We live in a society driven by data, whether with sports, business, or personal ventures. The beauty of data is that it provides insights that help you achieve new heights in your field. It also allows you to stay ahead of the curve in an ever-changing technological society.
You may have thought about data integration in your field because something is missing. However, you’re not sure where to begin. This guide will break down what it is, the different types, and how it can help you optimize your strategies.
So What Is Data Integration?
Data integration is a strategy used by businesses to improve their overall performance. Sometimes it can be viewed as a hassle because of the depth needed to understand its benefits. But it is necessary for any business looking to compete in their market.
The problem most businesses have is using multiple applications for their needs, whether it’s for accounting, spreadsheets, or asset management. While it may seem productive, there is more opportunity for errors, leading to miscommunication across sectors. As a result, data insights based on these errors could negatively affect a company. With seamless integration, it’ll be easier to optimize performance.
What Are the Different Types of Data Integration?
There are multiple ways to incorporate data usage into your business’s systems. Since each company’s approach will be different, it’s best to figure out which is more conducive to its success. Some of the integration methods include:
- Data Warehousing: Involves using a data warehouse to format and store data; allows analysts to compare consolidated data from multiple sources.
- Middleware Data Integration: Uses a middleware application to format and validate data before sending it to a repository.
- Data Consolidation: Combines data from multiple systems by using ETL software.
- Application-based Integration: Uses software to find, extract, and integrate data; processes data so that different source systems are compatible with the final destination.
How Does Data Integration Work?
When implementing this strategy in your business practices, there are multiple steps to take. But the first is data ingestion, which is moving data from each source system to a central location. Most companies also use an ETL tool which stands for extract, transform, and load. Here’s a quick breakdown of what it does:
- Extract: Connects to data sources with pre-built connectors and removes it.
- Transform: Changes the data and ensures consistency at the destination, regardless of where it originated. The transformation includes formatting changes, validating missing pieces, and applying business rules.
- Load: Once the data has arrived at the destination system, it can be used for analytics and reporting
Are There Challenges With Implementing this Strategy?
When using any new business strategy for the first time, there are bound to be some hiccups. It’s no different when trying to integrate data into your business practices. Some challenges you’ll likely encounter include:
- Exponential data growth: Networks produce data at enormous rates, so you’ll need to have scalable systems in place. Adding physical infrastructure isn’t cost-effective for significant amounts of data. Instead, opt for cloud-based warehouses for more flexibility.
- Trouble integrating different data types: There are various emerging data types; with a flexible system in place, it’ll be easier to gain insights from these types to increase business efficiency.
- Integration intimidation: Integrating data for the first time can be daunting, especially when your data comes from various sources. It seems an overwhelming task, but ideally, you’ll want a strategy that provides data security while simplifying the integration process. Cloud-based tools are best for these applications.
What Are the Benefits of Integration?
Although there are various challenges when integrating data, there are plenty of benefits. For example, if you use an ETL tool, some are:
- Making data easier to understand: The ETL tool breaks data down, making it easier for analysts to use that information for insights.
- Improving collaboration: Employees are in different physical locations and departments; with a unified network, it’ll be easier to collaborate no matter where they are.
- Increasing efficiency: If employees don’t need to access spreadsheet data manually, they can complete tasks with greater efficiency, improving business practices.
- Reducing errors: When there’s no central repository, it’s up to employees to manually handle the data sets to gain insight. This makes human error possible, leading to inaccurate reports. An integration solution keeps data updated, eliminating costly mistakes when it’s time to run reports.
- Improved data quality: Without an optimized system, data quality can be poor, which is why some integration projects fail. Having one in place can enhance your company’s data quality over time.
Take Your Business to New Heights With Better Data Insights
As you can see, data integration is key to increasing your business’s efficiency. While it may present some initial challenges, you’re bound to see its effectiveness in the long term. Think about which type of integration strategy is best for your business. Then implement it with the best practices.
