While companies continue to hire novice people in the data warehousing field, i.e., IT professionals with three years of experience or less, the set of compliance regulations have significantly increased, thus, giving this field an additional dimension of complexity. This is confirmed by a recent Gartner Research report.
Conventional data warehousing is about extracting, transforming, and loading data from one or several data sources, to attain integration through a variety of staging business processes, an possibly into a data mart. The process of ETL (Extract-Transform-Load) is quite traditional and conveys a set of constraints, such as, in most instances where the transformation is performed row-by-row, such that load can take place. E-LT (Extract-Load-Transform) is a modern approach where customized bulk load can occur without the need to be constrained by individual row-by-row transformations.
Oracle Data Integrator provides support for up to 10000 different concurrent data sources independently from their type, including a variety of structured and unstructured data sources, such as, relational and object relational databases, XML, flat files including csv and tab-delimited among others, various multi-dimensional data sources, message queuing and various other data source types.
Oracle Data Integrator is an ideal data warehousing tool to work with technologies such as Exadata and Oracle Solaris SuperCluster T4-4 (just released), as it provides seamless designing capabilities and transformations through bulk E-LT. Besides, Oracle Data Integrator is quite versatile in interaction with other tools such as Oracle Golden Gate, allowing for fast advanced replication, including both full replication and thin provisioning.
Other important capabilities available with Oracle Data Integrator involve the possibility of performing both complex traditional ETL (Extract-Transformation-Load) and fast bulk E-TL (Extract-Transform-Load). While the former allows row-by-row transformation, the latter allows bulk on-the-fly transformation, for which this stage can essential occur at any time in the datawarehousing timeline. This capability in conjunction with Oracle's demonstrated datawarehousing leadership by quadrant positions ODI as the datawarehousing tool of the future not only for conventional datawarehousing environments but also for the Big Data landscape. This feature also enhances its unique ability to reach optimal data quality while attaining outstanding performance and throughput and minimizing latency.
In addition to this, as part of the Oracle Fusion Middleware, ODI is extremely hot-pluggable. It can friendly interact with Oracle WebLogic, BPEL Process Manager, TopLink, JDeveloper, and Oracle Identity Management.
Concluding Remarks
Oracle Data Integrator is a comprehensive, solid datawarehousing tool that allows the fast and comprehensive, design, implementation, and development of a datawarehousing and reporting datamarts through the appropriate usage of bulk E-LT processing, highly relevant for the Big Data and general datawarehouse performance. Among the top benefits to adopt ODI, it is possible to mentioned reduced DW cost with best ROI, great flexibility, outstanding data quality, and data integrity and accuracy with increased productivity.
