Tech execs are driven to modernize legacy systems for increased agility to match the fast pace of business. A valuable asset locked up in legacy systems is data. By planning a migration to the cloud organizations can leverage their legacy data and transform it into actionable insights.
This transformation can unlock new business opportunities, improve decision-making processes, and increase competitive advantage. With the cloud’s scalability and flexibility, tech execs can easily access and analyze vast amounts of data in real-time.
Businesses hold decades of untapped legacy data, ready to be utilized for harnessing its advantages.
True, a good portion of it could be aged, corrupted, or duplicate. Cleaning this data is crucial for unlocking its true value and making smarter, focused business decisions. Thankfully, with the advancement of technology and data management tools, this process has become much more efficient and effective.
Migrating from legacy to the cloud enables organizations to utilize cloud service providers’ (CSP) capabilities for big data processing, real-time analytics, and machine learning. These capabilities allow for the extraction of insights from the data. But before this can happen, the data needs to go through a thorough cleaning process.
The first step in this process is identifying and removing any duplicate or redundant legacy data.
This saves storage space and ensures accurate data analysis, avoiding result discrepancies.
Next, the data must be organized and standardized.
This involves formatting text strings, converting data types, and resolving missing values. Without proper organization, it becomes difficult to make meaningful connections or draw insights from the data.
When migrating legacy data to the cloud, consider the target data structure based on the use cases.
Data currently in structured format may be okay to dump into an unstructured data lake for analytics, as an example.
The data format in your legacy environment may differ from that in the cloud. It’s going to depend on the business need. So, there will be a lot of thinking required for how you are going to use this information. Are you going to query it? Are you going to run analytics on it? All these considerations will impact how you structure and store your data.
A major plus of cloud data storage is the flexibility to scale as required.
Traditional on-premises solutions require organizations to predict storage needs and invest in costly infrastructure that might end up underutilized. In the cloud, resources can be added or removed as needed, providing cost savings and increased flexibility.
Another important consideration when moving data to the cloud is security.
Although cloud providers offer strong security measures, organizations must enforce their own protocols and monitor data access regularly. This becomes even more critical if sensitive or confidential data is being stored in the cloud.
Besides scalability and security, leveraging the cloud for data storage can enhance collaboration and productivity in an organization. Teams can effortlessly collaborate on documents or projects from anywhere with internet access, eliminating delays due to location or time differences.
Furthermore, utilizing the cloud for data storage can also lead to cost savings for organizations. By ditching physical servers and gear, while cutting maintenance costs, businesses can greatly reduce their IT expenses. This allows them to reallocate resources towards other areas of their operations.
Lastly, the cloud offers reliable backup and disaster recovery options.
During system failure or natural disasters, cloud storage keeps data safe and accessible. This eliminates the risk of losing important information and allows for a quick recovery in case of any unexpected events.
To sum up, Cloud Service providers offer various services and partner tools to aid in migrating your data, including files, databases, machine images, block volumes, and tape backups. Successful data migration hinges on knowing what to move, where to move it, how to utilize it, and having knowledgeable individuals who can apply the data for making business decisions.
Click here for a post on how to transition data using cloud-based AI tools.
