As a side benefit, organizations that optimize their data warehouses using Hadoop can keep their data for longer and can even mine and analyze the data for more advanced and impactful insights. Hadoop-based data also can be combined with logs, social media content, and other unstructured data to gain new analytical insights.
Of course, there’s a certain amount of effort and reengineering to make either of these opportunities a reality. That’s where ETL tools come in. By providing the codeless, visual means to port ETL streams to Hadoop without significant redevelopment, the process becomes that much easier and faster. There are even BI vendor tools that support Hadoop, allowing you to easily migrate analytic models and processes.
Ed. Note: This blog post has been updated from the original in 2014 to reflect additional content.