Collecting, integrating, and analyzing data gives your business a complete picture of how it performs. It shows you patterns, trends, and where things break down. But the right data does not always reach the systems that need it.
Most companies use separate tools for separate jobs. CRM systems collect customer and sales data. ERP systems handle accounting and financial data. Without a connection between these systems, your teams work from different versions of the same information. That creates data silos, and data silos cost money.
This article covers the most common data integration problems and solutions, why they persist, and what you need to know to solve them.
Why the need for data integration has grown
Data volumes across enterprises have grown far beyond what any single system was designed to handle. According to the Grand View Research 2025 data integration market report, the global market for data integration tools was valued at $15.18 billion in 2024 and is on track to reach $30.27 billion by 2030. That is a 12.1% annual growth rate. This growth reflects real buying pressure from companies that can no longer manage their data manually.
$12.9 million The average annual cost of poor-quality data for a business, according to Gartner research cited in multiple 2024 industry analyses.
Most companies now run a mix of ERP, CRM, accounting, marketing automation, business intelligence, ecommerce, and SaaS-native tools. Each was purchased to solve a specific problem. The result is that data gets created in many places at once. A 2025 Markets and Markets report on data integration found that over 80% of enterprise data now sits in unstructured formats across disconnected systems, including emails, PDFs, and IoT sensor feeds. Without a connection between your systems, each tool becomes a separate silo that weakens your ability to make accurate decisions.
A 2024 survey from DATAVERSITY, cited in a Cherry Bekaert analysis of data silo costs, found that 68% of organizations list data silos as their top concern. That figure is up 7% from the previous year. The problem is not going away. It is getting bigger.
Integration between your systems gives you one reliable view of your data. That single view is the only solid foundation for business decisions.
Why your data integration project is harder than it looks
Data integration gives you a unified view of your data. But getting there is rarely simple. The complexity of your project grows with three main factors.
- The number of systems you use. Data volumes grow with the number of data sources you have. Some enterprises run hundreds of systems. Some are on-premises. Some are cloud-based. Some are in different regions or different versions. When data lives in that many places, it adds both complexity and security risk to any integration project. More sources also mean more API formats, more data schemas, and more field-mapping work before a single record transfers cleanly.
- The customizations in your systems. Most ERP and CRM implementations include extra development work. Companies add custom modules, fields, and workflows to match how their teams actually operate. This leads to hundreds of non-standard configurations. Those configurations make integration harder because the out-of-the-box connectors may not account for how your system actually stores data. When you add integration on top of a heavily customized system, every custom field is a variable that needs to be mapped.
- A fragmented approach to integration. Building a different point-to-point script for each pair of systems is a mistake. You end up with a web of custom code that no one fully understands. Data must move in an automated and reliable way across all platforms. Without a consistent method, you get errors from inconsistent data and manual entry. Those errors are expensive. They disrupt business operations and erode trust in the data itself.
30% The share of their working week employees spend searching for data trapped across disconnected systems, according to Forrester Consulting research cited in a
Caspio report on the cost of data silos. For a company with 500 employees, that adds up to millions of dollars in lost productivity each year.
Before starting any integration project, you need clear answers to these questions.
- Which business objects need to transfer between systems?
- In which direction should data move, and should it move both ways?
- Do you need real-time data transfer, or are scheduled syncs enough?
- What volumes of data are you moving, and how often do they change?
- Who inside your company owns and supports the integration after it goes live?
- Do you have a data governance policy that defines who can change what?
Getting these answers before you pick a tool will save you significant time and money.
How to solve data integration problems
The path to solving your integration problems starts with two commitments: a strong focus on data quality at both the IT and business level, and close collaboration between those two groups on a shared definition of what good data looks like.
Once you have that foundation, your job is to find the right integration solution. The right solution brings all your systems together and delivers one reliable view of your data. Today, that means choosing a platform built for the way businesses actually operate in 2025, across clouds, on-premises servers, and SaaS applications simultaneously.
Pre-configured iPaaS (Integration Platform as a Service) solutions give you a faster start than custom development. These platforms ship with pre-built connectors, automated workflows, and data mapping tools. According to Gartner's 2024 market share analysis for iPaaS, the market grew 23.4% to $8.5 billion, making it the second-fastest-growing segment in enterprise middleware. That level of market activity means the tools have matured significantly. You are not experimenting with new technology. You are choosing from a field of proven platforms.
Rapidi is one of those platforms. It provides pre-configured connectors built specifically for Salesforce and Microsoft Dynamics 365, including Business Central, Finance, and Dynamics 365 Sales. These connectors are designed to cut implementation time from months to weeks without requiring your team to write custom code.
Before you go live with any integration tool, make sure you have addressed data quality and established a unified approach to data management. Pre-configured solutions work best when your data is clean and your teams agree on what each field means.
How AI is changing data integration in 2025
AI-assisted data integration is no longer experimental. Today, leading iPaaS platforms use machine learning to suggest field mappings, detect errors in data flows, and flag inconsistencies before they reach your business systems.
The business case for connecting your systems to AI is no longer theoretical. A McKinsey technical guide on scaling AI found that 70% of top-performing organizations report difficulties integrating data into AI models. The barriers they cite include data quality problems, unclear governance processes, and insufficient training data. In other words, the AI works. The data plumbing around it does not.
Modern iPaaS platforms are responding to that pressure. They now use machine learning to suggest field mappings, detect errors in data flows, and flag inconsistencies before they reach your business systems. Instead of spending time fixing broken field mappings, your team spends time on design and governance. That shift matters most in complex, multi-system environments where manual mapping is slow and error-prone.
Real-time integration has also become standard practice. Rather than scheduling overnight data syncs, modern tools push data the moment a record changes. For sales and operations teams using Salesforce and Dynamics 365 together, this closes the gap between what the CRM shows and what the ERP holds. Your sales rep sees current inventory. Your finance team sees the same closed deal your sales team does. No lag. No manual reconciliation.
If you are evaluating integration solutions in 2025, ask each vendor how their platform handles real-time triggers, AI-assisted field mapping, and error detection. These are no longer premium features. They are table stakes.
Want to see how Rapidi connects Salesforce and Microsoft Dynamics 365 without custom development?
Frequently Asked Questions: Data integration questions and answers
What is the difference between data integration and data migration?
Data migration is a one-time move. You take data from an old system and transfer it to a new one. Data integration is ongoing. It keeps two or more live systems in sync so that a change in one system automatically updates the other. Most companies need both at different stages. Migration happens when you switch platforms. Integration happens every day after that.
What is an iPaaS solution?
iPaaS stands for Integration Platform as a Service. It is a cloud-based platform that connects different applications and systems without requiring custom code for each connection. iPaaS solutions typically include pre-built connectors, drag-and-drop workflow builders, and automated error handling. They are designed so that IT teams and business users can set up integrations faster than traditional custom development allows.
How long does a data integration project take?
Timeline depends on how many systems you are connecting, how customized those systems are, and whether you use a pre-configured solution or build from scratch. Custom development projects frequently take six months or more. Pre-configured iPaaS solutions with existing connectors, like those Rapidi provides for Salesforce and Dynamics 365, can go live in three to four weeks. The preparation work, data governance and mapping, often takes as long as the technical setup.
What causes data silos in a business?
Data silos form when departments buy tools independently. Sales picks a CRM. Finance picks an ERP. Marketing picks an automation platform. Each tool collects data in its own format and stores it separately. Over time, these systems accumulate records that other systems cannot see. The silo problem gets worse as businesses grow and add more tools without integrating them. See our data integration FAQ for more common questions we hear from teams getting started.
Can I integrate highly customized ERP or CRM systems?
Yes, but it takes more planning. Heavily customized systems require field-by-field mapping to match your custom data structure to the target system. The more customizations you have, the more work goes into mapping before any data moves. This is where pre-configured solutions with flexible mapping tools have a clear advantage over rigid out-of-the-box connectors. A 360-degree customer view is still achievable with a customized CRM, but your integration layer needs to account for every non-standard field.
What is data governance, and why does it matter for integration?
Data governance is the set of rules your organization uses to define who owns which data, who is allowed to change it, and what format it must follow. Without governance, integration projects create new problems. Two systems may sync records that contradict each other because no one agreed on which system is the source of truth. Good governance sets that rule before the first record transfers. It also makes it easier to maintain integrations when staff changes and when your systems get upgraded.
How does real-time data integration differ from batch integration?
Batch integration moves data on a schedule, for example, every night at midnight. Real-time integration moves data the moment a trigger event happens, such as a new order being placed or a contact record being updated. Batch integration is simpler and cheaper to run but leaves a gap between when something happens and when other systems see it. Real-time integration is more complex but gives every system the same current picture. For sales and finance teams sharing a CRM and ERP, real-time sync removes a major source of confusion and manual work.
Where to go from here
Data integration is not a one-time project. It is an ongoing operational decision about how your systems share information. The more clearly you define your data governance, your source-of-truth system, and your integration scope before you start, the smoother the process will be.
If you are working through these decisions now, our Data Integration Handbook covers preparation, best practices, and how to evaluate solutions for your specific environment. It is a practical starting point for teams at any stage of an integration project.
For specific questions about connecting Salesforce and Microsoft Dynamics 365, you get direct answers from our team at Rapidi Open Office Hours. No sales pitch. Just answers.
