Companies that have relied on mainframe technology for decades are often hesitant to upgrade to modern technology platforms. This is understandable, especially considering the amount of legacy data that these companies hold. However, with the rise of cloud technology and AI, companies can seamlessly move their mainframe data onto the cloud and continue to leverage it, without having to invest in new infrastructure. Let’s explore how to leverage decades of legacy data on the mainframe with cloud technology and AI.
- Assessing your data – The first step in leveraging your mainframe data is to assess its size and complexity, alongside how it can be best used in the cloud. You need to determine if your data needs to be transformed, optimized, or just migrated to a new platform for easier analysis. By doing this, you’ll be able to determine its value and how to extract it. Additionally, you also need to consider the security requirements for your data. Ensure that your data privacy and compliance policies are up-to-date to meet modern standards.
- Migration Strategy – After assessing your data, you need to choose a migration strategy. You can decide whether to move data all at once or in chunks gradually so as to maintain consistency and avoid data loss. You can use migration services that eliminate the need for human intervention, prevent migration errors, and automate the migration process, thus saving time and money. Such services can move data from mainframes to different cloud providers such as AWS, Azure, or GCP.
- Cloud Storage – Once your data is on the cloud, you can use various storage solutions depending on the nature of your data, the frequency of data storage, and whether your data is temporary or permanent. Cloud storage providers offer options such as Amazon S3, Google Cloud Storage, and Azure Blob Storage among others. Each storage option has various advantages, and you need to be mindful of factors such as security, accessibility, and cost.
- Artificial Intelligence – Once you have migrated your data to the cloud, you can use AI to gain valuable insights. AI can identify hidden patterns, predict trends, and mine your data for valuable insights that can help you make decisions that improve your bottom line. With AI-powered analytics tools, you can continue to learn from historical data and more easily identify trends as they emerge in real-time.
- Managing your Mainframe Data – Although it’s now on the cloud, your decades-old mainframe data is a critical asset to your business. And while moving everything to the cloud might seem like the logical step, it’s not always necessary or feasible. Rather, managing mainframe data with integrated solutions that maintain data integrity and security, as well as compatibility with modern tools, can be a much more efficient option. Tools such as mainframe virtual tape libraries and third-party storage management programs can help manage mainframe data at a lower cost.
Companies that have tons of legacy data on a mainframe don’t have to continue relying on outdated technology. Migration to cloud technology provides an opportunity to modernize operations by improving data accessibility, security and analytics. In addition, the implementation of AI can help exploit critical business insights from historical data. By leveraging mainframe data, companies can gain a competitive advantage and position themselves for future growth.