A legacy system is any outdated hardware or software that's still in active use. Legacy systems are common in large companies with a long history, such as financial institutions.
Legacy systems can be expensive in terms of support and operating costs. Integration is often a challenge, which can impact overall performance. Outdated systems may also pose a security risk.
What are the Telltale Signs of a Legacy System?
"Legacy system" is something of a subjective term. Some users might ignore an available upgrade for a good reason, like when the new version is missing one or more essential features.
However, there are various definitive signs that hardware or software is a legacy system, such as these:
No active support: The vendor has stopped providing support, so they no longer release regular updates and security patches. For instance, Microsoft ended support for Windows 7 in 2020, so there will be no new versions of this operating system.
Few skilled professionals: Companies often find it hard to hire someone who understands their legacy systems. For example, college courses generally do not teach the 60-year-old programming language COBOL, but the banking sector still widely uses it. The banks then struggle to find COBOL developers who can assist with their code.
Poor interoperability: Most organizations will need to integrate their various systems with each other. This task is simple with modern cloud software. Older, on-premise software, however, may depend on manual file export and import processes.
Lack of features: Legacy systems don't receive updates, so they won't have any recent features. For example, an older Customer Relationship Management system might not offer modern tools, like sentiment analysis powered by machine learning.
Because legacy systems are no longer evolving, they become increasingly troublesome as time goes on.
Problems Associated with Legacy Systems
Companies may choose to stick with legacy systems for a number of reasons. Frequently, it's a matter of cost — migrating to a new system can be a complex and expensive process.
However, legacy systems are often more trouble than they're worth. Their poor performance can have a knock-on effect across the entire network and pose a threat to data quality.
Problems associated with legacy systems include:
Poor security: Legacy systems don't receive security patches, which leaves them permanently exposed. Hackers are constantly looking for vulnerabilities in legacy systems because they know these systems are weaker than systems that receive regular patches.
Data loss: A legacy system may not integrate easily with other systems on the network. This often means that the data team has to rely on manual processes to extract data from the system. It's a suboptimal approach with a high risk of data loss.
Bad user experience: User experience design is a rapidly growing area of computer science. Designers are getting better at providing friendly, feature-rich services to users. When companies rely on older interfaces, it can be a slow and frustrating experience for staff.
Legacy training: New users are less likely to have experience with a legacy system, especially if they're new to the workforce. That creates additional overhead, as the company has to train each user to work with older systems. Sometimes, this might be an entirely new paradigm for the user, such as when a system relies on command line prompts.
Compliance issues: Many older systems cannot handle modern compliance requirements. Laws such as GDPR and CCPA have a major impact on how companies handle Personally Identifiable Information (PII). Without the right tools, companies might struggle to meet the legal requirements for data management.
All these issues can drive up costs by a substantial margin. An objective cost analysis will often show that upgrading is more cost efficient in the long run than staying with the legacy system.
How to Move on from a Legacy System
System migration can be a complex challenge, especially if the legacy system is in everyday use. As with most change projects, it's typically a matter of good planning. The migration process usually goes like this:
1. Establish the new system. The organization will set up the new system so that it's ready to use. The data manager may run a small pilot scheme to confirm that the new system works and offers the same functionality as the old system.
2. Extract the existing data. The migration team will do this using the legacy system's export tools. This will create a file of raw data that's not yet compatible with the new system.
3. Apply data transformations. The team will then perform a sequence of data transformations. This may include:
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Data cleansing to remove any corrupt or duplicate values.
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Data validation to ensure that all values are logically consistent, like checking that all phone numbers contain ten digits.
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Data mapping transpose the data from the old schema to a new schema that's compatible with the more modern system.
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Data enrichment to merge the raw data with other relevant data, which helps to create more detailed records.
4. Load data into the new system. The team will then perform a data import to bring all the legacy data into the new system. Systems users will still have access to the records that previously lived on the legacy system.
5. Switch off and roll out. Finally, the team will take the legacy system offline. Users will move fully to the new system. This helps to avoid a situation in which some users are still creating fresh data on the legacy system, which may lead to inconsistency and redundancy.
This kind of migration is easier when there's a reliable data transfer platform between the two systems, such as an Extract Transform Load (ETL).