The entire database is copied and recopied again and again, no matter whether the data has changed since the last refresh. Snapshots only involve simple captures of parts of database files, which are comparable to looking at last week's stock market results to trade stock today. Almost immediately after the data is written, it moves straight from the originating database to the data warehouse. Most ETL tools are batch processors, not real-time engines. The larger the data warehouse, the longer it takes to replenish with this method.
Batch processing is both resource intensive and time consuming.
By making incremental updates, users significantly reduce batch window requirements and regain computing time once lost. These kinds of solutions stage the data on a separate server where data transformation and cleansing takes place before moving the data into a data warehouse on another system. This method is quicker, much more resilient, and can provide higher performance especially for very large enterprise data warehouses with high data volumes. Employees, decision-makers, partners, and customers alike need access to information while it is still relevant. With the implementation of real-time business intelligence, your business could be well on its way toward better meeting customer needs and generating a competitive edge in the new economy.