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5 Challenges in Integrated Data Platforms

Less than 5 min read Minute Read
April 20, 2024
5 Challenges in Integrated Data Platforms

Data is the backbone of any successful business. Organizations must have a strategy in place that prioritizes efficiency and ease when collecting, storing, and analyzing this information. Without this, you can’t expect to make decisions founded on fact. 

That’s where data integration comes in. It combines data from multiple sources across an organization into an accessible, unified dataset. Businesses must understand which parts of their organization are successful in order to tackle the areas that impact efficiency. The only way you can define these areas is by analyzing all of your data. But if you have a larger company, that is easier said than done. Integrated data platforms help to make this possible. 


What is a data integration platform?

A data integration platform is what aids professionals in making data integration successful. When data is flowing through your systems in large quantities from various sources and in different formats, you need someoneor somethingto help manage this information and make it easily digestible. 

In short, it does the trickier tasks of integration that would waste human resources so that they can be better used to analyze the found data and make empowered actions to improve business operations. 

With industries such as AV seeing success in embracing software tools to guide efficiency and scalability, it's safe to assume that others will soon follow suit to improve their data management. 

Businesses must integrate data correctly not only to improve business insights and decision-making, but to importantly maximize customer experience, too. However, that doesn’t mean that it doesn’t come with its own set of challenges. 


The challenges

The reality is that choosing an integration platform that is best for you can in and of itself be a struggle, which is why considering third-party software integrations can give you the flexibility to choose numerous solutions that best suit your business needs. 

However, even if you're armed with the best data integration platform, there are still factors that can challenge the success of your integration. While they might not seem like the end of the world on paper, ignoring these issues can make it impossible to control your data and ultimately waste resources. 

Here are a few things to watch out for to ensure your processes run as smoothly as possible and maximize the potential of your insights. 


Volume of data

Is there such a thing as too much data?

Yes. While data is invaluable to any business, you can easily become overwhelmed and overpowered by the influx of information available if you don’t manage it correctly. Therefore, scalability is crucial to growing businesses, especially when it comes to data integration. 

If your integrated data platform isn’t optimized to handle larger streams of information, you stand to lose sight of vital insights in a sea of useless information. That’s why it’s important to think ahead. Ensuring that your systems are prepared to handle business growth is a smart fix that can streamline integrations down the line. 

What’s more, having an integration solution that grows alongside your company is crucial if you want to manage and extract data that leads to results.  

Cloud-based integration can be a great way to ensure efficiency from the offset, allowing for more resources to be added as your data volume grows. Frameworks such as paas kubernetes are a great option if you want to balance both cloud and physical servers, optimizing systems in response to business needs. 


Quality of data

While having a lot of data to work with can be a virtue, if the quality of this information is poor, it’s likely to make your integration unsuccessful. Not only that, it can lead to lost revenue or damage your reputation if you use it to make business decisions. 

While it can be a simple fix if you’re looking at smaller quantities of data, you can’t rely on human agents to scale masses of data and eliminate repeated and outdated information without some slipping through the net. 

Proactively taking steps early in your data implementation processes, such as data profiling, data cleansing, and data validation, is an easy way to ensure the data that enters your systems is accurate. 

You can also consider additional end-to-end System Integrator software to automatically eliminate duplicated data and streamline efficiency with built-in reporting to measure the success of your activities. However, without a proactive approach from the offset, you stand to miss out on the full potential it can bring to your business operations. 

By managing your data from the start, you minimize the risk of bad data infiltrating your implementation and nip errors in the bud before they can spiral into larger issues. 


Free to use image sourced from Unsplash

Multiple data sources

As the capabilities of the digital world grow, the data that businesses need to collect also grows in quantity. 

While traditional data integrations focused on text-based files, platforms now must be equipped to manage images, device logs, and other customer data such as locational data if you decide to buy a domain with a geographical domain extension. The diversity of data can complicate integrations if you don’t have the correct platform at your disposal. 

Unlike the other challenges we’ve covered so far, the complexity and uniqueness of your data sources require a personalized approach. 

For example, if you’re an e-commerce business, consumer data will be crucial to any business decisions you make in response to your data implementation. 

If your data focuses on customer behaviors and transactional information, customer intelligence systems may help to streamline your data integration. It not only pools all of this data into one place, but it can also manage other aspects of your business-to-customer relationship, such as communication. 

Having this intel can help you to make decisions that meet the needs of your audience. Amid a customer-obsessed culture, having systems in place that improve customer experience (without adding pressure on your human agents to scrutinize every customer touchpoint) is a surefire way to maximize the impact of your insights. 

If you can pinpoint exactly what data channels may cause disruption, whether customer data or image-based information, you can find a solution that processes that specific dataset. Then, your integrated data platform can do what it does best uninterrupted, maximizing efficiency while also ensuring accurate results in all areas. 


Accessibility (or lack of)

One of the advantages of data integration is accessibility. However, it can also be an issue if you don’t have the best practices in place for collecting the data. 

When data isn’t available where and when it needs to be, it can significantly reduce the efficiency of your team, who will now spend more time finding the information they need than coming up with the best way to use it. 

You also run the risk of problematic data silos forming within your business. 

What is a data silo?

A data silo is a collection of information that is accessible to one group within an organization, rather than freely accessible to everyone.

When data isn’t readily accessible, it not only decreases employee productivity, but also limits their performance. In fact, 72% of executives in the manufacturing industry rely on data to maximize productivity. 


That’s why optimizing your integration platform is crucial, as data is collected and processed in a continuous data flow that reaches across your entire business. 

Automated integration tools are an easy fix to ensure everyone who needs it has the most relevant data, without teams having to manually check the accessibility of each piece of data. You can’t expect results without having the data to drive them, after all. 


Incorrect format

If you’re compiling data from a range of applications across your company, there are bound to be inconsistencies in the data collected. 

This is especially true if you combine manual and automated data integration methods. 


We all have individual preferences when noting down information, like whether we add spaces into phone numbers, for example. If each individual in your organization has a different way of formatting and updating data, your integration platform will struggle to merge the data correctly. 

Additionally, if your business uses telephone marketing, with human agents talking directly to potential prospects, you risk damaging the relationship with potential inbound leads if their contact details are not logged correctly. 

While you can stress a company-wide standard for inputting data, there are bound to be cases of human error. Of course, there are measures you can take to eliminate this risk. Making sure your team has the correct VoIP apps available (no matter their location or working environment) is one way to make data entry foolproof. 

Researching into the best esg software for your organization (and the data you collect) is another great way to ensure that all data is correlated in the correct format without relying on human agents to manually correct each error.


What comes next?

Without data integration, businesses would lack the knowledge to make smart and data-driven decisions. That’s why the challenges we’ve explored above should be on your radar when looking at the success of your integrated data platform. 

This is by no means an exhaustive list of what can impact your integration processes, however, if you ensure these issues are eliminated early, you can maximize the potential of your integration platform alongside your business' results.


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