Data management has come a long way since the 1990s. Yet, many businesses are still dealing with legacy data warehouses hailing from the 90s or 00s era.
Today, our data demands are far more complex than they used to be. Teams need to be able to run various queries on customer data in seconds, build advanced data pipelines, process huge volumes of information, and carry out interactive analysis that drive real-time decisions.
If you’re using an older, on-premise data warehouse, you’ll likely be all too familiar with the added strain and quirks that come with it. Reports take too long to load. Sifting through data feels impossible. Integrations with newer tools are clunky (or completely non-existent). The frustrations related to working with legacy data systems mount up, as do the associated costs and risks.
Legacy data warehouses simply aren’t built to keep up with the speed, scale, and sophistication of modern data demands.
In this article, we’ll explore the downfall of using legacy data systems, the impact it has on your business operations, why modern cloud solutions are leading the way forward, and how to transition smoothly and confidently.
Common drawbacks of legacy data warehousing
At first glance, legacy data warehouses seem reliable. They’ve been around for years, they hold critical business information, and you know how they work.
But beneath the surface, those comfortable, bedded-in data systems are likely stirring up more problems than solutions within your business. As data demands grow, legacy data warehouses struggle to keep up which leads to higher costs, slower performance, and increasing frustration across teams.
Here are some of the most common pain points we see within teams using legacy data management systems:
Costly to maintain and upgrade
On-premise data warehouses can be more expensive to keep alive than their modern cloud-based counterparts. Between the upfront investment into physical hardware, software licenses, and specialist maintenance, the cost of running legacy on-prem systems can quickly add up.
Terata Product Lifecycle matrix showing dates for sales and support discontinuation for various Teradata hardware platforms. Image source.
Many long-standing on-premises platforms, like those offered by Teradata and SAP BW, are now reaching end-of-life support. This forces businesses to pay premium rates just to stay operational. Using legacy systems can often mean data teams spend more time maintaining systems than they spend analysing the data. The higher maintenance needs of these legacy systems causes a costly imbalance that stifles innovation and progress.
Slow, inflexible, and hard to scale
Legacy data systems were built for the data demands of the 1990s and 2000s, not for the speed and scale of modern-day businesses. As such, legacy systems can wind up becoming a bottleneck as they struggle to support real-time decision-making or reporting needs.
The monolithic design of on-premises data warehouses means you have to scale all components even if you only want to scale one specific aspect of the system. This inflexibility causes poor scalability and leads to teams having to use inefficient workarounds.
We can’t talk about modern day scalability without bringing AI into the conversation. AI has become a core component of data management with many cloud-based solutions offering AI-powered insights. As the demand for AI increases, legacy data warehouses will struggle to keep pace and companies using legacy data warehouses will find themselves falling behind.
Siloed data and integration issues
Older, outdated data warehousing rarely integrates well with newer tools and technologies. This inability to integrate can lead to siloed data that’s hard to work with.
These data siloes impact cross-team collaboration, hold organisations back from making data-driven decisions, and can lead to teams working with incomplete, conflicting, or poor-quality data. As a result, your data winds up being fragmented and disconnected from other business operations. Centralising data and switching to a modern data warehouse can help overcome these challenges.
Security and compliance risks
As with any business system, outdated architecture brings heightened security risks. Keeping data well-protected should be a top priority for any organisation and working with legacy data systems could be putting your data at risk.
Older data warehouses aren’t prepared to defend against modern cyberattacks. Patching vulnerabilities in legacy systems is often slow and resource-heavy, which can leave critical data exposed. Meanwhile, cloud data warehouses are protected by multiple robust cybersecurity defences that help protect against cyber attacks and phishing.
Complying with regulatory requirements should also be standard practice for any organisation working with data. The introduction of GDPR, ISO 27001, and other data protection standards, has raised the bar for how companies handle, store, and manage data.
Legacy platforms, however, lack the data governance, management, security and audit trails needed to stay compliant. Modern data platforms can make it easier to combine the capabilities of AI with the needs of data governance for simplified compliance.
Many businesses using legacy on-prem data warehouses find themselves stuck in a constant game of catch-up, where one slip-up could result in costly fines or reputational damage.
“On the surface, older on-premise data warehouses look cost-effective… it’s already built in, after all. But the hidden cost of vulnerability, manual workarounds, and missed opportunities can be much more expensive than the expense of moving to a modern alternative” – Lee Connor, Technical Director at Catalyst BI
The business impact of sticking with legacy systems
While the technical challenges are reason enough to reconsider your setup, the real cost of legacy data warehousing shows up in how it impacts your people, performance, and profits.
When your on-site data warehouse can no longer communicate effectively with other business systems and tools, your team loses the ability to make quick, informed decisions. In turn, they lose the ability to effectively perform crucial tasks which can lead to projects stalling and innovation grinding to a halt.
These delays cause ripples of frustration across every department. Marketing can’t access insights fast enough. Finance struggles with incomplete or surface-level reports. Operations lose valuable time waiting on data that should already be at their fingertips. Over time, your business strains against bottlenecks across multiple processes and departments.
Beyond the technical frustration, there’s a human and strategic cost. Talent analysts want modern tools that let them innovate. Being held back by legacy systems or having to spend their time fighting maintenance fires can lead to higher employee turnover as team members leave in search of more innovative employers. Meanwhile, not updating your data infrastructure puts your company at risk of falling behind more agile competitors.
While the ongoing cost of maintaining outdated systems might seem manageable, the real cost lies in everything you lose: time, productivity, talent, and your competitive edge.
Why Cloud data warehousing is a better alternative
If legacy on-premise systems are holding your business back, migrating to a cloud data warehouse could help you overcome these challenges and turn data into a valuable asset for your company.
Unlike fixed on-premises setups, cloud data warehouses have the power to expand effortlessly to handle larger datasets, can be accessed by multiple users, and can perform complex data tasks.
Snowflake is a prime example. Built for the cloud from day one, it delivers near-instant scalability, advanced security, and powerful data engineering capabilities.
Moving to a cloud-based system empowers your data team to be more proactive. The robust and flexible nature of cloud data warehouses you’ll experience greater integration with other tools, increased performance, and richer insights, with fewer limitations.
Plus, your total cost of ownership could significantly reduce when transitioning to a cloud data warehouse. Whether it’s due to being able to capitalise on usage-based payment models, reducing the cost of data inefficiencies, or by making your company more agile, moving to cloud data warehousing can be far more cost efficient than sticking with legacy systems.
Our data experts at Catalyst BI can help you make the move with ease. We’ll work closely with your team to identify the best solution for your goals and take the lead on data ingestion so you can focus on driving insights, not managing migration.
Real-world proof: How we helped Fenwick save 40% in operational expenditure by moving to a Cloud data warehouse
When Fenwick wanted to modernise their data infrastructure, we helped them move from a legacy SQL-based warehouse to Snowflake.
This move allowed their team to tap into huge efficiency gains. From a 40% reduction in operational expenditure to 10x+ faster data processing, and a 100% uptime for reporting, moving away from their legacy data warehouse allowed Fenwick to benefit from smoother and more innovative operations.
“Snowflake has unlocked everything for us. We’ve not just improved reporting, we’ve opened the door to real-time decision making, automation, and innovation.” — Michael Laverick, Head of Data, Fenwick
Read the full Fenwick case study to see how we helped them overcome the challenges of their legacy data warehouse and reap the rewards of moving to a modern system.
How to transition to a Cloud data management solution (without any fears)
Moving from a legacy system to the cloud can feel daunting. You’ll rightfully have concerns about workflow disruption, the cost of migrating, or the upskilling required to learn new tools. We’d be worried if you didn’t.
Raising these concerns shows that you care about business impact and, here at Catalyst BI, we’re here to help you mitigate the risks and maximise the benefits of transitioning.
With Catalyst BI by your side, the transition to cloud can be smooth, secure, and surprisingly straightforward.
At Catalyst BI, we’re well-versed in helping companies transition between data systems. Our expert team will guide you through every stage. Taking you from strategy and planning to data ingestion and optimisation, we’ll remove the complexity from your cloud migration and make sure your new solution meets your exact needs from day one.
Make your data warehouse work smarter for your business
Legacy data warehouses might have served you well once, but they’re not built for the pace or potential of modern business. Cloud-based data warehousing offers enhanced speed, scalability, and insights. By moving to a cloud data warehouse solution, your business can make smarter decisions and maximise your data’s potential without high maintenance costs.
If you feel like your data warehouse could work smarter for your business, we recommend starting with a free Data Strategy Workshop to gain clarity on your data systems and how an improved strategy could unlock greater value for your business.
Book your free Data Strategy Workshop today.