Cloud data integration involves gathering data from various applications, websites, and computer systems into a single location. This lets your business tools share information.
Your company can have information about your customers stored in one application, sales in another, and your website’s information elsewhere. Cloud data integration will help combine all of these pieces of information for easy use.
Now let us try to understand it through an example.
Imagine copying data from one Excel sheet to another every day. It consumes a lot of your time, makes you feel bored, and you might even make mistakes while doing it. Cloud data integration helps you get rid of this effort by automatically moving information from different tools to others.
What Is Cloud Data Integration?
Think of different business applications as people speaking different languages. One tool will have information about customers, the other will have sales information, and the third will deal with payments.
There is no information sharing amongst all these applications.
Cloud data integration involves getting all of these tools to collaborate. This will involve the collection of information from different sources and placing it in one system.
The good thing about all this is that it happens through cloud technology. There will be no need for you to invest in expensive computers. You just have to connect and configure your applications, and the cloud platform will take care of the rest.
Why Do Businesses Need Cloud Data Integration?
Every business makes use of numerous applications and tools on a daily basis. All of these applications store data. This can be quite confusing.
Let us say that your sales team has one set of figures and your accounts team has another set. How will you be sure of the right numbers?
Data integration in the cloud helps to get everything sorted out. Everyone is now able to access the same data and work with accurate numbers.
This also means that time is saved since there is no need to transfer data from one application to another manually anymore.
How Cloud Data Integration Functions
The whole process is quite easy. It always has four stages.
Stage 1: Connecting Diverse Software
The first step is connecting the cloud platform to various applications, websites and databases containing your information. The connection can be made to customer management applications, sales software and even to Excel files.
Stage 2: Information Collection
Then, the platform starts collecting information from these diverse sources. This stage is also known as extraction.
Stage 3: Cleaning Information
Sometimes, the information might be stored differently. For instance, dates can have different formats, and the information about the same customers can appear repeatedly.
The platform starts cleaning this information and removing mistakes and duplicates.
Stage 4: Merging Information
In the final stage, the cleaned information is delivered to a particular source, such as a cloud storage solution or a reporting tool.
Now, you can start using the information for reporting, analyzing sales, etc.
Most of these stages occur automatically. After setting everything up, the process of information movement starts to run automatically.
New Terminologies in Cloud Data Integration
While studying cloud data integration, you will probably encounter a variety of new terms that might look scary at first sight, yet they have simple definitions.
ETL (Extract, Transform, Load)
ETL means extracting information, processing it, and moving to its destination.
In other words, a company extracts sales information, processes it by removing mistakes, and stores in a cloud system.
ELT (Extract, Load, Transform)
The process of ELT differs from the ETL process by the sequence of actions.
In other words, first, the company extracts information and loads it into cloud storage. Then, the information is processed and transformed.
This kind of cloud data integration is helpful for companies that deal with large amounts of data.
API-Based Integration
API enables applications to communicate with each other and share information.
In other words, in case an order is placed on a website, order information can be automatically transferred to another app.
Cloud vs Traditional Data Integration
Older integration setups ran on company-owned servers. They worked, but they came with baggage. Here’s how the two approaches compare.
| Factor | Traditional Integration | Cloud Data Integration |
| Setup | Slow, needs hardware | Fast, often within days |
| Cost | High upfront investment | Pay as you go |
| Scaling | Hard and expensive | Easy, grows with you |
| Maintenance | Handled by your IT team | Handled by the provider |
| Access | Usually limited to office networks | Available from anywhere |
| Updates | Manual and occasional | Automatic and regular |
For most growing businesses, the cloud route simply makes more sense. You start small, and you expand when you’re ready.
Key Features of Cloud Data Integration Services
There are plenty of cloud data integration services available on the market. Selecting one is difficult. A couple of easy-to-answer questions will help you choose.
Does it integrate with the solutions you use?
Find if it provides built-in connectors. Developing new connectors is time-consuming and costly.
Is it user-friendly?
If it works only for developers, it means your employees will have difficulty using it. Look for an intuitive interface and good documentation.
Is it scalable?
You will generate more data, and the service should be able to cope with that without increasing its performance time and charging twice as much.
What are its security measures?
Encryption and compliance requirements and user permissions are among key security features. Don’t forget about it.
What kind of support is provided?
At night when something is not working properly, you need a person to speak to.
And finally, don’t forget about the pricing model. It can vary from charging per volume of processed data to charging per connector or per usage.
Common Mistakes to Avoid
Most mistakes stem from being too quick. Just a few things will go a long way in avoiding major headaches.
Don’t begin without setting objectives. What are you hoping to accomplish? Speedier reports? One-stop access to customer information? Goals drive decisions.
Don’t neglect data quality. Tying together bad data merely means more trouble sooner. Clean data first.
Don’t attempt to tie together all of the information at once. Begin by tying two or three key data sources together. Establish that it works, and then scale up.
Finally, don’t overlook the human factor. Any tool is useless if the people using it have no idea how to. Some training really makes a difference.
Getting Started
Firstly, conduct an audit of your systems and see which ones have similar functions and how many gaps you can find in your infrastructure.
Secondly, choose a single challenge to be addressed. For example, you cannot match sales numbers and finance reports. Or your reporting is time-consuming and takes all of your Mondays.
Thirdly, select several cloud data integration platforms, test them, and decide on one. Most of the platforms have a trial or demo period. Test them on your actual data, not just examples.
After you have established a connection with one system, move forward gradually.
Conclusion
Cloud data integration is much more than a technical improvement of your existing infrastructure.
When your systems communicate, you know for sure the state of your business. Reporting becomes simpler, decision-making is faster, and your days become easier. Take it step by step. Choose one issue and integrate two systems.
