5 Common Cloud-Based Data Integration Challenges & How to Overcome Them

Cloud solutions have become a critical aspect of modern business and IT landscapes, offering convenience, better performance, and cost savings compared to traditional on-premises options. However, migrating to the cloud presents both opportunities and challenges. Therefore, before embarking on a cloud integration project, it is crucial to weigh the pros and cons carefully.

In this article, we will explore the five most common challenges associated with Cloud Integration and provide practical solutions to help you overcome them with ease.


Cloud computing has progressed from a fringe concept to a full-fledged best practice. Without significant security advancements for enterprises of all sizes and industries, the cloud computing revolution would never have occurred. According to the “2019 Cloud Adoption & Risk Report” published by McAfee, more than two-thirds of enterprises now believe cloud apps are as secure as, if not more secure than, on-premises counterparts.

This does not, however, imply that enterprises always adhere to cloud security best practices. According to the same report, only 20% of firms use a cloud data loss prevention solution. Another 2019 poll of IT security specialists discovered that 84 percent of firms find maintaining security configurations across cloud services “very difficult” or “somewhat difficult.”

SolutionWhile the cloud is generally more secure than on-premises, businesses must still take care to manage cloud risk and compliance. A robust cloud security solution must incorporate user identity and authorization, data encryption, and backup and recovery features.

Network Latency

Cloud-based solutions have become increasingly popular due to their scalability, but network latency can be a common challenge. According to a study by Cisco, the average round-trip latency for cloud-based applications is 100 milliseconds.

Hybrid clouds use wide-area networks (WANs) instead of local area networks (LANs). However, WANs can become congested if too many short, uncompressed data packets are sent via a remote database connection, overburdening the network.

SolutionOne solution is to utilize content delivery networks (CDNs), such as Akamai, Cloudflare, or Amazon CloudFront, which help to minimize network latency by caching content closer to users. However, this might impact data freshness, and might not be useful for “Write” or ”Update” operations. Another approach is to use software-defined wide area networks (SD-WANs), which optimize network traffic by directing it through multiple links and reducing the need for expensive dedicated WAN connections. Additionally, companies can leverage cloud-based integration platforms, such as Boomi or Make or MuleSoft, which can provide multiple geographies for their Cloud, reducing latency and improving data transfer speeds.

Moreover, from design pattern perspective, it is key to optimize the data flows to have low data footprint, by for example using Delta instead of Full data transfers, so that usage of bandwidth is limited to the “just enough”.

Selecting the Right Architecture

It is critical to choose the right architecture for your cloud environment. Most businesses have three alternatives to choose from:

  • A public cloud is provided by a third-party cloud provider, such as Amazon Web Services, Google Cloud Platform or Microsoft Azure.
  • A private cloud is used “privately” by one organization (but obviously more expensive than public alternatives).
  • A hybrid cloud is one that incorporates elements of both public and private clouds.

What’s more, according to a report by Flexera, 93% of enterprises now use a “multi-cloud” strategy, in which they use services from several cloud vendors (for example, different vendors for cloud computing, storage, and software).

SolutionUsing two or more cloud solutions would require seamless integration of data and services from various providers, resulting in a single, coherent cloud ecosystem. Make sure you understand the APIs and connectors required for your cloud architecture of choice, including whether you need to design your own solution.

In case of hybrid architecture, , you can think of Boomi, as it offers a cloud-native integration platform that can connect any combination of cloud and on-premises applications, without compromising on security.

Data Governance Issues

Cloud integrations transfer large amounts of data. How can you ensure that data quality is maintained while adhering to IT regulations and procedures?

“Data governance” refers to the data management policies that ensure your organization’s data’s high availability, integrity, and usability. Unfortunately, many organizations fail to create a good data governance plan as they migrate to the cloud. As a result, any new integration across disparate systems may generate new challenges and sites of failure. Furthermore, as your cloud environment expands in size, manually monitoring these integration points becomes increasingly impractical.

SolutionAny proposal to migrate to the cloud must be accompanied by a solid data governance plan. For example, automation is becoming increasingly crucial in many firms’ data governance initiatives to aid in the detection of possible integration difficulties. Each record should be allocated to a “data owner” who is responsible for the asset’s quality. You should also clearly outline policies for which data types can be integrated or combined, as well as how to assure subsequent security, confidentiality and integrity.

Choosing Custom vs. Pre-Built Solutions

When it comes to addressing cloud integration challenges, the focus is shifting from whether to consider them to what solutions to use. As 92% of organizations opt for a multi-cloud approach, choosing between custom-built and pre-built cloud data connections becomes a crucial decision. But it’s not always an either/or situation, as you can utilize both options for different integrations within a single cloud environment.

SolutionBoth custom and pre-built cloud integration solutions have advantages and disadvantages. Although custom-built connectors are time-consuming and costly, they may be required for highly unique use cases or legacy tools with the information system. Pre-built solutions, on the other hand, are highly handy, supported by vendor and cost-effective, but they may not work for every possible integration you need to perform. Before deciding where to deploy either option, be sure you grasp its benefits and capabilities.

If you are looking for a Data Integration Solution, you can check our complete Guide.

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