as more and more companies are investing huge sums to cut storage costs and boost productivity. As per
In this article, we will deep-dive into different, the stages of a , as well as the risks associated with the and how they can be mitigated.
While overhaulingand replacing them altogether is often the most common cause, businesses undertake for a variety of other reasons as well:
- Upgrading systems or database as databases expand in size and demand greater storage capacity
- Opting to shift to environments from physical, systems
- Consolidating different data sources after corporate or acquisitions
- Upgrades in existing hardware, applications, and file
- Archiving and removing data that is not useful anymore
- Establishing new or for analytics and reporting purposes
- Curtailing operational costs by reducing the number of data hosting systems
There are six majorand an individual can include multiple types from the following:
Migration refers to moving the infrastructure to a new physical or location. A houses network routers, storage devices, server systems, and other critical infrastructural equipment of an organization.
is when data related to certain applications has to be transferred to a new computing environment. This could involve shifting entire applications from a local server to a or between two different or moving just the underlying data in case of a software upgrade at the ’s end. This type of migration is especially complex because applications interact with other programs. Problems typically arise because and have unique data and models. Enterprise software vendors usually provide special to the companies to maintain during the .
According to Gartner, more than 45% of IT spending on infrastructure management, outsourcing, and application software will move from traditional to solutions by 2024.is related to the relocation of data, business , and services from one to another or from an on-site to a one. This is one of the most popular and it allows enterprises to scale more effectively, access resources more readily, and trim overheads related to the physical management of infrastructure.
becomes necessary when organizations have to shift to a different database vendor, upgrade the software, or migrate the database to a ’s environment. Typically, it could mean either updating to a new version of the same system or shifting to a new system offered by a different service such as migrating from Oracle to PostgreSQL.
Migration refers to the movement of business data, processes, and applications to a new environment. This could include the transfer of databases and programs relating to business operations, products, and customer experiences. The driving factors of this type of migration are business reorganization, acquisitions, and to realign goals or target new markets.
is the process of migrating data from one storage medium to another. A common of this migration is when companies need to do away with traditional storage equipment like hard-disk drives and move the data to more durable and faster storage devices such as solid-state drives. does not change the underlying data and it enables companies to not only achieve significantly faster performance but also ensure more effective data backup and .
Tips to Consider Before
, if executed correctly, can prove to be extremely beneficial for companies. Listed below are some points that companies can keep in consideration before migration. These can help in ensuring a smooth and painless but also in augmenting its positive impact on the business:
- Conducting pre-migration assessment of the existing system. This will help in better understanding the structure of the underlying system as well as in setting business goals for the migration.
- Analyzing performance statistics of the old infrastructural resources such as , databases, and application programs. This will give an idea of user requirements and will also help in setting performance benchmarks for post-migration .
- Review specifications of the physical and virtual assets of the company such as storage configurations, number of CPUs etcetera. This will assist in drafting a budget and preventing avoidable costs.
- Another way of preventing unwanted expenses is by segmenting servers according to their business requirement and by using the correct servers for the on which the migration is happening.
- is a continuous process and future migrations are unavoidable. Therefore, it is important for the higher-ups in an organization to utilize resources appropriately and apply best practices to ensure effective .
There are two major approaches to. While planning and implementation depend on the type of migration chosen, it is also imperative to choose the right as per the requirements of the business. The two approaches are detailed below:
Migration is when all data assets and associated services and programs are migrated from the to the in one operation within a set window. Its implementation strategy requires all systems to be unavailable for usage throughout the . Therefore, companies usually execute migrations during public vacations when system usage is not needed.
The advantages of this migration approach are that it isand also less as all transformations happen in a single operation. Companies do not have to contend with running old and at the same time. However, the downside of this approach is that there is a high risk of migration failure due to disrupting transmission processes. This could also result in in situations where proper backups are not assured. Therefore, migrations are generally utilized by small-sized companies or in those cases where the data to be transmitted is not overwhelming in size.
Trickle Migration, on the other hand, is a phased migration approach. Also known as iterative migration, it partitions theinto smaller migrations. The transfer of data from the to the happens in a phase-wise manner and each of these sub-processes has its own execution timelines.
In this way, nois required during the because the can remain in operation alongside the while the is on-going. This migration approach is also less prone to failures because if any sub-process confronts an unexpected error, only that sub-process needs to be re-run rather than redoing the whole migration again. However, trickle migrations tend to be much more complicated because of their iterative nature. They are also more expensive in terms of time and resource consumption because they require both old and to function simultaneously. This migration approach is usually used by large-scale enterprises that cannot afford across the entire system during migration.
Stages of a
If you are planning to migrate yourto a , upgrade your system, perform server maintenance, or simply relocate data to a new device, developing a can simplify the process. Following a thorough, step-by-step plan that clearly outlines the different steps is important, especially when dealing with . While a can be customized as per the and objectives, generally, it consists of the following stages:
Before the actual migration happens, it is vital to assess the source repository and understand the location andof the data. In this discovery phase, the underlying dependencies and constraints in the data are identified. The is evaluated by running audits and potential risks and security concerns that could arise during are noted down.
Once the underlying data has been thoroughly assessed, the scope of the migration project has to be defined. In this phase, a requirements specification is finalized for the resources required to carry out the migration. Organizations also decide on theto be used, i.e., or trickle, and draft a budget and a schedule accordingly.
All of the data should be backed up in a secure location before thegets underway. In situations where data is corrupted, lost, or transferred incompletely during migration, the backup would allow the restoration of data to its original state. can be used to adequately backup data.
Building Migration Solution
This is the phase where the actual implementation happens. The data is extracted from the, converted into an appropriate , and then transferred onto the using the mapping protocols already defined. During this step, initial tests on sample data are also conducted to set performance benchmarks for the actual .
Testing & Production Migrations
Subsequent testing migrations are then performed with real-world data to ensure foolproof performance. The transfer process is fully refined until all exceptions are accounted for. Once the accuracy of the migrated data is ensured, approvals from the relevantare collated and the production migration is executed.
Cleanup and Monitoring/Maintenance
As thegoes live, strategies are put into place to decommission the and set up auditing protocols to maintain the . Different practices and performance monitoring tools are employed in this final stage.
Mitigating the Risk Factors in
- Interference Risk: This problem is encountered when multiple users access an application program at the same time during the . It could lead to a lack of access for other if someone closes the program while the data transmission is happening.
- Solution: This could be avoided by discussing it beforehand in pre-migration planning. The organization could also plan a pilot run in a testing environment involving all
- : During the , some of the data may not transfer from the to the due to a variety of reasons such as incompatible system , incomplete etcetera. It can be extremely costly to recover data and can, in some cases, lead to permanent loss of data.
- Solution: Using data reconciliation technique which is a data verification process in which data in the is compared with original source data to check if the number of records in both the versions match or not.
- Data Breach/Corruption: If data in the differs from that in the then it has become corrupted during the . The presence of unrelated, missing, or anomalous data can also indicate data corruption.
- Solution: One way to prevent data corruption issues is by conducting and testing to ensure that data from the has been correctly mapped onto the .
- Semantics Risks: Semantics-related exceptions can occur even though the may have been completed smoothly. For instance, the contents of a column in a particular in the could get copied into a different field in the . This is not a case of data corruption or loss but it could lead to major concerns for companies.
- Solution: Experts of semantic data in the company should be kept in the loop while planning test cases to identify and mitigate such inconsistencies. Resolution of this issue often requires manual work to draw comparisons between the two systems.
Difference between, , and Data Conversion
The two terms,and data conversion are often used interchangeably. However, it is important to understand the difference between them.
, as established above, is the process of transferring data between different systems, , and locations.
Data conversion, meanwhile, refers to the transformation of data to a different. It is used because often have data stored in that need to be altered before the migration can happen. Therefore, data conversion is essentially a smaller step in the .
is another term that is used reciprocally with . It is the process of bringing together data from multiple sources and creating a consolidated view of the data for analytical purposes. It is used in data warehousing and is considered a major step in the process.
The global projected growth by 2026 is nearly $23 billion. It is becoming extremely important for businesses to equip themselves with the right and strategies. The Integrate.io toolkit offers all the cutting-edge tools that you need to perform smooth and secure .market is exponentially growing and its