Often, a company has data in many different places that can be difficult to find. With data integration solutions, you’ll be able to access all of your data quickly and accurately, without any headaches.

The Definition:

Chances are, if you are running a business, you’ve heard the term “data integration” thrown around. But, what does this buzzword mean?

This process combines data from different sources into a unified view. The process of data integration consolidates your data to create a system that is streamlined and easy to access. The integration process makes your data more accurate/streamlined and gives it a unified structure to your company’s enterprise data sets.

The data integration process uses a variety of techniques to combine business intelligence and raw data from a variety of sources. Data integration tools and software then combine the data together from the master server into a cohesive data set.

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What data integration means for your company

Currently, many companies have data that resides in many different data sources and data lakes. Even if your company has access to all the data it needs, data from disparate sources is often hard to access. It may even need to be manually pulled together before anything can be done with it. That can lead to both a data quality issue and an issue getting real time data performance.

This task is time consuming and can be expensive. Instead, a data integration company, like us, can help you organize and integrate your data from multiple sources. This creates a master server for your data with easy access to your data.

Data integration is one of the main components of data management, which becomes even more important in this digital age. Every day, more and more business apps take to market, creating massive amounts of data. All of this data is stored in massive data warehouses that can be confusing. With the help of data integration, your data is sorted to create better data access for you and your employees.

How does it work?

Data integration works in a variety of ways, all working to move data toward automated integration systems. A variety of techniques are used including the following:

  • Extract, transform and load

Datasets are copied from various sources and gathered together, matched and sorted, and then loaded into a new data warehouse. The new storage solution combines all of your data in one space, making it easier to access all of your data.

  • Extract, load and transform

Similar to extra, transform and load, this process starts by loading all of your data into a big data system. Here, it is then transformed and used at a later date. This technique is best for data that will eventually be used for analytics.

  • Data virtualization

The data virtualization process takes your data and virtually combines data from different systems. This then creates a unified view of the data into a new screen.

  • Data replication

This process takes data from one database and replicates it into other databases. This is done to keep all information synchronized between each data set. Data replication is best used in everyday operation, as well as to ensure all of your data has proper back-ups.

  • Change data capture

Change data capture technologies help to identify all database changes in real-time. In turn, it then applies them into a data warehouse. It tracks any changes that are made within all company intellectual property stored in its data warehouses.

  • Streaming data integration

This is another type of real-time integration. In this process, different streams of data are constantly integrated to form a cohesive data set. The dataset is then fed into your company’s data stores and analytics systems.

In addition to the different techniques and technologies used in data integration. There are also a few different strategies used to integrate your data. The strategy you use is dependent on available resources, need of fulfillment and size of business. All forms of data integration will help create a cohesive view of your data.

There are also many different tools used in the data integration process. The key features you should always look for in data integration tools include:

  • Connectors

The best data integration systems use many connectors. This essentially means that the more pre-build connectors the tool has, the more time your team will save.

  • Open source

Open source structures provide more flexibility while helping to avoid vendor lock-in.

  • Ease of use

Data integration tools should be easy to use and easy to learn. The interface should help make visualizing your data simple.

  • Portability

In the age of the cloud, portability is very important. All data integration done should be able to be used and run anywhere.

  • Cloud compatibility

All data integration should work in the cloud universe, whether it is a single cloud, multi-cloud or hybrid cloud environment.

Inter Operate is the solution your business needs

Like our company name suggests, we use the latest technology to help integrate your data into one master data management system. Our company specializes in making all of your business’s big data work in conjunction with each. We provide you with the ability to seamlessly engage with your data.

Data integration is the key to achieving your company’s full data potential. It is critical for company operations - your employees should have full access to every data set from every source.

Our company partners with various other applications to even better provide data virtualization, cloud data integration and application integration. Check out our website and connect with us to better understand what we do. We can provide your company with vital data integration systems.

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