Successful data integration requires data to be collected and combined from various sources that may use conflicting systems and technologies. Data integration is commonly used independent companies merge or when multiple applications are consolidated together.
Understand Data Migration
The basic principles of data migration must be understood because this key process involves digitally transferring data from one storage, database or application to another. Data migration offers three possibilities: merging separate systems, migrating systems or leaving systems intact in order to create a virtual data warehouse. Data migration often involves three steps: extract, transform and load (ETL). The middle step is sometimes skipped for compatible systems, but data migration always requires extraction and loading. Data migrations typically occur during platform, software or hardware upgrades. For example, when a company migrates from a traditional server system to a cloud-based storage system.
Every data integration project must be carefully discussed and strategically planned. Ideally, data integration projects will start within management, not IT departments. However, the management team must have an IT expert who understands the company’s systems and data assets. This individual will provide expert advice and lead the discussion on long-term data integration initiative. They will ask probing questions about system requirements and data sourcing as well as project objectives, deliverables and timetables. During the project design phase, the team must verify what the data extraction options are, such as full vs. incremental extracts, and what extraction limitations exist. They must also know if populated data fields are consistent and standardized.
Based on the project scope, a feasibility study should be conducted to select the appropriate tools to implement the data integration process. Small businesses with limited data infrastructure must carefully select the tools they will need because these choices may become permanent solutions. Large companies with previous data integration and migration experience can take advantage of existing systems and knowledge. There are occasional times when even large businesses will need to upgrade to a better platform or technology that is better suited to effectively handle operations. Therefore, when selecting the data migration and integration tools, be sure to choose one that provides adequate scaling for future expansion. The best solution will lower support, licensing and migration costs.
Helpful Data Integration Techniques
There are several proven ways to increase the effectiveness of data integration projects. First, application based integration will require the end users to fully support all the integration efforts. Second, any data integration that involves logic transfers should be based on the original application. Third, virtual integration may appear as easy solutions because they leave data intact in the source systems, but they may limit history tracking and version management. Finally, technical information that must be gathered includes the backup policy, system response time, number of users and data processing windows.
The final step to successfully integrate data requires awareness of application bugs, business needs and user preferences.