The downside of many relational data warehousing approaches is that they're rigid and hard to change. You start by modeling the data and creating a schema, but this assumes you know all the questions you'll need to answer. When new data sources and new questions arise, the schema and related ETL and BI applications have to be updated, which usually requires an expensive, time-consuming effort.
Enter Hadoop, which lets you store data on a massive scale at low cost (compared with similarly scaled commercial databases). What's more it easily handles variety, complexity and change because you don't have to conform all the data to a predefined schema. ... Read full story on InformationWeek
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