In the world of technological advancements and businesses going digital, data has proven to be one of the key assets to a business. The more customer data a business has, the more likely they are to generate lead and achieve higher conversion rates. Businesses also use data to improve their operating performance and profitability.
Data is typically stored in onsite servers or cloud data storages, data warehouses and even data lakes. These data storages often need upgrades, overhauling or the company might simply want to increase their storage capacity by adding more storage or merging data warehouses.
In such cases, the data needs to be transported from one to the other source. This is automated using programs or scripts to map the data and transport it in the desired format to the new or improved storage. This process of data transportation is technically known as data migration.
Automated Data Migration
Depending on the nature of business, data migration can actually be a very big deal for the companies. Organizations try to minimize the potential impacts a data migration process might have on their business by automating it.
A data migration process requires a lot of planning and understanding of the design, replication, hardware requirements followed by installation of migration software and configuration of hardware.
Data migration projects are accelerated using Robotic Process Automation (RPA) by adding speed as well as efficiency in the process. One of the major appeals of using an automated process is the scanning benefits that allow you to check for errors faster and more consistently compared to a manual operation where you would have to go back and check for errors and in some cases the errors might be detected after a significant amount of the process has already been completed.
Approaches to Data Migration
An organization’s approach to data migration is majorly dependent on their need for data or server availability. Parallel approach is the most preferred one in case of a storage change as this keeps the old and new storage running at the same time while the data migration keeps taking place. Phased approach follows a slower (hence, costlier) strategy where the data is transported slowly, part by part in phases.
However, this allows the users to get more time to get accustomed to the new data storage or system. The most cost-effective approach is The Big Bang approach where the entire process takes place in a very short time, as short as one weekend. You might leave office on a Friday using the old platform and walk into the office on Monday to start working on the new one. The Big Bang method is not applicable for all sorts of operations as this requires a complete shutdown during the data migration period.
Cloud Migration refers to a vast scope of moving digital assets across cloud platforms. This is not limited to any format of data but includes various resources such as workloads, applications etc. Cloud migration could refer to migration from a physical storage to the cloud or from one cloud platform to the other.
Organizations are now preferring to use cloud platforms over physical data centers as it empowers you with virtually unlimited computing resources. Which also means that data migration on the cloud or ‘cloud migration’ would be significantly faster.
Cloud migration requires expertise of planning, designing and implementing application, database and server migration. Firms like Epsilon Solutions who are experts in these projects are recognized by cloud companies like Amazon with certifications such as ‘AWS Certified Cloud Practitioner’ etc. so that clients can distinguish the right firm to deliver their desired solutions!