Computer databases store an endless amount of data for their users. Many companies rely on data warehouses to keep track of all their most essential information located in these data sets. One way of maintaining and incorporating this data into a company’s daily functions is through various strategies of integrating data. There are a wide variety of ways that you can integrate data. We’ll focus on a few of those methods here.
1. Physical Data Integration
With integrating data you’re dealing with the process of combining data from different sources, in the hopes of giving users a unified database. This helps to simplify your business process and to combine data into one database. This ultimately helps the data to move freely in real-time and makes the processing of such data easier for systems and users.
One integration strategy that you can utilize is physical data integration. This occurs when you physically move data from the source system to another staging area. In this area cleansing, mapping, and transformation occur before the raw data is moved to a data warehouse. This data integration process helps those businesses seeking a way to maintain their data quality, while also getting it into a new database.
2. Data Virtualization Approach
Another integration strategy includes the data virtualization approach. This occurs when you use a virtual layer to connect physical data stores. This allows an application to obtain raw data from disparate sources and influence said data without requiring technical details about the data source. Companies use data virtualization for different business processes including consuming raw data through reports, dashboards, portals, and Web applications. Data virtualization is a great integration tool that data software industry leaders such as TIBCO utilize to successfully for their businesses.
3. Extract Transform & Load (ETL)
Extract Transform & Load (ETL) is a data integration process that has a few different steps. First data is physically taken from several source systems. This can include a former database, data warehouse, or some other form of data repository. Once that takes place it’s then changed into a different format. Once this transformation takes place then the big data or raw data is moved into a centralized data store. ETL is but one of many integrations of data strategies that you can employ.
4. Manual Integration of Data
When a data manager is the overseer for every aspect of the data integration process manual integration occurs. This occurs when you connect different data sources, collect the big data, and clean it. This all occurs without the assistance of automation. One benefit you receive from using this method is reduced costs for such application integration. Another benefit includes allowing greater freedom for how you conduct your business processes.
5. Middleware Integration
Another data integration system includes middleware integration. Middleware integration involves software that connects applications and transfers raw data between them and databases like data warehouses. This system allows for better data streaming and easier access between systems. This can be a godsend for companies seeking unfettered and high-performance movement of such data between their systems.
6. Application-Based Integration
This method of integration allows most if not all software applications to handle the workload. Through this data integration system, the software applications receive and integrate data from different sources. When you make the big data compatible through such a method, it makes it that much easier to move data from one data pipeline to a data warehouse.
7. Uniform Access Integration
The great thing about uniform access integration is that it requires lower storage requirements, allows for easier data access, and provides a simplified view of raw data. This method access data from disparate sources of datasets and presents it to users in a uniform fashion. The method of uniform access integration is a great choice for businesses that are seeking a simple method for the delivery of data.
8. Common Storage Integration
Common storage integration involves creating and storing a copy of the data within a data warehouse. When you use this method, you have a bit more flexibility in how your business can manipulate data. This has become a popular form of data integration as a result.
9. Enterprise Data Replication (ELR)
This involves a real-time data consolidation method. The process requires moving data from one storage system to the other. You usually wind up moving one dataset from a database to another database, but they must have the same schema.