11 Data Integration Challenges In The Workplace and How To Solve Them

Email address, credit card info, shipping addresses, username information. Most businesses these days handle a lot of information about every one of us on a daily basis. More than most people realize.

As users alone, we generate roughly 2.5 quintillion bytes of data every day, and in order to keep it contained, companies are investing in big data and artificial intelligence to keep it contained. But while companies are getting really good at containing, not all the businesses are making the most out of the data they have.

Data integration strategies can be very difficult to pull off. Companies not only need to invest in systems and tools to collect data but they need solid framework for processing that data and then analyze it before making any meaningful changes.

Here are some of the common data integration challenges businesses face and how they can be solved:

1. Different Data Formats And Sources

Data is collected in all kinds of places for businesses. Accounting departments will get data through their billing and payable systems, your sales team will get more from their lead generation tools. You’ll also have to deal with the data gathered from your email lists, CRM, and customer service applications, and many others.

With so many sources and overlaying information from multiple teams, you will get redundant information. You’ve also got to contend with people’s own preferences for inputting data as well. For example, some people will input telephone numbers with the area code in parentheses. Others will settle with a plus sign at the front.

That’s a minor issue, but other disparities could become a problem when looking for specific data. A quick solution to this is to ensure that data that’s entered into the system follows a unified format.

2. Data Isn’t Available Where It’s Needed

Are you familiar with business silos? It’s a term that’s used for a group of people – usually those in a department – block other members of the business out for various reasons. It’s all too similar to cliques in high school.

Well, there are also data silos that can be created. This is data that is gathered up in a single department and is isolated from the rest of the organization.

The only time this situation is created is when a company doesn’t know how, who, and where to enter and update data. When there is no unified source, all kinds of data just gets accumulated in specific departments.

What’s worse about these silos though is that other department data could help other departments. For example, say your marketing team wants to put together a personalized email campaign for existing customers. What’ll really help with that campaign would be to get a better understanding of customers’ problems.

The problem is, if that data is in a data silo, marketing will spend more time trying to figure out customer problems or how to get that data rather than working on that campaign.

You can remove silos easily by simply having a focal point for people to update data and communicate that to your team.

3. Access To Low-Quality Or Outdated Data

This problem starts to arise when your data entry and maintenance practices require data to be input manually. Chances become very high that the data input could be inaccurate, out of date, or becomes duplicated.

Again, different departments have their own unique systems which will lead data to be overlapped. Furthermore, if you’re insisting on teams manually updating data occasionally, mistakes can be made or huge amounts of it can be left alone.

These problems also occur if you don’t bother to organize databases.

The data overall could become inconsistent and untrustworthy. And if the data can’t be trusted, any form of analysis can’t be trusted. Fortunately, there a ton of data integration tools to help you, however you’ll still need to be smart about which one to use because…

4. The Data Integration Software Doesn’t Fit Your Needs

Because of this wrinkle. Just selecting randomly your data integration software doesn’t mean all of your worries are over.

A good example of this is looking at trigger-based integration. These systems connect two databases together and merge information together. It sounds nice, but this type of integration doesn’t sync any historical data. This means any data that you’ve gathered before you got this system set up won’t be merged together. Any new data that’s entered in will be fine, but if you have way more historical data, you’ll need another solution. That solution might include two-way integration.

5. You Are Working With Too Much Data

Too much of a good thing can still cause problems and too much data is one of those things. If you’re collecting data indiscriminately, you could find yourself with information that you don’t even need. Worse, it can make it difficult to spot valuable information.

It’s no different to hoarding. If you’re making massive piles, you’ll have a tougher time finding the things you do need and it’ll take a lot of time to find it too.

6. There Are Delays With Data Collection or Latencies

Data these days needs to be processed in real-time or else you’re going to run into accuracy issues and could miss out on meaningful insights. This problem reinforces that requiring manual input for data is a terrible idea as there will be delays in the information gathered in addition to companies not being able to act on the latest information.

7. Data Is Poor Quality

On top of having too much data, there could be a possibility that you’re gathering data that’s really not necessary for your business. In order to determine what you actually need, it’s worth asking yourself questions:

  • How much of this data is worth processing?
  • Is it all useful for the business?
  • What could happen if this data is processed and we make decisions based around it?

It’s important to understand the gravity of the data collected. Fortunately there are tools such data quality management which can deal with unwanted data before you even lay eyes on it.

8. Employees Can’t Understand The Data

Gathering the data is one thing but data is only as useful as the person who is making decisions off of it. Your analysts should have a grasp on the information but if employees lack the proper training or struggle to understand it, then they’re not going to be on board with decisions or struggle to see the point in it.

It’s important for the data to be explained in simple terms that any department can understand and communicate it across departments. Your IT department is going to be very skilled at talking about data and use technical terms. Your accounting department or HR or finance departments aren’t going to have a clue what the IT department is saying.

Having a data integration strategy doesn’t just mean having a focal point for everyone to compile data. It’s also a place for everyone to communicate, leverage, and understand it. So it helps to create a common vocabulary that can be used across the business.

9. Existing Systems Have Other Customizations

Data integration isn’t just something you can slot in and everything will work out fine. Chances are high that the existing systems that you have already have been customized to suit your needs.

When you bring in more tools and software into the mix, you can run into issues. One such issue is the systems may not be compatible with one another or create glitches.

A quick fix to this issue is to ensure the data integration tools provide multiple deployment options. This way if it doesn’t work with one system, it could get data from another system.

10. You Have No Plan Or Approach

An obvious one but it’s still surprising how many companies decide overnight that they want to implement data integration and begin the process. The issue isn’t so simple unless your business is small in size.

Integration doesn’t involve installing a tool and leaving it at that as you can tell thus far. You’ll need to:

  • Understand the ins and outs of your business processes
  • Then create an environment for employees to communicate and learn
  • Only then can you start integrating data from different areas.

And even after that, there is still a lot of careful planning, overcoming all of these other challenges, and ensuring data from the multiple sources are all fine.

11. Data Security

Probably the most glaring challenge that data integration faces is the security of that data. As you may be aware, there have been a ton of attacks from cybercriminals lately. Worse, these attacks aren’t just focusing on big corporations. They’re attacking small startups and everything in between too.

Running into data leaks, breaches or corrupted data can make attacks on systems all the more easier for cybercriminals. And what’s worse is that it could take weeks or months before you realize these tools were creating these issues.

Because of this, you want to ensure that the data integration tool that you’re using does have safety features. One good sign is services offering end-to-end solutions. These measures ensure that authorized employees can access the data and add, delete, or edit it as they wish.

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