Due to the proliferation of application networks in the last two decades, a considerable growth has been witnessed in the database governance roles. It has become quintessential for IT teams to have a fully integrated view of their database. The conventional data management applications lack this ability to share data with other applications in a seamless way. However, companies with robust ETL Tools share heterogeneous and autonomous data fragmentation issues without much effort.
Difficulties with traditional data integration approaches
ETL Tools provide a uniform platform to access and integrate autonomous and heterogeneous data sources. Such tools help in querying disparate data sources, providing support to web-scale data integration, structuring the unstructured data, and accessing data in real time. On the contrary, manual data integration can be strenuous and resource consuming job.
- Heterogeneous Systems: The biggest reason which makes data integration difficult is a network of heterogeneous systems. Imagine a scenario where all your systems are feeding upon the same platform and other data sources relational databases supporting SQL/JDBC. SQL is a query language for relational databases but vendors might have deployed it in a different manner. The manual integration task becomes very difficult because of the discrepancies posed by hybrid application deployments and data fragmentation. And businesses need to overcome these problems if they want to do business with agility and acquire potential partner opportunities.
- Difficulties in Strategy Execution: Manual BI data integration does not solve the real purpose many times. Manually, it is difficult to integrate systems to the smallest level. Considering every point to point integration and creating interconnections requires delicate calibration. Data Integrity Therefore, thorny issues surface to the ground when IT teams try to integrate a Merchandise Management System (MMS) with Salesforce, QuickBooks or any other application.
- Lack of Drill-down Reporting Features: ETL Tools provide data visualization techniques that generate reports about every layer of integration. Such features to refine data elements at the deepest level are not available in the manual integration methods. That’s why it becomes difficult to optimize data with a manual integration approach.
- Lack of adequate know how: Organizations need specifically dedicated teams for migrating their critical data from legacy systems to any other premise. Unfortunately, experts in the field of information solutions and Electronic Data Interchange are very rare. Hence, setting up a team of integration specialists will include a lot of headhunting and recruitment cost as well.