Data migration is the process of transporting data from one place to another. While it is easy to understand the concept of data migration, it is a tough task to implement the process of data migration. In fact, data migration services are one of the most complex tasks in the field of data engineering. Please check our Data Migration Tips below…
What are the most common use cases of data migration?
Before getting into Data migration tips, let’s know three common use cases for data migration:
(a ) Application migration
(b) Storage migration
(c) Cloud migration
It is the transfer of an application from one storage or server location to another one. Either you can migrate an application from an onsite server to a cloud-based server, a cloud-based server to another cloud-based server, or shift data from one application to a new application, which only acknowledges data in a particular format.
It is the migration of data from legacy storage systems that are isolated and have become walled-off into data silos to storage systems that allow improved integration throughout all the information systems belonging to a business. Transferring data into a more integrated data warehousing system provides considerably better processing, flexibility, and economical scaling. It might also offer advanced data management capabilities such as snapshots, cloning, disaster recovery, backups, and more.
Cloud migration is the process of moving data from onsite servers or on-premises servers to a cloud-based data warehouse. This is the most important element for large organizational data systems right now. According to Forbes reports, 83% of businesses will be transferring their data systems to the cloud by 2020.
Concerns That Can Lead to Delay of Data Migration
There are various steps an organization can take to finish a data migration process effectively.
Conduct a migration impact assessment to analyze the levels of data quality and the probable cost of project delays. It defines the approach to be used for migration, creating a timeline and evaluating each level of the process. Additionally, it is essential to understand how to solve some of the most common challenges in data migration.
All data migration processes are different and regardless of the fact that projects will differ according to their scope, time limit, type of migrating database, and other significant circumstances; there are three major concerns that can delay the process of migration.
Insufficient Planning for Data Preparation
Data migration is not the same as copying information, so transferring data to a particular cloud storage solution requires good preparation. The time allowed for it must be measured in the data migration plan and the budget as well. If you ignore this step, you may lose the chance to filter out redundant data, like backups, old versions, or draft files that are often available in data sets that would not be required in the cloud workflow. The key is to discover an automated approach to choose what data will be moved and then save the important records without overlooking that various cloud workflows may need the data in a diverse format or enterprise than on-premises applications.
Lack of Data Integrity Assessment and Protection
Data validation is a vital step and also the easiest to however, it should not be assumed on the basis of thoughts and opinions but on confirmed facts. There is a valid concern that unauthorized access can occur during data transfer. It is the preparation and transfer of the data where the information is most vulnerable to lose or hacking.
Underestimating Cloud Scaling
Once the data reaches its target location in the cloud, the process of data migration is in the intermediate stage, the project is only halfway there. You have to make sure that the data transferred is true to the existing data source. Verifying that it can make storage cache layers complex. After the sent data has been verified, it is essential to extract, reformat, and dispense it so that it becomes ready to use by cloud-based applications and services.
Approaches to a Potential Journey to the Cloud
As organizations are adopting data analytics services and applications in the Cloud, the intricacy of their data management grows. As the Cloud itself has numerous environments and applications within its hybrid ecosystem.
Types of Hybrid Approaches
To compete in this multi-cloud environment, organizations require an end-to-end hybrid data management platform, enabling them to provide business data rapidly and safely in the cloud, hybrid platform, and on-premises ecosystems. It can be made possible based on various approaches:
• Simple hybrid integration- The most suitable for companies searching for a platform that supports them with integrating all of their cloud-based SaaS applications with all available local data to get a holistic view. For simple hybrid integration, an Integration Platform as a Service (iPaaS) would fulfill the needs to integrate applications, data, and processes in the cloud, hybrid and on-premises environments. The approach works well when companies are starting with a similar approach to integrate cloud applications and data sources.
• Advanced hybrid approach– As the organization grows, the intricacy around data management also increases, not only from the data sources or data volume but also related to new use cases. It needs a more developed platform to manage growing complexity, an advanced hybrid integration form. Businesses longing to see their requirements fulfilled should shift to next-generation iPaaS, which are exclusive, modular, metadata-based platforms, integrating big data, cloud, and on-premises systems. It even conducts advanced integration use cases, such as the Internet of Things and other compound data management solutions for business and IT users both.
The latest cloud, big data, and IoT technologies can be overwhelming. To take advantage of all these technologies, we must learn, modify our processes, and adapt our approach to data. This way, you can manage to master the complicacy and leverage the benefits. Migrating to the cloud is not only a matter of data but also of processes, this is vitally important when planning to conduct any data migration project.
If you want to avoid challenges, to ensure the final cloud infrastructure supports the required workflow, follow these data migration tips, if possible hire professional Data Migration Services to get expert assistance to complete your project. ExistBI has specialist teams in the United States, the United Kingdom, and Europe.