Data integration challenges refer to anything that prevents you from having complete control over your data integration’s operations and output. To put it plainly, it is considered the impediment to obtaining a single, unified view of your facts. Of course, data integration challenges can be seen in a variety of ways. For instance, data integration issues, data integration problems, etc. However, you must remember that they all refer to the same thing. When processing data at scale and developing your data strategy, it’s critical to come up with the best methods to overcome data integration challenges. In our previous article, ArrowHiTech gave you a comprehensive overview of Data integration. Then, today we will let you know popular data integration challenges you should know. Then, explore with us right now!
Most popular data integration challenges every business need to know
1. You will get a lot of different data formats and sources
In fact, any software from accounting and billing, lead generation tool, email marketing app, CRM to customer support application all collect data from your company.
Besides, different teams use and maintain each of these technologies. And, each of them have their own data inputting and updating methods. Not only that, they could even be entering data that already exists in other programs or in different formats into the system. For example, while one team may enter phone numbers as (00) 666-6666 in one application, another team can enter them as +00 666 6666 in another.
2. Your information isn’t available at necessary places
When this situation happens, your staff wastes a lot of time. Moreover, they also don’t have access to information that could make a huge difference in their work performance. Then, it will cause the second issue that arises as a result of the existence of data silos. For more details, data silos are collections of data that are available to one department but not to the rest of the company. Unfortunately, you will undoubtedly wind up with information silos across your business if there’s no consistency in how, how, and where data is entered and updated.
Now, let’s assume your marketing team is developing a new highly tailored email campaign for your current consumers. Your customer service team has been collecting exactly that kind of data while marketing is debating how to obtain consumer data to produce a more focused campaign. In particular, the marketing team is completely unaware of it. The information is stored in your customer support software, and the marketing tries best hard for ways to obtain it.
3. Your data is poor quality or out of date
One of the most popular data integration challenges is your data is poor quality or out of date.
If your company is without the wide data entry and maintenance standards, you’re bound to wind up with erroneous, obsolete, and/ or duplicate data. In particular, when much of your work still needs to be done manually. In fact, duplicates may occur as a result of various departments entering the same data into different systems. If your staff is required to manually update data on a regular basis, this can result in data input errors or large quantities of data not being updated at all. Not only that, this can also happen if you don’t organize your databases for a long time. Therefore, it will cause the issue of inconsistent and unreliable data. And, once you can’t trust your data, you can’t trust the analysis you derive from it.
4. Utilizing the incorrect integration software for your requirements
One of the data integration challenges is that businesses use the wrong integration software. In many cases, even if you’re already employing integration solutions to connect your software ecosystem, you can still easily use the wrong software for a certain job. Not only that, there are cases where the right software is used incorrectly.
You could, for example, use a trigger-based integration to align the databases of two programs. However, this method just sends data from one platform to another and does not sync historical data (info that was entered into your tools before the interface was set up). Thus, it requires a two-way integration in case you want these databases to be synchronized.
5. The amount of your data is far too much
In fact, there is a limit to how much data you can handle. Hence, if your firm collects data in an indiscriminate manner, you will definitely get a lot of data you don’t need. As a result, it will overshadow the really useful data underneath it. Additionally, if you’re collecting data from various sources without a good data management system in place, this situation becomes even worse. Furthermore, because the data collected everyday is massive. Thus, it is extremely difficult to manage, analyze, and extract value from your data when you can’t discover the signal among the noise.
How to overcome data integration challenges?
1. Clean up and organize your data
Most importantly, before ever considering connecting your software ecosystem, you must first clean up your data. Following that, you need to examine your existing databases and:
- Remove any duplicates
For de-duplicating, you can take advantage of lots of effective programs, one of them is Dedupely. Besides, duplicate scanning and merging may be an option in your applications. Plus, some CRMs and contact management platforms, such as Google Contacts also come with this feature.
- Use advanced tools for scanning outdated or invalid data
Moreover, don’t forget to examine your tools for any data that is obsolete or incorrect. Plus, emails that keep bouncing back on your email marketing platform, phone numbers with improper formats, contacts with misspelled names, and other issues fall into this category. You also need to get rid of this information because they don’t bring any benefit for you.
- Detailed consider the data collection channels you use
If you have a form on a landing page with extraneous information fields, let’s delete them and capture only the data you require. Furthermore, you also ensure that you adhere to data protection policies such as the General Data Protection Regulation (GDPR).
In general, it may take some time to clean up your databases. However, if you do it correctly and then use an integration tool, you will only have to do it once. Taking care of this will improve the overall quality of your data and allow for a smooth and efficient integration process.
2. Establish unambiguous data management procedures
After that, you should introduce company-wide data entry and maintenance standards. Data ownership is a crucial component of this. Because it entails allocating responsibility for the quality and administration of your data to a single team or individual. They will have to make sure that everything that goes into your systems is compliant with corporate policies and strategies. However, if this isn’t an ideal option for your company, you must make sure to train all team members on how to properly input and update data. Plus, you also have to let them know how to link your tools.
Additionally, you may drastically reduce the amount of low-quality, outdated, or duplicate data in your system by implementing company-wide data entry and management policies.
3. Backup your data
Backing up your data is a critical step before moving on to real data integration. However, it is frequently missed. So, you must check with your software vendor to see if your applications already have a backup option. Moreover, you can back it up to the cloud, a local hard disk, or both if you want to be extra safe. Then, you can proceed to the real integration after your data has been cleansed and backed up.
4. Select the appropriate program to help you with data integration
It’s critical to have the correct integration software for your purposes. It will automate a large portion of your data management duties and syncs data amongst your software stack’s applications. As a result, it will substantially reduce the need for human data entry, unifying data formats, and lowering the risk of error.
Besides, it can be said that integration software is the thread that binds everything in your stack together. It makes sure that data flows continuously between apps and that each team has access to the relevant information at the right time.
How to choose data integration solution?
More crucially, in order to select the right integration solution, you have to answer the following questions:
- Firstly, What type of data must be integrated?
- Secondly, Which of your applications, and how, do you need to integrate?
- Thirdly, What should the data flow look like within the company? Do you require a one-way or two-way information flow?
- Finally, Do you require continuous, real-time synchronization or data pushes as a result of a trigger action?
In fact, there are various types of integration platforms that are best suited for certain use cases. For example, you could use in-app integrations provided by your current tools. Not only that, you could use a third-party integration platform or Integration Platform as a Service (iPaaS) provider. Moreover, you will surely make a better decision once you’ve determined exactly what you need from an integration solution. In particular, if you are using a tool that has native integrations that meet all of your needs, that’s a terrific place to start.
But, in case those don’t quite match your needs, why don’t you think about using an iPaaS product? Platforms like Zapier, Tray.io, and Automate.io, which specialize in automating workflows and one-way data pushes are some of the perfect choices. Thanks to them, you can design trigger-action workflows throughout your entire software stack.
5. Manage & maintain your data
These stages we instruct here will assist you in automating large portions of your data management strategy. Plus, it also ensures that your business has consistent, up-to-date, and valuable data. As a result, it enables you to extract far superior insights to make data-driven decisions.
However, data management is a continuous process. For more details, you must check in on your databases on a regular basis to ensure that everything is running smoothly. Not only that, ensuring that your team is following the correct processes, that your existing tools are performing as expected, and that any parts of your strategy need to be updated or adapted. In particular, in case your business is on the period of expanding, your data integration approach will almost certainly need to change as well.
The amount of data is increasing at a quicker rate than ever before, and it is becoming increasingly important to the performance of any company. However, you won’t get the most out of your applications and the data integration until you avoid popular data integration challenges. Hence, the most essential thing is you need to analyze your business goals to see which of these obstacles is keeping you from achieving them.
Above all, AHT Tech JSC hopes that the information in this article will help you realize the most significant data integration challenges and ways to overcome them easily. If you have any questions, let’s fill out our CONTACT FORM to be clearer.