Companies often store data in many different places making it difficult to find when you need it. Data integration solutions make accessing all of your data quickly and accurately a reality, without any headaches.
The Definition:
If you are running a business, chances are you’ve heard the term “data integration” thrown around. But, what exactly does this buzzword mean? What is data integration?
The process of data integration combines data from different sources into a single, unified view.
This process consolidates your data to create a system that is streamlined and easy to access, making your company’s enterprise data sets more accurate and giving them a unified structure.
The data integration process uses a variety of techniques to combine business intelligence and raw data from a variety of sources.
These data integration software and tools then combine all the data together from the master server into one cohesive data set.
What data integration means for your company
Currently, many companies store their data in lots of different data sources and data lakes.
Even if your company has access to all the data it needs, unconnected sources often make this data hard to access.
It may even need to be manually pulled together before anything can be done with it, leading 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 find a centralized solution to organize and integrate your data from multiple sources.
This results in increased accessibility by providing a master server for 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 and create massive amounts of data stored in massive data warehouses that can be confusing.
With the help of data integration, your data is sorted to create seamless access for you and your team.
How Data Integration Works?
Data integration works in a variety of ways, all working to move data toward automated integration systems. These techniques include:
Extract, transform and load
Datasets are copied from various sources, gathered together, matched, sorted, and loaded into a new data warehouse. The new storage solution combines all of your data in one space, making it more accessible.
Extract, load and transform
Similar to extract, transform and load, this process starts by loading all of your data into a large data system where it will be 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 virtually combines your data from different systems. This creates a unified view of the data in a new screen.
Data Replication
This process takes data from one database and replicates it into other databases to keep all your information synchronized between each data set.
Data replication is best used in everyday operation 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. It then applies them into a data warehouse and tracks any changes that are made within 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.
All forms of data integration will help create a cohesive view of your data, but the strategy you use is dependent on your available resources, need of fulfillment, and size of business.
There are 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 multiple connectors. The more pre-built connectors the tool has, the more time your team will save.
Open Source
Open source structures provide increased flexibility while helping to avoid vendor lock-in.
Portability
In the age of the cloud, portability is very important. All data integrations 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.
InterOperate is the solution your business needs
Like our name suggests, we use the latest technology to help integrate your data into one master data management system.
We specialize in making all of your business’s big data work in conjunction with each and provide you with the ability to seamlessly engage with your data.
Data integration is critical for company operations and key to achieving your company’s full potential.
Your team should have full access to every data set from every source.
Our company partners with various other applications to better provide data virtualization, cloud data integration, and application integration.
Check out our website and connect with us to better understand what we do and let us provide your company with vital data integration systems.
