Build vs Buy: Which Data Integration Approach is Right For You?
In pursuit of better business decisions, today’s business leaders are looking to either build or buy their way into better data connectivity. Dated, siloed information is putting organizations so far behind their peers, Gartner predicts 80% of organizations will fail to scale their digital business through 2025.
Since no single data connectivity system works best for every situation, organizations leverage multiple solutions including:
- Embracing data fabrics,
- Focusing on DataOps, and
- Amplifying their data integration processes.
A data access layer bridges information from multiple solutions to inform every aspect of the enterprise – without further complicating IT workloads. Whether you build or buy this access layer carves the course for your long-term flexibility of your digital operations.
As your organization chooses to either build or buy this integration, you’ll want to keep your IT team lightweight while giving your data consumers the speed and access they need to readily support major corporate initiatives. We’ll walk through some key questions to ask as you weigh the pros and cons of creating your data access layer.
Will Your Data Access Layer Support Your Enterprise?
A reliable data access layer propels business forward, democratizes data, and enables data driven decisions throughout the organization.
However, you’ll need a focus on solving today’s challenges with flexibility to adapt for the future of your staff and customer needs. The right data access layer solves for today — and can change for tomorrow. Let’s drill down into specific traits of an effective data access layer.
- Are you streamlining development?
If your data connectivity tool adds tons of extra work for your team, it’s the wrong tool. Efficient organizations choose solutions that refocus their IT teams away from endless cycles of developing, testing, and maintaining custom code. Effective data access connects your teams to new data sets as soon as they decide they need it.
- Are you taking action in real-time?
Latent workflows can only leverage data once your teams retrieve and prepare it. Just as DevOps streamlines app support lifecycles, intuitive organizations choose a modern integration layer to support real-time decisions via DataOps. If your solution offers fewer steps from intake to action, your teams gain near-instant analysis and reporting.
- Is your integration future-proof?
IT maintenance is a major roadblock to flexibility. Organizations prepare for the future with solutions that constantly expand as their data ecosystem changes and grows — without congesting IT work queues. Embrace a data access layer that clears the queue and frees your IT team to work on more important initiatives.
- Do your connections benefit everyone equally?
Your data stack should spread information freely and integrate data stores equally for all. The right data access layer will eliminate patchwork integration to centralize and democratize your full data ecosystem for every department and team.
Custom data access layers can complicate these benefits in ways that existing market solutions already solve. If your internal IT lacks the bandwidth to build and support your expanding web of data pipelines, your new technologies become new problems.
Are In-House Data Access Layer Costs Worth It?
Managing your custom data integration solution can drain IT resources. As a result, frontline staff can lose productivity and eventually abandon your solution for shadow IT workarounds. This pokes holes in your carefully planned-out data strategy, and risks security and legal compliance.
Organizations now tap the growing data connectivity market for integration solutions that lighten their work rather than distract from it. Leading market providers are already solving the biggest data challenges with granular customization – rendering in-house solution simply unnecessary.
As you consider the DIY approach, will your teams want to sustain costly technical support cycles for throttled results?
In-House Development Costs
Data access layer development relies on a curated roster of specialized tech talent. Each data tool and storage source have unique programming languages that your IT team must speak.
Skill gaps are becoming more frequent as legacy languages retire with their original programmers. While most organizations are in the throes of digital transformation, some industries still rely heavily on systems built upon these languages. For instance, a 2018 Reuters report discovered the over 50-year-old COBOL language as the foundation of 43% of U.S. banking systems.
Organizations now seek to bridge legacy core systems with modern tools, but many modern developers aren’t receiving coursework on dated skill sets. McKinsey notes that 87% of organizations are finding future-ready tech talent scarce, which makes the available talent pool expensive to utilize and hard to keep.
Maintenance and Support Costs
Post-development upkeep of your data integration solution also demands attention from your tech talent — and it gets more complex with time.
Applications alone are increasingly selected in a decentralized fashion. In 2020, HubSpot discovered that enterprise teams use 288 SaaS apps on average. However, each person in the enterprise can contribute to a sum of 21,500 unique app connections — ranging from single-person shadow IT accounts to department-specific operations.
Sources, applications, and tools are constantly being added and modified across your enterprise. Your IT team may never have the ability to fully consolidate its custom data connections to encourage transparency and eliminate shadow IT at this scale. That’s where out-of-the-box connectors come into play.
What to Look for When Buying a Data Access Layer
More organizations are finding that their IT burdens are best offloaded by investing in a fully managed data integration platform.
Standardized data drivers, like those from CData, are connectors that wrap modern integration points (i.e. APIs) inside an SQL layer, making every API speak the same well-known language.
In other words, your apps and tools benefit from universal connectivity. Nearly every application on the market is compatible with these proven standards, and every connection is configured the exact same way. With simple SQL queries, your IT team democratizes data with no extra customization depending on various API models.
Drivers extend data to all corners of your enterprise, whether you’re trying to streamline reporting processes, gain a 360-degree view of customers, improve operations, tightly align Sales and Marketing, and more.
Enterprises use pre-built, standards-based drivers to make their data connections affordable and reliable. Ultimately, data connectivity providers simplify your journey towards making all your diverse tools work together.
Deciding to Build or Buy your Data Access Layer
In summary, upfront costs are just a single factor in deciding to build or buy your data access layer. Your data connectivity solution should:
- Streamline development,
- Help your teams act in real-time,
- Be future-proof,
- Benefit everyone in your organization equally,
- Be sustainable with your existing tech talent, and
- Introduce universal compatibility across all your data touchpoints.
Some teams may still opt for in-house custom builds, but the long-term costs for most will outweigh the benefits. A specialized data integration provider gives your data ecosystem the attention it needs to solve today’s needs and easily scale for tomorrow.
CData Drivers offer the highest-performing standards-based data connectivity solutions available on the market. With connections to over 250 data sources and counting, these drivers are expertly built and maintained around the clock by our team. Your organization will always have access to the data they need when they need it — without any of the maintenance headaches.
If you’d like to learn more about CData Drivers and fuel your decision to buy or build, access our full whitepaper for free.
