In this digital age, business dynamics are continuously evolving which can make it challenging for your IT team to keep up with the growing data requirements. This is a time when most organizations are moving to a digital-first approach where your applications and data systems can be the make-or-break factor behind your business’ success.
If you have any legacy data systems that hinder your ability from making critical business decisions in real-time then this is the right time for you to launch a legacy modernization initiative. Read on ahead to learn more about how to modernize your enterprise data and stay one step ahead of the curve.
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What is Legacy Data Modernization?
Legacy data modernization is a process in which you transform your existing data infrastructure to make it more accessible, easier to maintain, and scalable. The process helps you increase data availability, improve data consistency, and makes it possible for you to seamlessly integrate the various applications and systems running within your organization.
Rather than thinking of it as being just an update to your existing data architecture, it is better to consider legacy data modernization as a continuous process that brings your enterprise up to speed and allows it to reap the benefits of latest technologies (such as the cloud and big data).
Most enterprises have a data architecture that compromises both on-premise traditional applications and cloud-based modern applications. The challenge lies in retrieving information from all your applications in real-time, something legacy systems are not capable of because of the high complexity and maintenance they involve. This is where a high-performance data modernization solution can help you bridge the gap.
Most Common Legacy Modernization Approaches & Methods:
One key challenge with legacy modernization approaches is to ensure that the modernized system has similar capabilities and is compatible with all your existing data models and formats. Keeping this in mind, there is no single approach to modernizing your enterprise data but rather, based on your requirements and goals, you can choose one of these methods:
Data Migration
Data migration involves moving data from an existing database system to one from a different vendor. For example, you might move from the Oracle database to a Microsoft SQL Server database to enable better compatibility and connectivity with your Microsoft Azure applications.
When migrating data, you are not making any changes to the data structures or formats you use so both your existing and target schemas will remain the same and no major changes will need to be made to your existing applications. However, the process will involve migrating code such as stored procedures and views to the target database system.
Data Conversion
Data conversion is the process of moving from an existing legacy file system or database to a new (and more advanced) technology. For instance, if you have a file-based database, you may convert to an RDBMS to have less redundancy and better structure, or you may convert to a NoSQL database for better retrieval times and increased storage capabilities.
When using the data conversion method, quite a lot of re-engineering is involved since you need to refactor both your applications as well as your data formats. Your existing schemas will be different from those in the target system and data transformations and cleaning will be required during the conversion.
This process can be done by writing code for transformation and data migration, or you can make use of an ETL tool to simplify and automate the process for you.
Application Integration
An application integration approach is where you upgrade from an existing application version to a newer version to have access to new features and better support. For instance, you might be upgrading from Oracle server database’s version 11g to version 12c. Both the schema definitions and data formats remain the same in this approach, but you do need to remove deprecated and unsupported code from your applications.
As with data conversion, application integration can be automated and simplified through data modernization software that are available in the market.
Best Practices for Legacy Data Modernization in Enterprise Ecosystems
As we described earlier, data modernization is not a one-time effort but rather an ongoing process that ensures your business’ data architecture keeps evolving. Here are some best practices for legacy system modernization.
Build support for different data formats and structures
The volume of structured and unstructured data that businesses have to deal with has grown exponentially since the advent of big data. What this means is that your data architecture should be designed to accommodate and integrate data from multiple sources in different formats.
This is a key thing to keep in mind during legacy modernization because you do not want to go back to the drawing board a year down the line due to a rigid and unscalable data architecture.
Keep the future in mind
This is the 101 with all modern data initiatives: Build for the future. You need to have a data solution that can scale quickly, handle all the volume of data you throw at it, and still have the capacity to be customized to new data requirements. When driving your legacy modernization initiative, make sure that your architecture is scalable, agile, and enables real-time reporting.
Make use of the right tools
Utilizing the right tools is a crucial factor behind the success of any legacy modernization approach. You want to make the process as simple and quick as possible to ensure that: you are not reinventing the wheel, and you can automate the process to make modernization a continued effort rather than a one-time initiative.
Conclusion
In this era of big data, enterprises need quicker access to data with seamless integration between all their applications. Because of this, legacy data modernization has become an essential requirement for businesses.
The process of data modernization can be quite complex, especially without the right tools but this is where Astera Centerprise can help you out. Astera Centerprise is a powerful data integration tool that helps businesses realize the true potential of their information assets.
Whether you are looking to upgrade database systems, convert your legacy systems to an RDBMS, or migrate from one database system to another, Astera Centerprise has all the features you need to build a high-performance, automated, and scalable modernization solution.
To learn more about legacy data modernization and how Astera can help, please reach out to us.
