Legacy data can be essential to your business, yet it’s often increasingly difficult to access and manage. Despite its age, this data often still holds value, and it can impact everything from customer records to financial reporting.
Mismanagement, however, can lead to security risks and higher costs. So, let’s define legacy data, explore its challenges, and discover the various types of legacy data. We’ll also get a handle on the best practices you should follow to manage legacy data effectively.
How do you define legacy data?
So, what does legacy data mean exactly?
Legacy data is information stored in on-premises systems, which while often holding valuable data, also present challenges due to their limited accessibility and compatibility with newer tech.
Whether it’s customer info or financial records, legacy data is often critical to your business, even if the infrastructure around it makes it complex to use with modern systems.
Different types of legacy data
Legacy data can take various forms, each of which has its own unique characteristics:
Structured data
Structured data is organized and has predefined fields that allow for straightforward querying and analysis.
Think about your customer relationship management (CRM) system, which stores info like customer names, contact details, purchase histories, and past interactions.
Each of these elements fits neatly into a database table so you can quickly retrieve and analyze customer data.
However, plenty of businesses have this critical structured data locked away in legacy systems. For example, if your financial transaction records are stored in a legacy mainframe system, accessing them for reporting or auditing purposes might be cumbersome and time-consuming.
That’s why facilitating easier access to this structured data is essential. It means you can improve accessibility and enable real-time analysis for faster, data-driven decisions.
Unstructured data
Unstructured data poses a different challenge. This type of data lacks a predefined format and includes a variety of content like emails, PDFs, multimedia files, and other documents.
While it may not fit neatly into traditional database structures, unstructured data often contains useful info. For example, customer feedback collected through emails or social media can reveal trends in consumer preferences that your structured data might not.
Let’s say you run a manufacturing company that has archived years’ worth of design documents and project reports as unstructured data. If this info is stored in legacy systems without a retrieval strategy, it’ll be challenging to access when needed.
The solution? Implementing modern data management will help you make sure this unstructured data is preserved and made accessible.
Virtual Storage Access Method (VSAM) files
VSAM is a file storage access method developed by IBM in the 1970s. VSAM datasets don’t fit comfortably under the category of either structured or unstructured data. The data isn’t structured in the traditional sense, but is organized and maintained on an IBM mainframe in a catalog structure.
VSAM files often represent critical data for the enterprises who use the method, which typically includes organizations in the financial services industry.
Maintaining, accessing, and effectively utilizing VSAM files is becoming increasingly complicated due to factors such as the scarcity of resources and expertise. OpenLegacy, however, excels at aiding enterprises to make the most of this type of legacy data through legacy system integration.
Machine-generated data
Machine-generated data comes from automated systems like logs from software apps and network activity.
While this data is often structured (think of the logs your servers generate or the data collected from IoT devices), the sheer volume and speed at which it’s created can overwhelm some storage and processing solutions.
For example, a logistics company might generate massive amounts of data from devices used to track shipments and sensors used to check the temperature of refrigerated trucks.
If your legacy systems struggle to handle this influx of machine-generated data, you risk losing info that could improve your efficiency and reduce costs.
Legacy modernization can help you update your data architecture so you can collect and store this data more effectively.
Human-generated data
Finally, human-generated data includes everything produced by individuals, from business reports and presentations to user-generated content.
This data can be scattered across lots of platforms and formats, which complicates retrieval efforts when stored in legacy systems.
For example, your marketing team might create useful reports and presentations on customer engagement, but if those documents are stored in disparate locations (like shared drives, email attachments, or even legacy databases), gaining a big-picture view of customer insights will be a daunting task.
Imagine trying to compile a comprehensive analysis of your product performance by manually gathering data from multiple legacy sources. The process could take weeks.
With the right modernization strategy, you can streamline access to human-generated data, too.
Common challenges of managing legacy data
We’ve hinted already at the potential challenges posed by these different types of legacy data. Now, let’s look more closely at the problems that can typically arise.
1. Complexity of legacy systems
We know that attachments to old systems and traditional ways can make change difficult. However, legacy systems are known for being highly customized and complex.
While this might have worked well for specific needs in the past, it can quickly become a burden over time.
As your company grows and its technology evolves, the once-tailored systems can become increasingly difficult to manage, especially when they rely on frameworks that fewer and fewer people in your organization have the expertise to manage. Trying to integrate these systems with modern solutions often leads to unforeseen problems and can consume time and money.
Heavy customization
Chances are, your legacy system was designed and customized to meet the specific needs you had at the time. But what was once a perfect fit can start to feel restrictive.
Each and every customization layer can make changes or upgrades more challenging. Plus, the original engineers who built the system may no longer be available to help decode these customizations. As a result, even minor adjustments will require significant time and expertise.
Outdated or incomplete documentation
As people who originally worked on these systems leave or retire, documentation could be lost or left incomplete. Over time, crucial info about how the system functions or how it was customized will soon become fragmented or outdated.
Without thorough documentation, maintaining or upgrading the system becomes a guessing game for new IT teams. That means an increased risk of errors and system failures.
Technical debt and integration challenges
Technical debt builds up when your business delays necessary system improvements. This can leave you with technology that’s difficult to integrate with your newer solutions.
As these debts accumulate, your legacy systems may become more fragile and prone to disruptions. Before you know it, the task of integrating your data into the cloud or with modern apps will be a complex and costly endeavor.
2. Security
Security is one of the most pressing concerns when managing legacy systems. Cyber attackers are increasingly sophisticated, and older systems can be seen as easier targets.
This not only risks data breaches but also puts your entire business at risk of compliance failures and financial penalties.
Data integrity and vulnerabilities
Over time, legacy systems can develop vulnerabilities that weren’t considered threats when the systems were first built. These weaknesses can compromise data integrity (the accuracy, consistency, and completeness of your data).
Legacy systems also have a harder time integrating with modern security tools.
Larger attack surface
Aging infrastructure often has multiple, sometimes outdated, components—each creating an entry point for potential attackers. This larger attack surface means you’ll have to devote more resources to monitoring and defending these systems.
Outdated security protocols and ineffective access controls
Access controls in legacy systems are also often insufficient by today’s standards. Passwords and other access credentials might not be properly managed, and older encryption methods are vulnerable to hacking.
3. Cost
The financial burden of managing legacy systems can be significant. As tribal knowledge of the systems within your organization becomes limited to a smaller pool of people, it can become more difficult—and costly—to retain that expertise..
Hardware and software licences
Legacy systems can be expensive to maintain, in part, due to the price of the hardware and software licences required. That expense is in stark contrast to the comparative efficiency of cloud-based alternatives that can scale up and down based on your needs .
Training and support
Training employees to work with legacy systems and complicated tech stacks adds to the cost burden.
IT professionals skilled in modern tech may even lack the expertise to work on these older systems. You might have to invest in specialized training or hire external consultants.
Additionally, support services for legacy systems are harder to come by, meaning you may have to pay a premium for expertise when issues arise.
4. Data quality and compatibility
Over time, legacy data can suffer from quality and compatibility issues. Incomplete records and duplicate entries (or any data that no longer fits your business needs) can all lower the value of your legacy data.
When you try to integrate this data into modern systems, you’ll likely face compatibility problems that will require additional time and resources to sort out.
This is because legacy data might be stored in formats that are no longer supported by modern databases or software.
This means you’ll have to convert or clean the data before it can be effectively used in new systems or consider legacy database migration.
Without proper management, these compatibility issues can lead to data loss or inaccuracies.
5. Accessibility
Legacy data access is another pain point for lots of businesses. Legacy data is often siloed in different systems, which makes it hard to retrieve when needed. Without modern interfaces or user-friendly systems, accessing info will require specialized knowledge or custom-built solutions.
For many businesses, the difficulty in retrieving data isn’t just an inconvenience. It directly impacts your operations. When systems are slow or inaccessible, teams will struggle to get the information they need. This quickly results in inefficiencies that can slow down projects and delay customer service responses.
6. Legal and regulatory compliance
Relying solely on legacy systems can also be a liability when it comes to compliance with modern data protection laws and regulations.
Whether it’s the Health Insurance Portability and Accountability Act (HIPAA) in the US or the General Data Protection Regulation (GDPR) in Europe, failing to meet these regulatory standards can result in heavy fines and even damage your reputation.
Older systems can lack the necessary features to properly secure and manage sensitive data in line with the latest regulations. That makes ensuring better connectivity with modern solutions key.
Data retention policies
Legacy systems might not have the tools needed to comply with modern data retention policies. This leads to accidental data loss or breaches, and you can face serious penalties for failing to store or delete data.
Data security and privacy
Privacy laws have evolved a lot over the years, but legacy systems may not have the advanced encryption or security protocols needed to meet modern standards. Data breaches in these systems could expose sensitive info and leave you vulnerable to lawsuits and fines.
National or international legislation
If your business operates across borders, you have to comply with a host of national and international regulations. Your legacy systems may struggle to meet the requirements set forth by these laws, especially if they don’t have the flexibility to adjust to new standards.
Industry-specific regulations
In industries like healthcare and finance, additional layers of regulation apply. Legacy systems that haven’t been updated to meet these industry-specific rules can put you at risk of non-compliance, which can lead to fines and even legal action.
Benefits of legacy data system management done right
Despite their challenges, a well-managed legacy data system can improve your operational efficiency and strategic decision-making. Addressing the challenges associated with legacy data is a must, but when done right, you can harness these systems for the future. Here’s how:
Improved data access
Streamlining data retrieval and integrating intuitive interfaces will make it much easier for your employees to find and use critical info.
Picture your customer service representatives having the ability to quickly access past interactions with clients. This will help them address inquiries accurately and swiftly.
A tool like this not only boosts customer satisfaction but also equips your team to make timely, informed decisions.
When data is easier to access, it also encourages collaboration among departments. Different teams can share valuable information without friction. For example, your marketing team might discover useful customer behavior trends from legacy data that can then inform your sales approach.
Higher data quality
Managing legacy data effectively means cleaning and validating records so you have that all-important high data quality. This involves:
- Identifying and eliminating duplicates
- Correcting errors
- Updating outdated info
- Ensuring consistency across datasets
Doing all of this means you can be sure that you’re using trustworthy data. After all, reliable data translates to more accurate analytics and reporting.
Focusing on data quality will also help you avoid costly errors that could disrupt business operations. For example, if your financial records are accurate, you’ll minimize the risk of mistakes during audits and maintain trust and transparency with your clients and stakeholders.
Better decision-making and improved efficiency
Having usable, accessible data that can be used for analytics is a top concern for many businesses. With accurate and accessible data, your decision-makers can rely on real-time data so they can make decisions quickly and effectively.
This, in turn, leads to improved operational efficiency. Teams can adapt quickly based on current info.
For example, if sales data reveals a sudden shift in customer preferences, your marketing team can promptly adjust campaigns.
Well-managed legacy data becomes a vital resource. It provides a solid foundation for launching new products or refining existing processes, but it needs to be accurate and accessible.
Enhanced risk management
Security and privacy are at the top of everyone’s mind when it comes to buying new software and handling business data.
When you manage legacy data properly, you can also better identify and mitigate risks. Keeping accurate records and staying compliant with regulations means your business can lower the chances of facing legal and financial repercussions.
Additionally, by monitoring legacy data, you can spot possible system failures or security issues before they escalate. This proactive approach doesn’t just shield your business, it also builds confidence in your brand. You want to be seen as having a reliable risk management approach.
Easier compliance with regulations
Effective data management is essential if you want your legacy systems to fit in with compliance standards. This includes implementing strong security measures and data retention policies.
For example, if you operate in the healthcare sector, adhering to strict patient data protection regulations is essential.
Having a clear audit trail through well-managed legacy data also simplifies compliance reporting and makes it easier to demonstrate adherence to regulations when necessary.
This can be a huge time-saver during audits, as you have a quick route when needing to know how to check legacy data, and you’ll appear much more credible rather than chaotic.
Cost savings
Finally, while managing legacy systems can seem pricey, proper management often leads to cost savings in the long run. Ultimately, if you’re boosting efficiency and improving data quality, you can cut costs associated with errors and poor resource management.
Cost savings become even more noticeable if legacy systems are integrated with cloud solutions. Transitioning to a cloud-based model allows you to reduce infrastructure expenses and increase scalability. Over time, these savings can free up resources and make you more agile as a business.
Key elements of legacy data management
Managing legacy data involves several key elements. Focus on these areas, and you’ll create a smoother experience for your team and improve the usefulness of your legacy data.
Legacy data archive management
When it comes to a business’s trustworthiness, how they use and store data is a top concern. That’s why a solid data archiving strategy is a key part of any enterprise’s on-premises systems. What can be challenging, however, is maintaining such if you decide to migrate legacy data or otherwise modernize your systems.
A legacy data archiving strategy is critical in those circumstances to retain compliance and operational continuity, as well as strategic planning.
You might implement a tiered storage solution—actively used data can be kept on high-performance cloud storage, while archived data can be moved to less expensive, slower storage options.
A well-structured archiving system also allows you to maintain a clear data lineage. This means you can easily trace where data originated—whether it pre-dated any migration or modernization efforts or not—and how it has been transformed over time, which is essential for audits and compliance checks.
Legacy data preservation
Maintaining the integrity and usability of legacy data over time is also vital. Diminishing expertise in on-premises systems can make accessing and using the data more difficult. As such, migration or modernization efforts are often needed to provide sustainable access. .
For example, if your company has historical sales records stored in a legacy database, you might choose to migrate that data to a newer cloud-based platform. This can improve accessibility to the data for your operational teams and make innovation in how you use the data easier.
Additionally, it’s worth thinking about how the preservation process can facilitate better analytics. Ensuring the accessibility and utility of legacy data may means you can leverage advanced analytics tools that provide more useful insights into your performance.
Let’s say you have old customer databases. Making these accessible to machine learning models may mean you can use them to identify patterns and trends that inform your marketing strategies.
Taking the time to preserve legacy data not only safeguards its usability but also makes sure that it remains relevant for future decision-making. This is especially important for historical records that inform your strategic planning, such as market analyses from previous years.
Legacy access and retrieval of data
Streamlining access to legacy data should be a top priority. You should implement user-friendly interfaces and modern search capabilities, as these make it much easier for your team to find the information they need.
Imagine a scenario where your sales team is trying to analyze previous sales trends to craft a new strategy. If they can quickly pull up relevant data from legacy systems with a simple search, they can make faster and better-informed decisions.
You could use application programming interfaces (APIs) to help do this. Integrating your legacy systems with modern applications through APIs means you’ll create pathways for data retrieval that are both efficient and secure.
This not only reduces barriers to access but also allows different departments to collaborate more effectively, as everyone can draw from the same pool of data.
Finally, make sure you invest in training your staff on how to navigate these new systems and tools. When your employees feel confident in their ability to access and utilize legacy data, they’re more likely to use it well.
Data migration from legacy systems or legacy data integration?
Moving data is a top concern for many businesses. But when it comes to legacy data migration, you might find yourself at a crossroads.
Should you perform data migration from the legacy system to a new system, or should you integrate your legacy system with, and therefore make the data accessible to, modern cloud solutions?
The latter is often a more palatable choice for businesses than complex data migration from legacy systems. OpenLegacy is at the forefront of this transition, especially with our recent achievement of the AWS Migration and Modernization Software Competency status.
With this recognition, OpenLegacy has established itself as a trusted partner for businesses that, rather than necessarily migrating data from legacy systems, want to modernize and make their data cloud-ready. The flagship product, OpenLegacy Hub, is designed to simplify the entire process.
Types of legacy data migration
When considering your options, it's important to understand the different types of legacy data migration that you could pursue.
Platform migration
Platform migration involves transitioning your entire legacy system from its current environment to a new one, which is likely to be cloud-based. This is especially useful if you’re looking to capitalize on the scalability and flexibility that cloud platforms offer.
For example, if you’re a financial company, you might want to migrate your legacy transaction processing system to AWS to take advantage of cloud resources that can handle peak loads during high-transaction periods like month-end processing.
OpenLegacy can support a phased approach to migrating legacy data and applications using a hybrid or co-existence framework. This mitigates risk, as well as accelerating the need for cloud-based access (no need to wait for full migration of both data and apps) to support business needs now.
Database migration
Migrating your legacy databases to a more scalable and flexible cloud-based environment can also lead to better performance and cost savings, as well as easier access to data.
How does it work? Let’s say you’re a retail company migrating your customer relationship management (CRM) system from an on-premises database to a cloud database.
The migration process typically involves mapping data from the legacy database to the new cloud-based database and making sure that all data relationships are preserved.
OpenLegacy can support and simplify this process by making your data accessible via a modern API that is auto generated and deployed in the cloud..
With this simpler process in hand, you can focus on leveraging your data rather than getting bogged down in technical details.
Application migration
If you’re looking to move entire applications to the cloud, OpenLegacy provides a straightforward pathway.
For example, a healthcare provider may be migrating legacy applications like patient management apps from an outdated server to the cloud to improve accessibility for remote workers and enhance security protocols.
Application migration can involve significant reengineering of your applications to ensure they function optimally in the cloud.
OpenLegacy's platform helps with this by providing tools that help maintain vital connections between legacy applications and modern cloud services.
This ultimately helps you migrate your applications without disrupting ongoing operations so you have a smooth transition.
Storage migration
Cloud storage offers scalability. That means you can increase or decrease your storage capacity as needed without the upfront investment in physical hardware.
Returning to the manufacturing company example, you could migrate your vast archives of production data to a cloud-based storage solution. This frees up valuable on-premises resources while benefiting from cloud providers’ advanced security measures.
With OpenLegacy, you can automate the migration process to cloud storage so that your data is securely transferred while maintaining compliance with data protection regulations.
Server migration
Legacy servers can become a bottleneck in your operations and often require extensive maintenance and upgrades to remain functional. Migrating these servers to cloud-based solutions improves performance and reduces maintenance costs.
For example, if you’re a logistics company, you might migrate your order processing server to AWS. This wouldn’t just improve speed; it would reduce costs associated with physical server maintenance, too.
Format migration
Legacy data often exists in formats that are incompatible with modern apps, which quickly creates obstacles to using it effectively. Format migration involves converting legacy data into more modern formats that modern systems can easily interpret.
Imagine you’re an insurance company that needs to convert claims data from a proprietary format into JSON or XML for integration with new apps. Doing this manually would take weeks (or months) and create huge disruptions to your business.
Luckily, OpenLegacy facilitates this process by providing tools that automate data transformation. And once data is transformed, your teams will find it easier to gather insights from previously siloed data and make decisions with it in the future.
A hybrid integration approach to legacy modernization
Many businesses are already shifting their operations to the cloud thanks to decreased workloads and more secure environments.
At OpenLegacy, we understand that every business is unique. That’s why we advocate for a hybrid integration approach to legacy modernization.
This method allows you to gradually migrate your legacy systems to the cloud while maintaining those all-important connections to your existing infrastructure.
Using the OpenLegacy Hub will also allow you to automate the creation of cloud-native APIs directly from your legacy systems.
This not only speeds up the migration process but also minimizes the risks typically associated with traditional modernization methods, such as data loss and breaches.
Leigh-Ann Silver, the Head of Technology Alliances, emphasizes OpenLegacy’s commitment to this mission:
“OpenLegacy is thrilled to be recognized by AWS as the leading integration and modernization platform. This recognition underscores our dedication to providing enterprises with cutting-edge solutions for legacy modernization.”
Understand legacy data and get the most from yours with OpenLegacy’s help
Navigating the complexities of legacy data can be daunting, but you don’t have to go it alone. With the right strategies and tools in place, you can transform your legacy systems into powerful assets that work more readily with modern solutions. OpenLegacy is dedicated to helping you make this transition as smooth and efficient as possible.
If you make use of our cloud-native modernization platform, you can accelerate and de-risk the accessibility of your legacy data for modern cloud applications.
As you embark on your legacy modernization journey, remember that the goal isn’t necessarily to move data but to empower your business with data-backed insights.
Ready to take the next step? Let OpenLegacy guide you through the complexities of legacy data and help you achieve your modernization goals.
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